Welcome to the reference page!

Here you will be able to find all references for the original pieces, literature thesis and articles published in the ABC Journal from issue 10 onward.

Protect the planet 🌱

Table of Contents

Issue 14

Wearable (Neuro)Technology: Promises and challenges

Ahn, J. W., Ku, Y., & Kim, H. C. (2019). A novel wearable EEG and ECG recording system for stress assessment. Sensors (Switzerland), 19(9). https://doi.org/10.3390/S19091991

Bagot, K. S., Matthews, S. A., Mason, M., Squeglia, L. M., Fowler, J., Gray, K., Herting, M., May, A., Colrain, I., Godino, J., Tapert, S., Brown, S., & Patrick, K. (2018). Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health. Developmental Cognitive Neuroscience, 32, 121–129. https://doi.org/10.1016/J.DCN.2018.03.008

Billeci, L., Tonacci, A., Tartarisco, G., Narzisi, A., Palma, S. Di, Corda, D., Baldus, G., Cruciani, F., Anzalone, S. M., Calderoni, S., Pioggia, G., & Muratori, F. (2016). An integrated approach for the monitoring of brain and autonomic response of children with Autism Spectrum Disorders during treatment by wearable technologies. Frontiers in Neuroscience, 10(JUN), 276. https://doi.org/10.3389/FNINS.2016.00276/BIBTEX

Cannard, C., Wahbeh, H., & Delorme, A. (2021). Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System. Frontiers in Human Neuroscience, 15, 736. https://doi.org/10.3389/FNHUM.2021.745135/BIBTEX

Cartocci, G., Rossi, D., Modica, E., Maglione, A. G., Martinez Levy, A. C., Cherubino, P., Canettieri, P., Combi, M., Rea, R., Gatti, L., & Babiloni, F. (2021). NeuroDante: Poetry Mentally Engages More Experts but Moves More Non-Experts, and for Both the Cerebral Approach Tendency Goes Hand in Hand with the Cerebral Effort. Brain Sciences, 11(3), 1–25. https://doi.org/10.3390/BRAINSCI11030281

Coates McCall, I., Lau, C., Minielly, N., & Illes, J. (2019). Owning Ethical Innovation: Claims about Commercial Wearable Brain Technologies. Neuron, 102(4), 728–731. https://doi.org/10.1016/J.NEURON.2019.03.026

Frijia, E. M., Billing, A., Lloyd-Fox, S., Vidal Rosas, E., Collins-Jones, L., Crespo-Llado, M. M., Amadó, M. P., Austin, T., Edwards, A., Dunne, L., Smith, G., Nixon-Hill, R., Powell, S., Everdell, N. L., & Cooper, R. J. (2021). Functional imaging of the developing brain with wearable high-density diffuse optical tomography: A new benchmark for infant neuroimaging outside the scanner environment. NeuroImage, 225, 117490. https://doi.org/10.1016/J.NEUROIMAGE.2020.117490

Goldstein-Piekarski, A. N., Holt-Gosselin, B., O’Hora, K., & Williams, L. M. (2019). Integrating sleep, neuroimaging, and computational approaches for precision psychiatry. Neuropsychopharmacology 2019 45:1, 45(1), 192–204. https://doi.org/10.1038/s41386-019-0483-8

Hielscher, A. H., Bluestone, A. Y., Abdoulaev, G. S., Klose, A. D., Lasker, J., Stewart, M., Netz, U., & Beuthan, J. (2002). Near-infrared diffuse optical tomography. Disease Markers, 18(5–6), 313–337. https://doi.org/10.1155/2002/164252

Jonasdottir, S. S., Minor, K., & Lehmann, S. (2021). Gender differences in nighttime sleep patterns and variability across the adult lifespan: a global-scale wearables study. Sleep, 44(2), 1–16. https://doi.org/10.1093/SLEEP/ZSAA169

Mota-Rolim, S. A., Pavlou, A., Nascimento, G. C., Fontenele-Araujo, J., & Ribeiro, S. (2019). Portable devices to induce lucid dreams-are they reliable? Frontiers in Neuroscience, 13(MAY), 428. https://doi.org/10.3389/FNINS.2019.00428/BIBTEX

Salchow-Hömmen, C., Skrobot, M., Jochner, M. C. E., Schauer, T., Kühn, A. A., & Wenger, N. (2022). Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders. Frontiers in Human Neuroscience, 16, 11. https://doi.org/10.3389/FNHUM.2022.768575/BIBTEX

Schofield, D. (2021, January 5). Lucid dreamers are using unproven tech to hack their sleep. Wired UK. https://www.wired.co.uk/article/lucid-dreaming-tech

The Wearable Market Will See 344.9 Million Shipments in 2022 With Sports, Fitness, and Wellness Trackers Leading the Way. (2022, January 27). ABI Research. https://www.abiresearch.com/press/the-wearable-market-will-see-3449-million-shipments-in-2022-with-sports-fitness-and-wellness-trackers-leading-the-way/

Wearable tech set to become a $54bn industry by 2023. (2019, August 7). GlobalData. https://www.globaldata.com/wearable-tech-set-to-become-a-54bn-industry-by-2023/

Wexler, A., & Reiner, P. B. (2019). Oversight of direct-to-consumer neurotechnologies: Efficacy of products is far from clear. Science (New York, N.Y.), 363(6424), 234. https://doi.org/10.1126/SCIENCE.AAV0223

Wexler, A., & Thibault, R. (2018). Mind-Reading or Misleading? Assessing Direct-to-Consumer Electroencephalography (EEG) Devices Marketed for Wellness and Their Ethical and Regulatory Implications. Journal of Cognitive Enhancement 2018 3:1, 3(1), 131–137. https://doi.org/10.1007/S41465-018-0091-2

Wheelock, M. D., Culver, J. P., & Eggebrecht, A. T. (2019). High-density diffuse optical tomography for imaging human brain function. Review of Scientific Instruments, 90(5), 051101. https://doi.org/10.1063/1.5086809


Experimental Amimals in Neuroscience

Ahn, J. W., Ku, Y., & Kim, H. C. (2019). A novel wearable EEG and ECG recording system for stress assessment. Sensors (Switzerland), 19(9). https://doi.org/10.3390/S19091991

Bagot, K. S., Matthews, S. A., Mason, M., Squeglia, L. M., Fowler, J., Gray, K., Herting, M., May, A., Colrain, I., Godino, J., Tapert, S., Brown, S., & Patrick, K. (2018). Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health. Developmental Cognitive Neuroscience, 32, 121–129. https://doi.org/10.1016/J.DCN.2018.03.008

Billeci, L., Tonacci, A., Tartarisco, G., Narzisi, A., Palma, S. Di, Corda, D., Baldus, G., Cruciani, F., Anzalone, S. M., Calderoni, S., Pioggia, G., & Muratori, F. (2016). An integrated approach for the monitoring of brain and autonomic response of children with Autism Spectrum Disorders during treatment by wearable technologies. Frontiers in Neuroscience, 10(JUN), 276. https://doi.org/10.3389/FNINS.2016.00276/BIBTEX

Cannard, C., Wahbeh, H., & Delorme, A. (2021). Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System. Frontiers in Human Neuroscience, 15, 736. https://doi.org/10.3389/FNHUM.2021.745135/BIBTEX

Cartocci, G., Rossi, D., Modica, E., Maglione, A. G., Martinez Levy, A. C., Cherubino, P., Canettieri, P., Combi, M., Rea, R., Gatti, L., & Babiloni, F. (2021). NeuroDante: Poetry Mentally Engages More Experts but Moves More Non-Experts, and for Both the Cerebral Approach Tendency Goes Hand in Hand with the Cerebral Effort. Brain Sciences, 11(3), 1–25. https://doi.org/10.3390/BRAINSCI11030281

Coates McCall, I., Lau, C., Minielly, N., & Illes, J. (2019). Owning Ethical Innovation: Claims about Commercial Wearable Brain Technologies. Neuron, 102(4), 728–731. https://doi.org/10.1016/J.NEURON.2019.03.026

Frijia, E. M., Billing, A., Lloyd-Fox, S., Vidal Rosas, E., Collins-Jones, L., Crespo-Llado, M. M., Amadó, M. P., Austin, T., Edwards, A., Dunne, L., Smith, G., Nixon-Hill, R., Powell, S., Everdell, N. L., & Cooper, R. J. (2021). Functional imaging of the developing brain with wearable high-density diffuse optical tomography: A new benchmark for infant neuroimaging outside the scanner environment. NeuroImage, 225, 117490. https://doi.org/10.1016/J.NEUROIMAGE.2020.117490

Goldstein-Piekarski, A. N., Holt-Gosselin, B., O’Hora, K., & Williams, L. M. (2019). Integrating sleep, neuroimaging, and computational approaches for precision psychiatry. Neuropsychopharmacology 2019 45:1, 45(1), 192–204. https://doi.org/10.1038/s41386-019-0483-8

Hielscher, A. H., Bluestone, A. Y., Abdoulaev, G. S., Klose, A. D., Lasker, J., Stewart, M., Netz, U., & Beuthan, J. (2002). Near-infrared diffuse optical tomography. Disease Markers, 18(5–6), 313–337. https://doi.org/10.1155/2002/164252

Jonasdottir, S. S., Minor, K., & Lehmann, S. (2021). Gender differences in nighttime sleep patterns and variability across the adult lifespan: a global-scale wearables study. Sleep, 44(2), 1–16. https://doi.org/10.1093/SLEEP/ZSAA169

Mota-Rolim, S. A., Pavlou, A., Nascimento, G. C., Fontenele-Araujo, J., & Ribeiro, S. (2019). Portable devices to induce lucid dreams-are they reliable? Frontiers in Neuroscience, 13(MAY), 428. https://doi.org/10.3389/FNINS.2019.00428/BIBTEX

Salchow-Hömmen, C., Skrobot, M., Jochner, M. C. E., Schauer, T., Kühn, A. A., & Wenger, N. (2022). Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders. Frontiers in Human Neuroscience, 16, 11. https://doi.org/10.3389/FNHUM.2022.768575/BIBTEX

Schofield, D. (2021, January 5). Lucid dreamers are using unproven tech to hack their sleep. Wired UK. https://www.wired.co.uk/article/lucid-dreaming-tech

The Wearable Market Will See 344.9 Million Shipments in 2022 With Sports, Fitness, and Wellness Trackers Leading the Way. (2022, January 27). ABI Research. https://www.abiresearch.com/press/the-wearable-market-will-see-3449-million-shipments-in-2022-with-sports-fitness-and-wellness-trackers-leading-the-way/

Wearable tech set to become a $54bn industry by 2023. (2019, August 7). GlobalData. https://www.globaldata.com/wearable-tech-set-to-become-a-54bn-industry-by-2023/

Wexler, A., & Reiner, P. B. (2019). Oversight of direct-to-consumer neurotechnologies: Efficacy of products is far from clear. Science (New York, N.Y.), 363(6424), 234. https://doi.org/10.1126/SCIENCE.AAV0223

Wexler, A., & Thibault, R. (2018). Mind-Reading or Misleading? Assessing Direct-to-Consumer Electroencephalography (EEG) Devices Marketed for Wellness and Their Ethical and Regulatory Implications. Journal of Cognitive Enhancement 2018 3:1, 3(1), 131–137. https://doi.org/10.1007/S41465-018-0091-2

Wheelock, M. D., Culver, J. P., & Eggebrecht, A. T. (2019). High-density diffuse optical tomography for imaging human brain function. Review of Scientific Instruments, 90(5), 051101. https://doi.org/10.1063/1.5086809


Aerts, L., Miccoli, B., Delahanty, A., Witters, H., Verstraelen, S., De Strooper, B., Braeken, D., & Verstreken, P. (2022). Do we still need animals? Surveying the role of animal-free models in Alzheimer’s and Parkinson’s disease research. The EMBO Journal, 41(6), e110002. https://doi.org/10.15252/embj.2021110002


ALURES – European Commission. (n.d.). Retrieved 2 October 2022, from https://webgate.ec.europa.eu/envdataportal/content/alures/section1_number-of-animals.html


Bourin, M., Petit-Demoulière, B., Nic Dhonnchadha, B., & Hascöet, M. (2007). Animal models of anxiety in mice. Fundamental & Clinical Pharmacology, 21(6), 567–574. https://doi.org/10.1111/j.1472-8206.2007.00526.


Cummings, J., Lee, G., Nahed, P., Kambar, M. E. Z. N., Zhong, K., Fonseca, J., & Taghva, K. (2022). Alzheimer’s disease drug development pipeline: 2022. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 8(1), e12295. https://doi.org/10.1002/trc2.12295


Dragunsky, E., Chernokhvostova, Y., Taffs, R., Chumakov, K., Gardner, D., Asher, D., Nomura, T., Hioki, K., & Levenbook, I. (1997). TgPVR21 mice for testing type-3 oral poliovirus vaccines: Role of clinical observation and histological examination. Vaccine, 15(17), 1863–1866. https://doi.org/10.1016/S0264-410X(97)00142-4


Ellenbroek, B., & Youn, J. (2016). Rodent models in neuroscience research: Is it a rat race? Disease Models & Mechanisms, 9(10), 1079–1087. https://doi.org/10.1242/dmm.026120


Ferreira, G. S., Veening-Griffioen, D. H., Boon, W. P. C., Moors, E. H. M., & van Meer, P. J. K. (2020). Levelling the Translational Gap for Animal to Human Efficacy Data. Animals : An Open Access Journal from MDPI, 10(7), 1199. https://doi.org/10.3390/ani10071199


Ferreira, G. S., Veening-Griffioen, D. H., Boon, W. P. C., Moors, E. H. M., Wied, C. C. G., Schellekens, H., & Meer, P. J. K. van. (2019). A standardised framework to identify optimal animal models for efficacy assessment in drug development. PLOS ONE, 14(6), e0218014. https://doi.org/10.1371/journal.pone.0218014


Zay, M., Thomas, D. W., Craighead, J. L., Economides, C., & Rosenthal, J. (2014). Clinical development success rates for investigational drugs. Nature Biotechnology, 32(1), 40–51. https://doi.org/10.1038/nbt.2786


Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., Yao, Z., Eggermont, J., Höllt, T., Levi, B. P., Shehata, S. I., Aevermann, B., Beller, A., Bertagnolli, D., Brouner, K., … Lein, E. S. (2019). Conserved cell types with divergent features in human versus mouse cortex. Nature, 573(7772), 61–68. https://doi.org/10.1038/s41586-019-1506-7


Hubrecht, R. C., & Carter, E. (2019). The 3Rs and Humane Experimental Technique: Implementing Change. Animals : An Open Access Journal from MDPI, 9(10), 754. https://doi.org/10.3390/ani9100754


Knopman, D. S., Jones, D. T., & Greicius, M. D. (2021). Failure to demonstrate efficacy of aducanumab: An analysis of the EMERGE and ENGAGE trials as reported by Biogen, December 2019. Alzheimer’s & Dementia, 17(4), 696–701. https://doi.org/10.1002/alz.12213


Ma, C., Peng, Y., Li, H., & Chen, W. (2021). Organ-on-a-Chip: A New Paradigm for Drug Development. Trends in Pharmacological Sciences, 42(2), 119–133. https://doi.org/10.1016/j.tips.2020.11.009


Mak, I. W., Evaniew, N., & Ghert, M. (2014). Lost in translation: Animal models and clinical trials in cancer treatment. American Journal of Translational Research, 6(2), 114–118.


Miller, P. G., & Shuler, M. L. (2016). Design and demonstration of a pumpless 14 compartment microphysiological system. Biotechnology and Bioengineering, 113(10), 2213–2227. https://doi.org/10.1002/bit.25989


Mouse Genome Sequencing Consortium, Waterston, R. H., Lindblad-Toh, K., Birney, E., Rogers, J., Abril, J. F., Agarwal, P., Agarwala, R., Ainscough, R., Alexandersson, M., An, P., Antonarakis, S. E., Attwood, J., Baertsch, R., Bailey, J., Barlow, K., Beck, S., Berry, E., Birren, B., … Lander, E. S. (2002). Initial sequencing and comparative analysis of the mouse genome. Nature, 420(6915), 520–562. https://doi.org/10.1038/nature01262


Pound, P., & Ritskes-Hoitinga, M. (2018). Is it possible to overcome issues of external validity in preclinical animal research? Why most animal models are bound to fail. Journal of Translational Medicine, 16(1), 304. https://doi.org/10.1186/s12967-018-1678-1


Prior, H., Baldrick, P., de Haan, L., Downes, N., Jones, K., Mortimer-Cassen, E., & Kimber, I. (2018). Reviewing the Utility of Two Species in General Toxicology Related to Drug Development. International Journal of Toxicology, 37(2), 121–124. https://doi.org/10.1177/1091581818760564


Prior, H., Haworth, R., Labram, B., Roberts, R., Wolfreys, A., & Sewell, F. (2020). Justification for species selection for pharmaceutical toxicity studies. Toxicology Research, 9(6), 758–770. https://doi.org/10.1093/toxres/tfaa081


Russell, W. M. S., & Burch, R. L. (1959). The Principles of Humane Experimental Technique. Methuen.


Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062. https://doi.org/10.1016/j.apsb.2022.02.002


Ueno, H., Suemitsu, S., Murakami, S., Kitamura, N., Wani, K., Okamoto, M., Matsumoto, Y., Aoki, S., & Ishihara, T. (2018). Empathic behavior according to the state of others in mice. Brain and Behavior, 8(7), e00986. https://doi.org/10.1002/brb3.986


van den Berg, A., Mummery, C. L., Passier, R., & van der Meer, A. D. (2019). Personalised organs-on-chips: Functional testing for precision medicine. Lab on a Chip, 19(2), 198–205. https://doi.org/10.1039/c8lc00827b


Wieschowski, S., Chin, W. W. L., Federico, C., Sievers, S., Kimmelman, J., & Strech, D. (2018). Preclinical efficacy studies in investigator brochures: Do they enable risk–benefit assessment? PLoS Biology, 16(4), e2004879. https://doi.org/10.1371/journal.pbio.2004879


Würbel H. (2017). More than 3Rs: the importance of scientific validity for harm-benefit analysis of animal research. Lab animal, 46(4), 164–166. https://doi.org/10.1038/laban.1220



Categorising Mental Disorders: Phenomenology as an Alternative Approach

Ahmad, I., Khalily, M. T., & Hallahan, B. (2017). Reasons associated with treatment non-adherence in schizophrenia in a Pakistan cohort. Asian journal of psychiatry, 30, 39-43.


Alves, B. L. M., Hidalgo, C. R., Pamplona, R. A. C., da Conceição Sanches, L., & Ribeiro, E. R. (2020). Factors that Change the Quality of Life of Patients with Schizophrenia: A Systematic. International Journal, 8(2), 9-19.


American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).


American Psychological Association. (2013, May 3). Statement by David Kupfer, MD. [Press release]. Retrieved from https://www.madinamerica.com/wp-content/uploads/2013/05/Statement-from-dsm-chair-david-kupfer-md.pdf


Andreasen, N. C. (2007). DSM and the death of phenomenology in America: an example of unintended consequences. Schizophrenia bulletin, 33(1), 108-112.


Arnaud, S. (2020). Self-consciousness in autism: A third-person perspective on the self. Mind & Language, 1-17.


Bleuler E. (1911). Dementia Praecox oder Gruppe der Schizophrenien. Leipzig, Germany.


Caplan, P. J. (1995). They say you’re crazy: How the world’s most powerful psychiatrists decide who’s normal. Addison-Wesley/Addison Wesley Longman.


Daly, A., & Gallagher, S. (2019). Towards a phenomenology of self-patterns in psychopathological diagnosis and therapy. Psychopathology, 52(1), 33-49.


De Crescenzo, F., Postorino, V., Siracusano, M., Riccioni, A., Armando, M., Curatolo, P., & Mazzone, L. (2019). Autistic symptoms in schizophrenia spectrum disorders: a systematic review and meta-analysis. Frontiers in psychiatry, 10, 1-11.


Drożdżowicz, A. (2020). Increasing the Role of Phenomenology in Psychiatric Diagnosis – The Clinical Staging Approach. In The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine, 45(6), 683-702.


Dupré, J. (2001). In defence of classification. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 32(2), 203-219.


Dupré, J. (2006). Scientific classification. Theory, culture & society, 23(2-3), 30-32.


Ereshefsky, M. (1994). Pluralism, normative naturalism, and biological taxonomy. In PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 2, 382-389.


Ferri, F., Frassinetti, F., Mastrangelo, F., Salone, A., Ferro, F. M., & Gallese, V. (2012). Bodily self and schizophrenia: the loss of implicit self-body knowledge. Consciousness and cognition, 21(3), 1365-1374.


First. (2005). Mutually Exclusive versus Co-Occurring Diagnostic Categories: The Challenge of Diagnostic Comorbidity. Psychopathology, 38(4), 206–210.


Fuchs, T. 2015. Pathologies of intersubjectivity in autism and schizophrenia. Journal of Consciousness Studies, 22(1-2), 191-214.


Gureje, O., & Stein, D. J. (2012). Classification of mental disorders: the importance of inclusive decision-making. International Review of Psychiatry, 24(6), 606-612.


Haag, G., Tordjman, S., Duprat, A., Urwand, S., Jardin, F., Cukierman, A., … & Dumont, A. M. (2005). Psychodynamic assessment of changes in children with autism under psychoanalytic treatment. The International Journal of Psychoanalysis, 86(2), 335-352.


Howes, O. D., McCutcheon, R., Agid, O., De Bartolomeis, A., Van Beveren, N. J., Birnbaum, M. L., … & Correll, C. U. (2017). Treatment-resistant schizophrenia: treatment response and resistance in psychosis (TRRIP) working group consensus guidelines on diagnosis and terminology. American Journal of Psychiatry, 174(3), 216-229.


Huffman, L. C., Sutcliffe, T. L., Tanner, I. S., & Feldman, H. M. (2011). Management of symptoms in children with autism spectrum disorders: a comprehensive review of pharmacologic and complementary-alternative medicine treatments. Journal of Developmental & Behavioral Pediatrics, 32(1), 56-68.


Jääskeläinen, E., Juola, P., Hirvonen, N., McGrath, J. J., Saha, S., Isohanni, M., … & Miettunen, J. (2013). A systematic review and meta-analysis of recovery in schizophrenia. Schizophrenia bulletin, 39(6), 1296-1306.


Jablensky, A. (1988). Methodological issues in psychiatric classification. The British Journal of Psychiatry, 152, 15–20.


Jablensky, A., & Kendell, R. E. (2002). Criteria for assessing a classification in psychiatry. Psychiatric diagnosis and classification, 1.

Jablensky, A., & Kendell, R. E. (2002). Criteria for assessing a classification in psychiatry. Psychiatric diagnosis and classification, 1.


Kanner, L. (1943). Autistic disturbances of affective contact. Nervous child, 2(3), 217-250.


Kendler, K. S. (2016). The phenomenology of major depression and the representativeness and nature of DSM criteria. American Journal of Psychiatry, 173(8), 771-780.


Kretchy, I. A., Osafo, J., Agyemang, S. A., Appiah, B., & Nonvignon, J. (2018). Psychological burden and caregiver-reported non-adherence to psychotropic medications among patients with schizophrenia. Psychiatry research, 259, 289-294.


Lempérière, T. (1995). The importance of classifications in psychiatry. L’encephale, 21, 3-7.


Lynch, T. (2018). The Validity of the DSM: An overview. The Irish Journal of Counselling and Psychotherapy, 18(2), 5-10.


Masi, Mucci, M., & Pari, C. (2006). Children with Schizophrenia: Clinical Picture and Pharmacological Treatment. CNS Drugs, 20(10), 841–866.


Matson, J. L., Sipes, M., Fodstad, J. C., & Fitzgerald, M. E. (2011). Issues in the management of challenging behaviours of adults with autism spectrum disorder. CNS drugs, 25(7), 597-606.


Merleau-Ponty, M. (1962). Phenomenology of perception: Translated from the French by Colin Smith. Humanities Press.


Mul, C. L., Cardini, F., Stagg, S. D., Sadeghi Esfahlani, S., Kiourtsoglou, D., Cardellicchio, P., & Aspell, J. E. (2019). Altered bodily self-consciousness and peripersonal space in autism. Autism, 23(8), 2055-2067.


Mullins-Sweatt, S. N., Hopwood, C. J., Chmielewski, M., Meyer, N. A., Min, J., Helle, A. C., & Walgren, M. D. (2020). Treatment of personality pathology through the lens of the hierarchical taxonomy of psychopathology: Developing a research agenda. Personality and mental health, 14(1), 123-141.


Noel, J. P., Pfeiffer, C., Blanke, O., & Serino, A. (2015). Peripersonal space as the space of the bodily self. Cognition, 144, 49-57.


Oskolski, A. (2011). The Taxon as an Ontological Problem. Biosemiotics, 4(2), 201-222.


Parnas J, Gallagher S. (2015). Phenomenology and the interpretation of psychopathological experience. In: Kirmayer L, Lemelson R, Cummings C, editors. Revisioning Psychiatry Integrating Biological, Clinical and Cultural Perspectives. Cambridge: Cambridge University Press, 65–80.


Parnas J, Møller P, Kircher T, Thalbitzer J, Jansson L, Handest P, et al. EASE: examination of anomalous self-experience. (2005). Psychopathology. 38(5), 236–58.


Parnas, J., & Zahavi, D. (2002). The role of phenomenology in psychiatric diagnosis and classification. Psychiatric diagnosis and classification, 137-162.


Patel, K. R., Cherian, J., Gohil, K., & Atkinson, D. (2014). Schizophrenia: overview and treatment options. P & T : a peer-reviewed journal for formulary management, 39(9), 638–645.


Pérez-Álvarez, M., García-Montes, J. M., Vallina-Fernández, O., & Perona-Garcelán, S. (2016). Rethinking schizophrenia in the context of the person and their circumstances: Seven reasons. Frontiers in psychology, 7, 1-16.


Pina-Camacho, L., Parellada, M., & Kyriakopoulos, M. (2016). Autism spectrum disorder and schizophrenia: Boundaries and uncertainties. BJPsych Advances, 22(5), 316-324.


Rutter, M. (1972). Childhood schizophrenia reconsidered. Journal of Autism and Childhood Schizophrenia, 2(3), 315–337.


Sass, L. A., & Parnas, J. (2003). Schizophrenia, consciousness, and the self. Schizophrenia bulletin, 29(3), 427-444.


Schulz, S., Stenzhorn, H., & Boeker, M. (2008). The ontology of biological taxa. Bioinformatics, 24(13), 313-321.


Shorter, E. (2013). The history of DSM. Making the DSM-5, 3-19. Springer, New York, NY.


Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008). Psychiatric disorders in children with autism spectrum disorders: prevalence, comorbidity, and associated factors in a population-derived sample. Journal of the American Academy of Child & Adolescent Psychiatry, 47(8), 921-929.


Spek, A. A., & Wouters, S. G. (2010). Autism and schizophrenia in high functioning adults: Behavioral differences and overlap. Research in Autism Spectrum Disorders, 4(4), 709-717.


Stanghellini, G. (2009). Embodiment and schizophrenia. World Psychiatry, 8(1), 56-59.


Stein, D. J., Phillips, K. A., Bolton, D., Fulford, K. W., Sadler, J. Z., & Kendler, K. S. (2010). What is a mental/psychiatric disorder? From DSM-IV to DSM-V. Psychological medicine, 40(11), 1759–1765.


Tareke, M., Tesfaye, S., Amare, D., Belete, T., & Abate, A. (2018). Antipsychotic medication non-adherence among schizophrenia patients in Central Ethiopia. South African Journal of Psychiatry, 1-6.


Tordjman, S., Celume, M. P., Denis, L., Motillon, T., & Keromnes, G. (2019). Reframing schizophrenia and autism as bodily self-consciousness disorders leading to a deficit of theory of mind and empathy with social communication impairments. Neuroscience & Biobehavioral Reviews, 103, 401-413.


Valderas, J. M., Starfield, B., Sibbald, B., Salisbury, C., & Roland, M. (2009). Defining comorbidity: implications for understanding health and health services. The Annals of Family Medicine, 7(4), 357-363.


Wakefield, J. C. (2010). False positives in psychiatric diagnosis: implications for human freedom. Theoretical medicine and bioethics, 31(1), 5-17.


World Health Organization. (2019). International classification of diseases for mortality and morbidity statistics (11th Revision).


The Ethics behind Brain-Computer Interfaces

Ahn, H., Sorkpor, S., Miao, H., Zhong, C., Jorge, R., Park, L., Abdi, S., & Cho, R. Y. (2019). Home-based self-administered transcranial direct current stimulation in older adults with knee osteoarthritis pain: An open-label study. Journal of clinical neuroscience: official journal of the Neurosurgical Society of Australasia, 66, 61–65. https://doi.org/10.1016/j.jocn.2019.05.023


Burwell, S., Sample, M. & Racine, E. (2017). Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics 18, 60. https://doi.org/10.1186/s12910-017-0220-y


Drew L. (2019). The ethics of brain–computer interfaces. Nature 571, S19-S21. https://doi.org/10.1038/d41586-019-02214-2


Feng, Z., Sun, Y., Qian, L., Qi, Y., Wang, Y., Guan, C., & Sun, Y. (2021). Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: A case study. IEEE Transactions on Biomedical Engineering, 69(5), 1554-1563.


Forum on Neuroscience and Nervous System Disorders; Board on Health Sciences Policy; Institute of Medicine; The National Academies of Sciences, Engineering, and Medicine. Non-Invasive Neuromodulation of the Central Nervous System: Opportunities and Challenges: Workshop Summary (2015). Washington (DC): National Academies Press (US); Ethical, Legal, and Social Issues. Available from: https://www.ncbi.nlm.nih.gov/books/NBK332930/


Lu, Y., Lyu, H., Richardson, A. G., Lucas, T. H., & Kuzum, D. (2016). Flexible neural electrode array based-on porous graphene for cortical microstimulation and sensing. Scientific reports, 6(1), 1-9.


Mattei, T. A. (2014). How graphene is expected to impact neurotherapeutics in the near future. Expert Review of Neurotherapeutics, 14(8), 845-847.


Maynard, E. M., Nordhausen, C. T., & Normann, R. A. (1997). The Utah intracortical electrode array: a recording structure for potential brain-computer interfaces. Electroencephalography and clinical neurophysiology, 102(3), 228-239.


Moore, A.D. Privacy, Neuroscience, and Neuro-Surveillance. (2017). Res Publica 23, 159–177. https://doi.org/10.1007/s11158-016-9341-2


Naseer, N., & Hong, K. S. (2015). fNIRS-based brain-computer interfaces: a review. Frontiers in human neuroscience, 9, 3.


Rainey, S., Maslen H., & Savulescu, J. (2020). When Thinking is Doing: Responsibility for BCI-Mediated Action, AJOB Neuroscience, 11:1, 46-58. https://10.1080/21507740.2019.1704918


Shead, S. (2021). Elon Musk says his start-up Neuralink has wired up a monkey to play video games using its mind. Tech. Available from: https://www.cnbc.com/2021/02/01/elon-musk-neuralink-wires-up-monkey-to-play-video-games-using-mind.html


Smith, S. (2021). Elon Musk’s Neuralink is being outperformed by this Spanish graphene startup. Sifted. Available from: https://sifted.eu/articles/neuralink-competitor-inbrain/


Steyrl, D., Kobler, R. J., & Müller-Putz, G. R. (2016). On similarities and differences of invasive and non-invasive electrical brain signals in brain-computer interfacing. Journal of biomedical science and engineering, 9(08), 393.


Tangermann, M., Krauledat, M., Grzeska, K., Sagebaum, M., Blankertz, B., Vidaurre, C., & Müller, K. R. (2008, December). Playing pinball with non-invasive BCI. In NIPS (pp. 1641-1648).


Zuk, P., Torgerson, L., Sierra-Mercado, D. & Lázaro-Muñoz, G. (2018). Neuroethics of Neuromodulation: An Update. Curr Opin Biomed Eng.  https://doi.org/10.1016/j.cobme.2018.10.003



Neuroscience - a science of the cis-gendered male

Ahn, H., Sorkpor, S., Miao, H., Zhong, C., Jorge, R., Park, L., Abdi, S., & Cho, R. Y. (2019). Home-based self-administered transcranial direct current stimulation in older adults with knee osteoarthritis pain: An open-label study. Journal of clinical neuroscience: official journal of the Neurosurgical Society of Australasia, 66, 61–65. https://doi.org/10.1016/j.jocn.2019.05.023


Burwell, S., Sample, M. & Racine, E. (2017). Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics 18, 60. https://doi.org/10.1186/s12910-017-0220-y


Drew L. (2019). The ethics of brain–computer interfaces. Nature 571, S19-S21. https://doi.org/10.1038/d41586-019-02214-2


Feng, Z., Sun, Y., Qian, L., Qi, Y., Wang, Y., Guan, C., & Sun, Y. (2021). Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: A case study. IEEE Transactions on Biomedical Engineering, 69(5), 1554-1563.


Forum on Neuroscience and Nervous System Disorders; Board on Health Sciences Policy; Institute of Medicine; The National Academies of Sciences, Engineering, and Medicine. Non-Invasive Neuromodulation of the Central Nervous System: Opportunities and Challenges: Workshop Summary (2015). Washington (DC): National Academies Press (US); Ethical, Legal, and Social Issues. Available from: https://www.ncbi.nlm.nih.gov/books/NBK332930/


Lu, Y., Lyu, H., Richardson, A. G., Lucas, T. H., & Kuzum, D. (2016). Flexible neural electrode array based-on porous graphene for cortical microstimulation and sensing. Scientific reports, 6(1), 1-9.


Mattei, T. A. (2014). How graphene is expected to impact neurotherapeutics in the near future. Expert Review of Neurotherapeutics, 14(8), 845-847.


Maynard, E. M., Nordhausen, C. T., & Normann, R. A. (1997). The Utah intracortical electrode array: a recording structure for potential brain-computer interfaces. Electroencephalography and clinical neurophysiology, 102(3), 228-239.


Moore, A.D. Privacy, Neuroscience, and Neuro-Surveillance. (2017). Res Publica 23, 159–177. https://doi.org/10.1007/s11158-016-9341-2


Naseer, N., & Hong, K. S. (2015). fNIRS-based brain-computer interfaces: a review. Frontiers in human neuroscience, 9, 3.


Rainey, S., Maslen H., & Savulescu, J. (2020). When Thinking is Doing: Responsibility for BCI-Mediated Action, AJOB Neuroscience, 11:1, 46-58. https://10.1080/21507740.2019.1704918


Shead, S. (2021). Elon Musk says his start-up Neuralink has wired up a monkey to play video games using its mind. Tech. Available from: https://www.cnbc.com/2021/02/01/elon-musk-neuralink-wires-up-monkey-to-play-video-games-using-mind.html


Smith, S. (2021). Elon Musk’s Neuralink is being outperformed by this Spanish graphene startup. Sifted. Available from: https://sifted.eu/articles/neuralink-competitor-inbrain/


Steyrl, D., Kobler, R. J., & Müller-Putz, G. R. (2016). On similarities and differences of invasive and non-invasive electrical brain signals in brain-computer interfacing. Journal of biomedical science and engineering, 9(08), 393.


Tangermann, M., Krauledat, M., Grzeska, K., Sagebaum, M., Blankertz, B., Vidaurre, C., & Müller, K. R. (2008, December). Playing pinball with non-invasive BCI. In NIPS (pp. 1641-1648).


Zuk, P., Torgerson, L., Sierra-Mercado, D. & Lázaro-Muñoz, G. (2018). Neuroethics of Neuromodulation: An Update. Curr Opin Biomed Eng.  https://doi.org/10.1016/j.cobme.2018.10.003


Issue 13

Cognitive Flexibility in Times of COVID-19

Afshari, A., Hashemikamangar, S., & Hashemikamangar, S. S. (2021). The correlation of perceived stress and professional concerns during COVID-19 pandemic among Iranian dentists: the mediating role of cognitive flexibility. Dentistry 3000, 9(1). https://doi.org/10.5195/D3000.2021.119

Aytur, S. A., Ray, K. L., Meier, S. K., Campbell, J., Gendron, B., Waller, N., & Robin, D. A. (2021). Neural mechanisms of acceptance and commitment therapy for chronic pain: A network based fMRI approach. Frontiers in human neuroscience, 15, 28

Bogliacino, F., Codagnone, C., Montealegre, F., Folkvord, F., Gómez, C., Charris, R., Liva, G., Lupiáñez-Villanueva, F., & Veltri, G. A. (2021). Negative shocks predict change in cognitive function and preferences: assessing the negative affect and stress hypothesis. Scientific Reports 2021 11:1, 11(1), 1–10. https://doi.org/10.1038/s41598-021-83089-0

Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., & Zettle, R. D. (2011). Preliminary psychometric properties of the Acceptance and Action Questionnaire-II: a revised measure of psychological inflexibility and experiential avoidance. Behavior therapy, 42(4), 676–688. https://doi.org/10.1016/j.beth.2011.03.007

Borders, A. (2020). Rumination and Related Constructs: Causes, Consequences, and Treatment of Thinking Too Much. (pp. 279-311) Academic Press

Brashear, C. A., & Thomas, N. (2020). Core competencies for combatting crisis: fusing ethics, cultural competence, and cognitive flexibility in counseling. Counselling Psychology Quarterly, 1–15. https://doi.org/10.1080/09515070.2020.1768362

Cambaz, H. Z., & Ünal, G. (2021). Does Student’s Cognitive Flexibility Decrease During Pandemic? A New Approach to Measure Cognitive Flexibility. International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 9(1), 13–22. https://doi.org/10.23947/2334-8496-2021-9-1-13-22

Chahal, R., Kirshenbaum, J. S., Miller, J. G., Ho, T. C., & Gotlib, I. H. (2021). Higher executive control network coherence buffers against puberty-related increases in internalizing symptoms during the COVID-19 pandemic. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(1), 79-88. https://doi.org/10.1016/j.bpsc.2020.08.010

Dajani, D. R., & Uddin, L. Q. (2015). Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience. Trends in neurosciences, 38(9), 571-578. https://doi.org/10.1016/j.tins.2015.07.003

Daks, J. S., Peltz, J. S., & Rogge, R. D. (2020). Psychological flexibility and inflexibility as sources of resiliency and risk during a pandemic: Modeling the cascade of COVID-19 stress on family systems with a contextual behavioral science lens. Journal of Contextual Behavioral Science, 18, 16–27. https://doi.org/10.1016/J.JCBS.2020.08.003

Dawson, D. L., & Golijani-Moghaddam, N. (2020). COVID-19: Psychological flexibility, coping, mental health, and wellbeing in the UK during the pandemic. Journal of contextual behavioral science, 17, 126–134. https://doi.org/10.1016/j.jcbs.2020.07.010

Derrfuss, J., Brass, M., Neumann, J., & von Cramon, D. Y. (2005). Involvement of the inferior frontal junction in cognitive control: Meta‐analyses of switching and Stroop studies. Human brain mapping, 25(1), 22-34

Diamond, A. (2013). Executive functions. Annual review of psychology, 64, 135-168. https://doi.org/10.1146/annurev-psych-113011-143750

Dodangeh, Z., Malek Hosseini, E., & Dehkordi, P. S. (2021). The effect of parents attitudes to play in green space on childrens cognitive flexibility during Covid-19 home quarantine. Shenakht Journal of Psychology & Psychiatry , 8(2), 100–112. http://shenakht.muk.ac.ir/article-1-1169-en.html

Francis, A. W., Dawson, D. L., & Golijani-Moghaddam, N. (2016). The development and validation of the Comprehensive assessment of Acceptance and Commitment Therapy processes (CompACT). Journal of Contextual Behavioral Science, 5 (3), 134-145. https://doi.org/10.1016/j.jcbs.2016.05.003

Gabrys, R. L., Tabri, N., Anisman, H., & Matheson, K. (2018). Cognitive control and flexibility in the context of stress and depressive symptoms: The cognitive control and flexibility questionnaire. Frontiers in Psychology, 9, 2219. https://doi.org/10.3389/fpsyg.2018.02219

Gozzi, N., Tizzani, M., Starnini, M., Ciulla, F., Paolotti, D., Panisson, A., & Perra, N. (2020). Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis. Journal of Medical Internet Research, 22(10). https://doi.org/10.2196/21597

Hayes, S. C., Luoma, J. B., Bond, F. B., Masuda, A. & Lillis, J. (2006). Acceptance and Commitment Therapy: Model, processes and outcomes. Behaviour Research and Therapy, 44(1), 1-25. https://doi.org/10.1016/j.brat.2005.06.006

Hayes, S. C., Villatte, M., Levin, M. & Hildebrandt, M. (2011). Open, aware, and active: Contextual approaches as an emerging trend in the behavioral and cognitive therapies. Annual Review of Clinical Psychology, 7(4), 141-168. https://doi.org/10.1146/annurev-clinpsy-032210-104449

Kroska, E. B., Roche, A. I., Adamowicz, J. L. & Stegall, M. S. (2020). Psychological flexibility in the context of COVID-19 adversity: Associations with distress. Journal of Contextual Behavioral Science, 18, 28-33. https://doi.org/10.1016/j.jcbs.2020.07.011

Luijten, M. A., van Muilekom, M. M., Teela, L., Polderman, T. J., Terwee, C. B., Zijlmans, J., … & Haverman, L. (2021). The impact of lockdown during the COVID-19 pandemic on mental and social health of children and adolescents. Quality of Life Research, 1-10

Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain structure and function, 214(5-6), 655-667. https://doi.org/10.1007%2Fs00429-010-0262-0

Ong, C. W., Pierce, B. G., Petersen, J. M., Barney, J. L., Fruge, J. E., Levin, M. E. & Twohig, M. P. (2020). A psychometric comparison of psychological inflexibility measures: Discriminant validity and item performance. Journal of Contextual Behavioral Science, 34 – 47. https://doi.org/10.1016/j.jcbs.2020.08.007

Seiter, J. S., & Curran, T. (2021). Social-distancing fatigue during the COVID-19 pandemic: a mediation analysis of cognitive flexibility, fatigue, depression, and adherence to CDC guidelines. Communication Research Reports, 38(1), 68–78. https://doi.org/10.1080/08824096.2021.1880385

Sibel Demirtas, A. (2021). Predictive roles of state hope and cognitive control/flexibility in state anxiety during COVID-19 outbreak in Turkey. Turkey. Dusunen Adam The Journal of Psychiatry and Neurological Sciences, 34, 89–96. https://doi.org/10.14744/DAJPNS.2020.00124

Uddin, L. Q. (2021). Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. Nature Reviews Neuroscience, 22(3), 167-179. https://doi.org/10.1038/s41583-021-00428-w

van der Velden, P.G., Hyland, P., Contino, C., von Gaudecker, H.M., Muffels, R. and Das, M. (2021). Anxiety and depression symptoms, the recovery from symptoms, and loneliness before and after the COVID-19 outbreak among the general population: Findings from a Dutch population-based longitudinal study. PloS one, 16(1), p.e0245057

Wąsowicz, G., Mizak, S., Krawiec, J. & Białaszek, W., (2021). Mental Health, Well-Being, and Psychological Flexibility in the Stressful Times of the COVID-19 Pandemic. Frontiers in Psychology, 12:647975. https://doi.org/10.3389/fpsyg.2021.647975

Wu, X., Wang, Z., Zhang, H., Yuan, P., Yu, Q., Zhou, Z., & Zhao, Q. (2021). Effects of Internet Language Related to COVID-19 on Mental Health in College Students: The Mediating Effect of Cognitive Flexibility. Frontiers in Psychology, 12. https://doi.org/10.3389/FPSYG.2021.600268

Jafari, A. (2020). Comparing Cognitive Flexibility, Psychological Capital and Coping Strategies with Pain between Individuals with COVID-19 Responding and Non-Responding to Home Treatment. Journal of Counseling Research, 19(74), 4–35. https://doi.org/10.29252/JCR.19.74.4

Effects of methylphenidate on default mode network resting-state fMRI connectivity and their relationship with attention in medication-naïve children and adults with ADHD

Supplementary Figures

Supplementary figure 1. Illustration of the graph theory measures used. (A) Modularity – Reflects the extent to which a network is divided into modules. Modules are clusters of nodes with denser links among themselves than among the rest of the network, displayed in grey. (B) Module degree – Measure of the number of connections a module (grey area) has with the rest of the network. Here, the module circled in red has a higher number of connections to the rest of the network than the green module, and therefore has a higher module degree. (C) Participation coefficient – Measures the diversity of connections between modules. Here, the red node is connected to all three modules, whereas the green node only has connections to nodes within its own module. As such, the red node has a higher participation coefficient. (D) Eigenvector centrality – Reflects the extent to which a node is connected to other highly connected nodes. Here, the green nodes both have a high number of connections. Therefore, the red node, which is connected to both of these highly connected nodes, has high eigenvector centrality.


American Psychiatric Organization. (1994). Diagnostic and statistical manual of mental disorders, 4th edition. Washington, DC.

Andersen, S. L. (2005). Stimulants and the developing brain. Trends in Pharmacological Sciences, 26(5), 237–243.

Arnsten, A. F. T. (2009). ADHD and the Prefrontal Cortex. The Journal of Pediatrics, 154(5), I-S43.

Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1–48.

Biswal, B., Yetkin, F. Z., Haughton, V. M., & Hyde, J. S. (1995). Functional Connectivity in the Motor Cortex of Resting Human Brain Using Echo-Planar MRI. Magnetic Resonance in Medicine, 34(4), 537–541.

Bottelier, M. A., Schouw, M. L. J., Klomp, A., Tamminga, H. G. H., Schrantee, A. G. M., Bouziane, C., … Reneman, L. (2014). The effects of Psychotropic drugs On Developing brain (ePOD) study: Methods and design. BMC Psychiatry, 14(1).

Bouziane, C., Filatova, O. G., Schrantee, A., Caan, M. W. A., Vos, F. M., & Reneman, L. (2019). White matter by diffusion MRI following methylphenidate treatment: A randomized control trial in males with attention-deficit/hyperactivity disorder. Radiology, 293(1), 186–192.

Bozhilova, N., Michelini, G., Kuntsi, J., & Asherson, P. (2018). Mind wandering perspective on attention-deficit/hyperactivity disorder. Neuroscience and Biobehavioral Reviews, 92, 464–476.

Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38.

Butzbach, M., Fuermaier, A. B. M., Aschenbrenner, S., Weisbrod, M., Tucha, L., & Tucha, O. (2021). Metacognition in adult ADHD: subjective and objective perspectives on self-awareness of cognitive functioning. Journal of Neural Transmission.

Cary, R. P., Ray, S., Grayson, D. S., Painter, J., Carpenter, S., Maron, L., … Fair, D. A. (2017). Network structure among brain systems in adult ADHD is uniquely modified by stimulant administration. Cerebral Cortex, 27(8), 3970–3979.

Castellanos, F. X., & Proal, E. (2012). Large-scale brain systems in ADHD: Beyond the prefrontal-striatal model. Trends in Cognitive Sciences, 16(1), 17–26.

Castellanos, F. X., Margulies, D. S., Kelly, A. M. C., Uddin, L. Q., Ghaffari, M., Kirsch, A., … Milham, M. P. (2008). Cingulate – Precuneus Interactions: A New Locus of Dysfunction in Adult Attention-Deficit/Hyperactivity Disorder. Biol Psychiatry, 63(3), 332–337.

Castellanos, F. X., Sonuga-Barke, E. J. S., Milham, M. P., & Tannock, R. (2006). Characterizing cognition in ADHD: Beyond executive dysfunction. Trends in Cognitive Sciences, 10(3), 117–123.

Castellanos, X., & Aoki, Y. (2016). Intrinsic Functional Connectivity in Attention-Deficit/ Hyperactivity Disorder: A Science in Development. Biol Psychiatry Cogn Neurosci Neuroimaging., 1(3), 253–261.

Castells, X., Ramos-Quiroga, J. A., Rigau, D., Bosch, R., Nogueira, M., Vidal, X., & Casas, M. (2011). Efficacy of methylphenidate for adults with attention-deficit hyperactivity disorder: a meta-regression analysis. CNS Drugs, 25(2), 157–169.

Cortese, S., D’Acunto, G., Konofal, E., Masi, G., & Vitiello, B. (2017). New Formulations of Methylphenidate for the Treatment of Attention-Deficit/Hyperactivity Disorder: Pharmacokinetics, Efficacy, and Tolerability. CNS Drugs, 31(2), 149–160.

Cortese, S., Faraone, S. V., Bernardi, S., Wang, S., & Blanco, C. (2016). Gender Differences in Adult Attention-Deficit/Hyperactivity Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). J Clin Psychiatry, 77(4), 421–428.

DuPaul, G. J., Power, T. J., McGoey, K. E., Ikeda, M. J., & Anastopoulos, A. D. (1998). Reliability and validity of parent and teacher ratings of attention-deficit/hyperactivity disorder symptoms. Journal of Psychoeducational Assessment, 16(1), 55–68.

Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., … Gorgolewski, K. J. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111–116.

Fair, D. A., Miranda-Dominguez, O., Snyder, A. Z., Perrone, A., Earl, E. A., Van, A. N., … Dosenbach, N. U. F. (2020). Correction of respiratory artifacts in MRI head motion estimates. NeuroImage, 208(November 2019), 116400.

Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., … Jiang, T. (2016). The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cerebral Cortex, 26(8), 3508–3526.

Faraone, S. V., Asherson, P., Banaschewski, T., Biederman, J., Buitelaar, J. K., Ramos-Quiroga, J. A., … Franke, B. (2015). Attention-deficit/hyperactivity disorder. Nature Reviews Disease Primers, 1.

Faraone, S. V., & Buitelaar, J. (2010). Comparing the efficacy of stimulants for ADHD in children and adolescents using meta-analysis. European Child and Adolescent Psychiatry, 19(4), 353–364.

Ferdinand, R. F., & van der Ende, J. (2000). NIMH DISC-IV: Diagnostic Interview Schedule for Children. Authorized Dutch Translation. Erasmus MC Sophia: Rotterdam, The Netherlands.

Fox, K. C. R., Spreng, R. N., Ellamil, M., Andrews-Hanna, J. R., & Christoff, K. (2015). The wandering brain: Meta-analysis of functional neuroimaging studies of mind-wandering and related spontaneous thought processes. NeuroImage, 111, 611–621.

Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102(27), 9673–9678.

Hoekzema, E., Carmona, S., Ramos-Quiroga, J. A., Richarte Fernández, V., Bosch, R., Soliva, J. C., … Vilarroya, O. (2014). An independent components and functional connectivity analysis of resting state FMRI data points to neural network dysregulation in adult ADHD. Human Brain Mapping, 35(4), 1261–1272.

Holbrook, J. R., Cuffe, S. P., Cai, B., Visser, S. N., Forthofer, M. S., Bottai, M., … McKeown, R. E. (2016). Persistence of Parent-Reported ADHD Symptoms From Childhood Through Adolescence in a Community Sample. J Atten Disord., 20(1), 11–20.

Ingalhalikar, M., Smith, A., Parker, D., Satterthwaite, T. D., Elliott, M. A., Ruparel, K., … Verma, R. (2014). Sex differences in the structural connectome of the human brain. Proceedings of the National Academy of Sciences of the United States of America, 111(2), 823–828.

Kong, X. Z., Zhen, Z., Li, X., Lu, H. H., Wang, R., Liu, L., … Liu, J. (2014). Individual differences in impulsivity predict head motion during magnetic resonance imaging. PLoS ONE, 9(8).

Konrad, K., & Eickhoff, S. B. (2010). Is the ADHD brain wired differently? A review on structural and functional connectivity in attention deficit hyperactivity disorder. Human Brain Mapping, 31(6), 904–916.

Kooij, J. J. S., & Francken, M. H. (2010). Diagnostisch Interview Voor ADHD bij volwassenen. Den Haag.

Kooij, J. J.Sandra, Buitelaar, J. K., van den Oord, E. J., Furer, J. W., Rijnders, C. A. T., & Hodiamont, P. P. G. (2005). Internal and external validity of Attention-Deficit Hyperactivity Disorder in a population-based sample of adults. Psychological Medicine, 35(6), 817–827.

Krain, A. L., & Castellanos, F. X. (2006). Brain development and ADHD. Clinical Psychology Review, 26(4), 433–444.

Larsson, H., Dilshad, R., Lichtenstein, P., & Barker, E. D. (2011). Developmental trajectories of DSM-IV symptoms of attention-deficit/ hyperactivity disorder: Genetic effects, family risk and associated psychopathology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 52(9), 954–963.

Liddle, E. B., Hollis, C., Batty, M. J., Groom, M. J., Totman, J. J., Liotti, M., … Liddle, P. F. (2011). Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 52(7), 761–771.

Linssen, A. M. W., Sambeth, A., Vuurman, E. F. P. M., & Riedel, W. J. (2014). Cognitive effects of methylphenidate in healthy volunteers: A review of single dose studies. International Journal of Neuropsychopharmacology, 17(6), 961–977.

Maia, C. R. M., Cortese, S., Caye, A., Deakin, T. K., Polanczyk, G. V., Polanczyk, C. A., & Rohde, L. A. P. (2017). Long-Term Efficacy of Methylphenidate Immediate-Release for the Treatment of Childhood ADHD: A Systematic Review and Meta-Analysis. Journal of Attention Disorders, 21(1), 3–13.

Meijer, K. A., Eijlers, A. J. C., Douw, L., Uitdehaag, B. M. J., Barkhof, F., Geurts, J. J. G., & Schoonheim, M. M. (2017). Increased connectivity of hub networks and cognitive impairment in multiple sclerosis. Neurology, 88(22), 2107–2114.

Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506.

Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain Stuct Funct., 214(5–6), 655–667.

Molina, B. S. G., Pelham, W. E., & Galiszewski, E. (1998). Agreement Among Teachers’ Behavior Ratings of Adolescents With a Childhood History of Attention Deficit Hyperactivity Disorder. J Clin Child Psychol., 27(3), 330–339.

Oosterlaan, J., Scheres, A., Antrop, I., Roeyers, H., & Sergeant, J. A. (1998). Vragenlijst voor Gedragsproblemen bij Kinderen (VvGK). [Dutch Translation of the Disruptive Behavior Disorders Rating Scale]. Amsterdam.

Pereira-Sanchez, V., Franco, A. R., Vieira, D., de Castro-Manglano, P., Soutullo, C., Milham, M. P., & Castellanos, F. X. (2021). Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 60(2), 222–235.

Peterson, B. S., Potenza, M. N., Wang, Z., Zhu, H., Martin, A., Marsh, R., … Yu, S. (2009). An fMRI Study of the Effects of Psychostimulants on Default- Mode Processing During Stroop Task Performance in Youths With ADHD. Am J Psychiatry, 166(11), 1286–1294.

Picon, F. A., Sato, J. R., Anés, M., Vedolin, L. M., Mazzola, A. A., Valentini, B. B., … Rohde, L. A. P. (2020). Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD. Journal of Attention Disorders, 24(3), 447–455.

Posner, J., Park, C., & Wang, Z. (2014). Connecting the dots: A review of resting connectivity MRI studies in attention-deficit/hyperactivity disorder. Neuropsychology Review, 24(1), 3–15.

Pruim, R. H. R., Mennes, M., van Rooij, D., Llera, A., Buitelaar, J. K., & Beckmann, C. F. (2015). ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. NeuroImage, 112, 267–277.

Querne, L., Fall, S., Le Moing, A. G., Bourel-Ponchel, E., Delignières, A., Simonnot, A., … Berquin, P. (2017). Effects of Methylphenidate on Default-Mode Network/Task-Positive Network Synchronization in Children With ADHD. Journal of Attention Disorders, 21(14), 1208–1220.

Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 676–682.

Rosch, K. S., Mostofsky, S. H., & Nebel, M. B. (2018). ADHD-related sex differences in fronto-subcortical intrinsic functional connectivity and associations with delay discounting. Journal of Neurodevelopmental Disorders, 10(1), 1–14.

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52(3), 1059–1069.

Sato, J. R., Hoexter, M. Q., Castellanos, X. F., & Rohde, L. A. (2012). Abnormal Brain Connectivity Patterns in Adults with

ADHD: A Coherence Study. Plos One, 7(9), 1–9.

Satterthwaite, T. D., Wolf, D. H., Roalf, D. R., Ruparel, K., Erus, G., Vandekar, S., … Gur, R. C. (2015). Linked Sex Differences in Cognition and Functional Connectivity in Youth. Cerebral Cortex, 25(9), 2383–2394.

Schachter, H. M., Pham, B., King, J., Langford, S., & Moher, D. (2001). How efficacious and safe is short-acting methylphenidate for the treatment of attention-deficit disorder in children and adolescents? A meta-analysis. Cmaj, 165(11), 1475–1488.

Schmand, B., Bakker, D., Saan, R., & Louman, J. (1991). The Dutch Reading Test for Adults: a measure of premorbid intelligence level. Tijdschr Gerontol Geriatr, 22, 15–19.

Schrantee, A., Mutsaerts, H. J. M. M., Bouziane, C., Tamminga, H. G. H., Bottelier, M. A., & Reneman, L. (2017). The age-dependent effects of a single-dose methylphenidate challenge on cerebral perfusion in patients with attention-deficit/hyperactivity disorder. NeuroImage: Clinical, 13, 123–129.

Schrantee, A., Tamminga, H. G. H., Bouziane, C., Bottelier, M. A., Bron, E. E., Mutsaerts, H. J. M. M., … Reneman, L. (2016). Age-dependent effects of methylphenidate on the human dopaminergic system in young vs adult patients with attention-deficit/hyperactivity disorder: A randomized clinical trial. JAMA Psychiatry, 73(9), 955–962.

Silveri, M. M., Anderson, C. M., McNeil, J. F., Diaz, C. I., Lukas, S. E., Mendelson, J. H., … Kaufman, M. J. (2004). Oral methylphenidate challenge selectively decreases putaminal T2 in healthy subjects. Drug and Alcohol Dependence, 76(2), 173–180.

Singh, K. D., & Fawcett, I. P. (2008). Transient and linearly graded deactivation of the human default-mode network by a visual detection task. NeuroImage, 41(1), 100–112.

Sonuga-Barke, E. J. S., & Castellanos, F. X. (2007). Spontaneous attentional fluctuations in impaired states and pathological conditions: A neurobiological hypothesis. Neuroscience and Biobehavioral Reviews, 31(7), 977–986.

Spencer, T. J., Biederman, J., Ciccone, P. E., Madras, B. K., Dougherty, D. D., Bonab, A. A., … Fischman, A. J. (2006). PET study examining pharmacokinetics, detection and likeability, and dopamine transporter receptor occupancy of short- and long-acting oral methylphenidate. American Journal of Psychiatry, 163(3), 387–395.

Sun, L., Cao, Q., Long, X., Sui, M., Cao, X., Zhu, C., … Wang, Y. (2012). Abnormal functional connectivity between the anterior cingulate and the default mode network in drug-naïve boys with attention deficit hyperactivity disorder. Psychiatry Research – Neuroimaging, 201(2), 120–127.

Swanson, J. M., & Volkow, N. D. (2003). Serum and brain concentrations of methylphenidate: Implications for use and abuse. Neuroscience and Biobehavioral Reviews, 27(7), 615–621.

Thomas, R., Sanders, S., Doust, J., Beller, E., & Glasziou, P. (2015). Prevalence of attention-deficit/hyperactivity disorder: A systematic review and meta-analysis. Pediatrics, 135(4), 994–1001.

Tooley, U. A., Bassett, D. S., & Mackey, A. P. (2021). Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries. BioRxiv.

Wagner, A. K., Kline, A. E., Ren, D., Willard, L. A., Wenger, M. K., Zafonte, R. D., & Dixon, C. E. (2007). Gender associations with chronic methylphenidate treatment and behavioral performance following experimental traumatic brain injury. Behavioural Brain Research, 181(2), 200–209.

Walhovd, K. B., Amlien, I., Schrantee, A., Rohani, D. A., Groote, I., Bjørnerud, A., … Reneman, L. (2020). Methylphenidate effects on cortical thickness in children and adults with attention-deficit/hyperactivity disorder: A randomized clinical trial. American Journal of Neuroradiology, 41(5), 758–765.

Wang, J., Zuo, X., & He, Y. (2010). Graph-based network analysis of resting-state functional MRI. Frontiers in Systems Neuroscience, 4(June), 1–14.

Wechsler, D. (1981). The psychometric tradition: Developing the wechsler adult intelligence scale. Contemporary Educational Psychology, 6(2), 82–85.

Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The neural bases of momentary lapses in attention. Nature Neuroscience, 9(7), 971–978.

Wolraich, M. L., Hagan, J. F., Allan, C., & Chan, E. (2015). Clinical Practice Guideline for the Diagnosis, Evaluation, and Treatment of ADHD in Children and Adolescents. Developmental Pediatrics, 144(4), 54–54.

Yoo, J. H., Kim, D., Choi, J., & Jeong, B. (2018). Treatment effect of methylphenidate on intrinsic functional brain network in medication-naïve ADHD children: A multivariate analysis. Brain Imaging and Behavior, 12(2), 518–531.

Zhou, Y., Liang, M., Jiang, T., Tian, L., Liu, Y., Liu, Z., … Kuang, F. (2007). Functional dysconnectivity of the dorsolateral prefrontal cortex in first-episode schizophrenia using resting-state fMRI. Neuroscience Letters, 417(3), 297–302.

The Affective Influence of Walking In Urban Environments

Al-Barrak, L., & Kanjo, E. (2013). NeuroPlace: Making sense of a place. Proceedings of the 4th Augmented Human International Conference, 186–189. https://doi.org/10.1145/2459236.2459267

Alexander, C. (2002). The Phenomenon of Life: The Nature of Order (1st Edition). The Center for Environmental Structure.

Aspinall, P., Mavros, P., Coyne, R., & Roe, J. (2015). The urban brain: Analysing outdoor physical activity with mobile EEG. British Journal of Sports Medicine, 49(4), 272–276. https://doi.org/10.1136/bjsports-2012-091877

Bailey, A. W., Allen, G., Herndon, J., & Demastus, C. (2018). Cognitive benefits of walking in natural versus built environments. World Leisure Journal, 60(4), 293–305. https://doi.org/10.1080/16078055.2018.1445025

Ball, T., Demandt, E., Mutschler, I., Neitzel, E., Mehring, C., Vogt, K., Aertsen, A., & Schulze-Bonhage, A. (2008). Movement related activity in the high gamma range of the human EEG. NeuroImage, 41(2), 302–310. https://doi.org/10.1016/j.neuroimage.2008.02.032

Banaei, M., Yazdanfara, A., Nooreddina, M., & Yoonessi, A. (2017). Neural Correlates of Mobile EEG and the Built Environment. Asian Journal of Environment-Behaviour Studies, 2(3), 67–75. https://doi.org/10.21834/aje-bs.v2i4.199

Barontini, M., Lázzari, J. O., Levin, G., Armando, I., & Basso, S. J. (1997). Age-related changes in sympathetic activity: Biochemical measurements and target organ responses. Archives of Gerontology and Geriatrics, 25(2), 175–186. https://doi.org/10.1016/S0167-4943(97)00008-3

Baum, H. (2015). Planning with half a mind: Why planners resist emotion. Planning Theory & Practice, 16(4), 498–516. https://doi.org/10.1080/14649357.2015.1071870

Beebeejaun, Y. (2017). Gender, urban space, and the right to everyday life. Journal of Urban Affairs, 39(3), 323–334. https://doi.org/10.1080/07352166.2016.1255526

Benasich, A. A., Gou, Z., Choudhury, N., & Harris, K. D. (2008). Early cognitive and language skills are linked to resting frontal gamma power across the first 3 years. Behavioural Brain Research, 195(2), 215–222. https://doi.org/10.1016/j.bbr.2008.08.049

Bergman, P., Vastfjall, D., Fransson, N., & Skold, A. (2008). Emotion and meaning in interpretation of sound sources. Journal of the Acoustical Society of America, 123(5), 3567.

Berlyne, D. E. (1960). Conflict, arousal, and curiosity (pp. xii, 350). McGraw-Hill Book Company. https://doi.org/10.1037/11164-000

Berman, M. G., Jonides, J., & Kaplan, S. (2008). The Cognitive Benefits of Interacting With Nature. Psychological Science, 19(12), 1207–1212. https://doi.org/10.1111/j.1467-9280.2008.02225.x Berry, H. L. (2007). ‘Crowded suburbs’ and ‘killer cities’: A brief review of the relationship between urban environments and mental health. New South Wales Public Health Bulletin, 18(12), 222. https://doi.org/10.1071/NB07024

Berto, R., Baroni, M. R., Zainaghi, A., & Bettella, S. (2010). An exploratory study of the effect of high and low fascination environments on attentional fatigue. Journal of Environmental Psychology, 30(4), 494–500. https://doi.org/10.1016/j.jenvp.2009.12.002

Birenboim, A., Reinau, K. H., Shoval, N., & Harder, H. (2015). High-Resolution Measurement and Analysis of Visitor Experiences in Time and Space: The Case of Aalborg Zoo in Denmark. The Professional Geographer, 67(4), 620–629. https://doi.org/10.1080/00330124.2015.1032874

Bonnet, M. H., & Arand, D. L. (2001). Impact of activity and arousal upon spectral EEG parameters. Physiology & Behavior, 74(3), 291–298. https://doi.org/10.1016/S0031-9384(01)00581-9 Bornioli, A., Parkhurst, G., & Morgan, P. L. (2019). Affective experiences of built environments and the promotion of urban walking. Transportation Research Part A: Policy and Practice, 123, 200–215. https://doi.org/10.1016/j.tra.2018.12.006

Bostock, L. (2001). Pathways of disadvantage? Walking as a mode of transport among low-income mothers. Health & Social Care in the Community, 9(1), 11–18. https://doi.org/10.1046/j.1365-2524.2001.00275.x

Boucsein, W., Fowles, D. C., Grimnes, S., Ben-Shakhar, G., Roth, W. T., Dawson, M. E., & Filion, D. L. (2012). Publication recommendations for electrodermal measurements. Psychophysiology, 49(8), 1017–1034. https://doi.org/10.1111/j.1469-8986.2012.01384.x

Bower, I., Tucker, R., & Enticott, P. G. (2019). Impact of built environment design on emotion measured via neurophysiological correlates and subjective indicators: A systematic review. Journal of Environmental Psychology, 66, 101344. https://doi.org/10.1016/j.jenvp.2019.101344

Bradley, M., & Lang, P. J. (1994). Measuring Emotion: The Self-Assessment Manikin (SAM) and the Semantic Differential. Journal of Experimental Psychiatry & Behavior Therapy, 25, 49–59. Bratman, G. N., Daily, G. C., Levy, B. J., & Gross, J. J. (2015). The benefits of nature experience: Improved affect and cognition. Landscape and Urban Planning, 138, 41–50. https://doi.org/10.1016/j.landurbplan.2015.02.005

Bridgeman, B., & Tseng, P. (2011). Embodied cognition and the perception–action link. Physics of Life Reviews, 8(1), 73–85. https://doi.org/10.1016/j.plrev.2011.01.002

Brown, B. B., Werner, C. M., Amburgey, J. W., & Szalay, C. (2007). Walkable Route Perceptions and Physical Features: Converging Evidence for En Route Walking Experiences. Environment and Behavior, 39(1), 34–61. https://doi.org/10.1177/0013916506295569

Buschman, T. J., & Miller, E. K. (2007). Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices. Science, 315(5820), 1860–1862. https://doi.org/10.1126/science.1138071

Bynion, T.-M., & Feldner, M. T. (2017). Self-assessment manikin. Encyclopedia of Personality and Individual Differences, 1–3.

Cardoso, R., Meijers, E., van Ham, M., Burger, M., & de Vos, D. (2019). Why bright city lights dazzle and illuminate: A cognitive science approach to urban promises. Urban Studies, 56(2), 452–470. https://doi.org/10.1177/0042098018804762

Carlson, R. A., Avraamides, M. N., Cary, M., & Strasberg, S. (2007). What do the hands externalize in simple arithmetic? Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(4), 747–756. https://doi.org/10.1037/0278-7393.33.4.747

Carmona, M. (2020). Home comforts: Stress testing our homes and neighbourhoods during the Covid-19 lockdown. https://matthew-carmona.com/2020/10/12/76-home-comforts-stress-testing-our-homes-and neighbourhoods-during-the-covid-19-lockdown/

Catania, J. J., Thompson, L. W., Michalewski, H. A., & Bowman, T. E. (1980). Comparisons of Sweat Gland Counts, Electrodermal Activity, and Habituation Behavior in Young and Old Groups of Subjects. Psychophysiology, 17(2), 146–152. https://doi.org/10.1111/j.1469-8986.1980.tb00127.x

Chang, C.-Y., Hammitt, W. E., Chen, P.-K., Machnik, L., & Su, W.-C. (2008). Psychophysiological responses and restorative values of natural environments in Taiwan. Landscape and Urban Planning, 85(2), 79–84. https://doi.org/10.1016/j.landurbplan.2007.09.010

Chemero, A. (2003). An Outline of a Theory of Affordances. Ecological Psychology, 15(2), 181–195. https://doi.org/10.1207/S15326969ECO1502_5

Chen, Z., He, Y., & Yu, Y. (2016). Enhanced functional connectivity properties of human brains during in-situ nature experience. PeerJ, 4, e2210. https://doi.org/10.7717/peerj.2210 Chu, M., & Kita, S. (2008). Spontaneous gestures during mental rotation tasks: Insights into the microdevelopment of the motor strategy. Journal of Experimental Psychology: General, 137(4), 706–723. https://doi.org/10.1037/a0013157

Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. https://doi.org/10.1037/1040-3590.7.3.309

Clark, L. A., & Watson, D. (2016). Constructing validity: Basic issues in objective scale development (p. 203). American Psychological Association. https://doi.org/10.1037/14805-012 Conger, R. D., & Donnellan, M. B. (2007). An interactionist perspective on the socioeconomic context of human development. Annu. Rev. Psychol., 58, 175–199.

Crenshaw, K. (1990). Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color. Stanford Law Review, 43(6), 1241–1300.

Cronin-de-Chavez, A., Islam, S., & McEachan, R. R. C. (2019). Not a level playing field: A qualitative study exploring structural, community and individual determinants of greenspace use amongst low-income multi-ethnic families. Health & Place, 56, 118–126. https://doi.org/10.1016/j.healthplace.2019.01.018

Darvas, F., Scherer, R., Ojemann, J. G., Rao, R. P., Miller, K. J., & Sorensen, L. B. (2010). High gamma mapping using EEG. NeuroImage, 49(1), 930–938. https://doi.org/10.1016/j.neuroimage.2009.08.041

Davidson, R. J. (2004). What does the prefrontal cortex “do” in affect: Perspectives on frontal EEG asymmetry research. Biological Psychology, 67(1), 219–234. https://doi.org/10.1016/j.biopsycho.2004.03.008

Dawson, M. E., Schell, A. M., & Filion, D. L. (2017). The electrodermal system. In Handbook of psychophysiology, 4th ed (pp. 217–243). Cambridge University Press.

de Lange, F. P., Heilbron, M., & Kok, P. (2018). How Do Expectations Shape Perception? Trends in Cognitive Sciences, 22(9), 764–779. https://doi.org/10.1016/j.tics.2018.06.002 Dehzangi, O., & Williams, C. (2015). Towards multi-modal wearable driver monitoring: Impact of road condition on driver distraction. 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), 1–6. https://doi.org/10.1109/BSN.2015.7299408

Di Nota, P. M., Chartrand, J. M., Levkov, G. R., Montefusco-Siegmund, R., & DeSouza, J. F. X. (2017). Experience-dependent modulation of alpha and beta during action observation and motor imagery. BMC Neuroscience, 18(1), 28. https://doi.org/10.1186/s12868-017-0349-0

Dillman-Hasso, N. (2020). When the Nature of ‘Nature’ is Inconsistent: Evaluating the Natural Environment in Attention Restoration Theory. PsyArXiv. https://doi.org/10.31234/osf.io/w36rg

Djebbara, Z., Fich, L. B., Petrini, L., & Gramann, K. (2019). Sensorimotor brain dynamics reflect architectural affordances. PNAS Proceedings of the National Academy of Sciences of the United States of America, 116(29), 14769–14778. https://doi.org/10.1073/pnas.1900648116

Djebbara, Z., Parr, T., & Friston, K. (2020). Anticipation in architectural experience: A computational neurophenomenology for architecture? ArXiv:2011.03852 [q-Bio]. http://arxiv.org/abs/2011.03852

Eerland, A., Guadalupe, T. M., & Zwaan, R. A. (2011). Leaning to the Left Makes the Eiffel Tower Seem Smaller: Posture-Modulated Estimation. Psychological Science, 22(12), 1511–1514. https://doi.org/10.1177/0956797611420731

Ekkekakis, P., & Petruzzello, S. J. (2001). Analysis of the affect measurement conundrum in exercise psychology: II. A conceptual and methodological critique of the Exercise-induced Feeling inventory. Psychology of Sport and Exercise, 2(1), 1–26. https://doi.org/10.1016/S1469-0292(00)00020-0

Ekman, Paul. (1992). An argument for basic emotions. Cognition and Emotion, 6(3–4), 169–200. https://doi.org/10.1080/02699939208411068

Elsadek, M., Liu, B., & Lian, Z. (2019). Green façades: Their contribution to stress recovery and well-being in high-density cities. Urban Forestry & Urban Greening, 46, 126446. https://doi.org/10.1016/j.ufug.2019.126446

Elsadek, M., Liu, B., & Xie, J. (2020). Window view and relaxation: Viewing green space from a high-rise estate improves urban dwellers’ wellbeing. Urban Forestry & Urban Greening, 55, 126846. https://doi.org/10.1016/j.ufug.2020.126846

Esplin, J. A., Austin, A. M. B., Blevins-Knabe, B., Neilson, B. G., & Corwyn, R. F. (2020). Preschool Mathematics Performance and Executive Function: Rural-Urban Comparisons across Time. Journal of Research in Childhood Education, 0(0), 1–19. https://doi.org/10.1080/02568543.2020.1736219

Ettema, D., & Smajic, I. (2015). Walking, places and wellbeing. The Geographical Journal, 181(2), 45 102–109. https://doi.org/10.1111/geoj.12065

Evans, G. W. (2003). The built environment and mental health. Journal of Urban Health, 80(4), 536–555. https://doi.org/10.1093/jurban/jtg063

Fajen, B. R., Riley, M. A., & Turvey, M. T. (2008). Information, affordances, and the control of action in sport. International Journal of Sport Psychology, 40(1), 79–107.

Fathullah, A., & Willis, K. S. (2018). Engaging the Senses: The Potential of Emotional Data for Participation in Urban Planning. Urban Science, 2(4), 98. https://doi.org/10.3390/urbansci2040098

Fogel, S. M., & Smith, C. T. (2011). The function of the sleep spindle: A physiological index of intelligence and a mechanism for sleep-dependent memory consolidation. Neuroscience & Biobehavioral Reviews, 35(5), 1154–1165. https://doi.org/10.1016/j.neubiorev.2010.12.003

Fonteyn, M. E., Kuipers, B., & Grobe, S. J. (1993). A Description of Think Aloud Method and Protocol Analysis. Qualitative Health Research, 3(4), 430–441. https://doi.org/10.1177/104973239300300403

Frijda, N. H. (1994). Varieties of affect: Emotions and episodes, moods, and sentiments. In P Ekman & R. J. Davidson (Eds.), The nature of emotion: Fundamental questions (pp. 59–67). Oxford University Press.

Frisch, M. (2015). Finding transformative planning practice in the spaces of intersectionality. Planning and LGBTQ Communities: The Need for Inclusive Queer Spaces, 129–146.

Friston, K. (2005). A theory of cortical responses. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1456), 815–836. https://doi.org/10.1098/rstb.2005.1622 Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138. https://doi.org/10.1038/nrn2787

Friston, K., Mattout, J., & Kilner, J. (2011). Action understanding and active inference. Biological Cybernetics, 104(1), 137–160. https://doi.org/10.1007/s00422-011-0424-z

Galea, S., Uddin, M., & Koenen, K. (2011). The urban environment and mental disorders. Epigenetics, 6(4), 400–404. https://doi.org/10.4161/epi.6.4.14944

Gauvin, L., & Rejeski, W. J. (1993). The Exercise-Induced Feeling Inventory: Development and Initial Validation. Journal of Sport and Exercise Psychology, 15(4), 403–423. https://doi.org/10.1123/jsep.15.4.403

Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Psychology Press. Gong, Y., Palmer, S., Gallacher, J., Marsden, T., & Fone, D. (2016). A systematic review of the relationship between objective measurements of the urban environment and psychological distress. Environment International, 96, 48–57. https://doi.org/10.1016/j.envint.2016.08.019 Goodman, E., McEwen, B. S., Dolan, L. M., Schafer-Kalkhoff, T., & Adler, N. E. (2005). Social disadvantage and adolescent stress. Journal of Adolescent Health, 37(6), 484–492. Gould, K. A., & Lewis, T. L. (2016). Green Gentrification: Urban sustainability and the struggle for environmental justice. Routledge.

Gramann, K., Ferris, D. P., Gwin, J., & Makeig, S. (2014). Imaging natural cognition in action. International Journal of Psychophysiology, 91(1), 22–29. https://doi.org/10.1016/j.ijpsycho.2013.09.003

Grassini, S., Revonsuo, A., Castellotti, S., Petrizzo, I., Benedetti, V., & Koivisto, M. (2019). Processing of natural scenery is associated with lower attentional and cognitive load compared with urban ones. Journal of Environmental Psychology, 62, 1–11. https://doi.org/10.1016/j.jenvp.2019.01.007

Gray, E. K., & Watson, D. (2007). Assessing Positive and Negative Affect via Self-Report. In J. A. Coan & J. J. B. Allen (Eds.), Handbook of Emotion Elicitation and Assessment (pp. 171–183). Oxford University Press, USA.

Gross, J. J. (2010). The Future’s So Bright, I Gotta Wear Shades. Emotion Review, 2(3), 212–216. https://doi.org/10.1177/1754073910361982

Guite, H. F., Clark, C., & Ackrill, G. (2006). The impact of the physical and urban environment on mental well-being. Public Health, 120(12), 1117–1126. https://doi.org/10.1016/j.puhe.2006.10.005

Hackman, D. A., Robert, S. A., Grübel, J., Weibel, R. P., Anagnostou, E., Hölscher, C., & Schinazi, V. R. (2019). Neighborhood environments influence emotion and physiological reactivity. Scientific Reports, 9(1), 9498. https://doi.org/10.1038/s41598-019-45876-8

Hadavi, S., Kaplan, R., & Hunter, M. C. R. (2015). Environmental affordances: A practical approach for design of nearby outdoor settings in urban residential areas. Landscape and Urban Planning, 134, 19–32. https://doi.org/10.1016/j.landurbplan.2014.10.001

Haga, A., Halin, N., Holmgren, M., & Sörqvist, P. (2016). Psychological Restoration Can Depend on Stimulus-Source Attribution: A Challenge for the Evolutionary Account? Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01831

Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17(1), 13–26. https://doi.org/10.1080/14725860220137345

Hartig, T., Evans, G. W., Jamner, L. D., Davis, D. S., & Gärling, T. (2003). Tracking restoration in natural and urban field settings. Journal of Environmental Psychology, 23(2), 109–123. https://doi.org/10.1016/S0272-4944(02)00109-3

Hayden, D. (1980). What Would a Non-Sexist City Be Like? Speculations on Housing, Urban Design, and Human Work. Signs: Journal of Women in Culture, 5(3), S170–S187.

Heath, T., Smith, S. G., & Lim, B. (2000). Tall Buildings and the Urban Skyline: The Effect of Visual Complexity on Preferences. Environment and Behavior, 32(4), 541–556. https://doi.org/10.1177/00139160021972658

Hebb, D. O. (1954). The social significance of animal studies. In G. Lindzey (Ed.), Handbook of social psychology (pp. 532–561). Addison-Wesley.

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). Most people are not WEIRD. Nature, 466(7302), 29–29. https://doi.org/10.1038/466029a

Hink, R. F., Van Voorhis, S. T., Hillyard, S. A., & Smith, T. S. (1977). The division of attention and the human auditory evoked potential. Neuropsychologia, 15(4), 597–605. https://doi.org/10.1016/0028-3932(77)90065-3

Hohwy, J. (2013). The Predictive Mind. Oxford University Press.

Humberto, M., Laboissière, R., Giannotti, M., Marte, C. L., Cruz, D. A., Primon, H., Humberto, M., Laboissière, R., Giannotti, M., Marte, C. L., Cruz, D. A., & Primon, H. (2019). Walking and walkability: Do built environment measures correspond with pedestrian activity? Ambiente Construído, 19(4), 23–36. https://doi.org/10.1590/s1678-86212019000400341

Isen, A. M., & Erez, A. (2006). Some Measurement Issues in the Study of Affect. In A. D. Ong & M. H. M. V. Dulmen (Eds.), Oxford Handbook of Methods in Positive Psychology (pp. 250–265). Oxford University Press.

Itti, L. (2006). Quantitative modelling of perceptual salience at human eye position. Visual Cognition, 14(4–8), 959–984. https://doi.org/10.1080/13506280500195672

Iturregui-Gallardo, G., & Méndez-Ulrich, J. L. (2020). Towards the Creation of a Tactile Version of the Self-Assessment Manikin (T-SAM) for the Emotional Assessment of Visually Impaired People. International Journal of Disability, Development and Education, 67(6), 657–674. https://doi.org/10.1080/1034912X.2019.1626007

Jamalian, A., Giardino, V., & Tversky, B. (2013). Gestures for thinking. Proceedings of the Annual Meeting of the Cognitive Science Society, 35(35), 645–650.

Jensen, T. W., & Pedersen, S. B. (2016). Affect and affordances – The role of action and emotion in social interaction. Cognitive Semiotics, 9(1), 79–103. https://doi.org/10.1515/cogsem-2016-0003

Johansson, Marcus, Hartig, T., & Staats, H. (2011). Psychological Benefits of Walking: Moderation by Company and Outdoor Environment. Applied Psychology: Health and Well-Being, 3(3), 261–280. https://doi.org/10.1111/j.1758-0854.2011.01051.x

Johansson, Maria, Karlsson, J., Pedersen, E., & Flykt, A. (2012). Factors Governing Human Fear of Brown Bear and Wolf. Human Dimensions of Wildlife, 17(1), 58–74. https://doi.org/10.1080/10871209.2012.619001

Johansson, Maria, Sternudd, C., & Kärrholm, M. (2016). Perceived urban design qualities and affective experiences of walking. Journal of Urban Design, 21(2), 256–275. https://doi.org/10.1080/13574809.2015.1133225

Johnson, L. C., & Corah, N. L. (1963). Racial differences in skin resistance. Science, 139(3556), 766–767.

Jones, K. (2004). Mission drift in qualitative research, or moving toward a systematic review of qualitative studies, moving back to a more systematic narrative review. Qualitative Report, 9(1), 95–112.

Joye, Y. (2007). Architectural Lessons from Environmental Psychology: The Case of Biophilic Architecture. Review of General Psychology, 11(4), 305–328. https://doi.org/10.1037/1089-2680.11.4.305

Kacha, L., Matsumoto, N., & Mansouri, A. (2015). Electrophysiological Evaluation of Perceived Complexity in Streetscapes. Journal of Asian Architecture and Building Engineering, 14(3), 585–592. https://doi.org/10.3130/jaabe.14.585

Kana, R. K., Blum, E. R., Ladden, S. L., & Ver Hoef, L. W. (2012). “How to do things with Words”: Role of motor cortex in semantic representation of action words. Neuropsychologia, 50(14), 3403–3409. https://doi.org/10.1016/j.neuropsychologia.2012.09.006

Kang, S., & Tversky, B. (2016). From hands to minds: Gestures promote understanding. Cognitive Research: Principles and Implications, 1(1), 4. https://doi.org/10.1186/s41235-016-0004-9 Kaplan, R., & Kaplan, S. (1989). The Experience of Nature: A Psychological Perspective. CUP Archive.

Kaplan, S. (1995). The restorative benefits of nature: Toward an integrative framework. Journal of Environmental Psychology, 15(3), 169–182. https://doi.org/10.1016/0272-4944(95)90001-2 Kiecolt-Glaser, J. K., McGuire, L., Robles, T. F., & Glaser, R. (2002). Emotions, Morbidity, and Mortality: New Perspectives from Psychoneuroimmunology. Annual Review of Psychology, 53(1), 83–107. https://doi.org/10.1146/annurev.psych.53.100901.135217

Kim, T.-H., Jeong, G.-W., Baek, H.-S., Kim, G.-W., Sundaram, T., Kang, H.-K., Lee, S.-W., Kim, H.-J., & Song, J.-K. (2010). Human brain activation in response to visual stimulation with rural and urban scenery pictures: A functional magnetic resonance imaging study. Science of The Total Environment, 408(12), 2600–2607. https://doi.org/10.1016/j.scitotenv.2010.02.025

Kita, S., & Özyürek, A. (2003). What does cross-linguistic variation in semantic coordination of speech and gesture reveal?: Evidence for an interface representation of spatial thinking and speaking. Journal of Memory and Language, 48(1), 16–32. https://doi.org/10.1016/S0749-596X(02)00505-3

La Puma, J. (2019). Nature Therapy: An Essential Prescription for Health. Alternative and Complementary Therapies, 25(2), 68–71. https://doi.org/10.1089/act.2019.29209.jlp Lagopoulos, J., Xu, J., Rasmussen, I., Vik, A., Malhi, G. S., Eliassen, C. F., Arntsen, I. E., Sæther, J. G., Hollup, S., Holen, A., Davanger, S., & Ellingsen, Ø. (2009). Increased Theta and Alpha EEG Activity During Nondirective Meditation. The Journal of Alternative and Complementary Medicine, 15(11), 1187–1192. https://doi.org/10.1089/acm.2009.0113

Lederbogen, F., Kirsch, P., Haddad, L., Streit, F., Tost, H., Schuch, P., Wüst, S., Pruessner, J. C., Rietschel, M., Deuschle, M., & Meyer-Lindenberg, A. (2011). City living and urban upbringing affect neural social stress processing in humans. Nature, 474(7352), 498–501. https://doi.org/10.1038/nature10190

Lega, B. C., Jacobs, J., & Kahana, M. (2012). Human hippocampal theta oscillations and the formation of episodic memories. Hippocampus, 22(4), 748–761. https://doi.org/10.1002/hipo.20937 Leisman, G., Moustafa, A. A., & Shafir, T. (2016). Thinking, Walking, Talking: Integratory Motor and Cognitive Brain Function. Frontiers in Public Health, 4. https://doi.org/10.3389/fpubh.2016.00094

Levenson, R. W. (1999). The Intrapersonal Functions of Emotion. Cognition & Emotion, 13(5), 481–504. https://doi.org/10.1080/026999399379159

Levinson, S. C. (2018). Spatial cognition, empathy and language evolution. Studies in Pragmatics, 20, 16–21.

Levinson, S. C., & Holler, J. (2014). The origin of human multi-modal communication. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1651), 20130302. https://doi.org/10.1098/rstb.2013.0302

Liao, Y., Shonkoff, E. T., & Dunton, G. F. (2015). The Acute Relationships Between Affect, Physical Feeling States, and Physical Activity in Daily Life: A Review of Current Evidence. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.01975

Lin, W., Chen, Q., Jiang, M., Tao, J., Liu, Z., Zhang, X., Wu, L., Xu, S., Kang, Y., & Zeng, Q. (2020a). Sitting or Walking? Analyzing the Neural Emotional Indicators of Urban Green Space Behavior with Mobile EEG. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 97(2), 191–203. https://doi.org/10.1007/s11524-019-00407-8

Lin, W., Chen, Q., Jiang, M., Tao, J., Liu, Z., Zhang, X., Wu, L., Xu, S., Kang, Y., & Zeng, Q. (2020b). Sitting or Walking? Analyzing the Neural Emotional Indicators of Urban Green Space Behavior with Mobile EEG. Journal of Urban Health, 97(2), 191–203. https://doi.org/10.1007/s11524-019-00407-8

Lynch, K. (2005). The image of the city (Nachdr.). MIT PRESS.

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109(2), 163.

Marcuse, P. (1986). Abandonment, gentrification, and displacement: Linkages in New York City. In Gentrification in the city, edited by N. Smith and P. Williams, 153-177. Boston: Allen & Unwin.

Mark, L. S. (1987). Eyeheight-scaled information about affordances: A study of sitting and stair climbing. Journal of Experimental Psychology: Human Perception and Performance, 13(3), 361.

Martínez-Soto, J., Gonzales-Santos, L., Pasaye, E., & Barrios, F. A. (2013). Exploration of neural correlates of restorative environment exposure through functional magnetic resonance. Intelligent Buildings International, 5(sup1), 10–28. https://doi.org/10.1080/17508975.2013.807765

Massey, D. (2013). Space, Place and Gender. John Wiley & Sons.

Matos Wunderlich, F. (2008). Walking and Rhythmicity: Sensing Urban Space. Journal of Urban Design, 13(1), 125–139. https://doi.org/10.1080/13574800701803472

Matthews, G., Jones, D. M., & Chamberlain, A. G. (1990). Refining the measurement of mood: The UWIST Mood Adjective Checklist. British Journal of Psychology, 81(1), 17–42. https://doi.org/10.1111/j.2044-8295.1990.tb02343.x

Mavros, P., Austwick, M. Z., & Smith, A. H. (2016). Geo-EEG: Towards the Use of EEG in the Study of Urban Behaviour. Applied Spatial Analysis and Policy, 9(2), 191–212. https://doi.org/10.1007/s12061-015-9181-z

Maxwell, S. E., Lau, M. Y., & Howard, G. S. (2015). Is psychology suffering from a replication crisis? What does “failure to replicate” really mean? American Psychologist, 70(6), 487–498. https://doi.org/10.1037/a0039400

Mazumder, R., Spiers, H., & Ellard, C. (2020). Exposure to High-Rise Buildings Negatively Influences Affect: Evidence from Real World and 360-degree Video [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/w8e4b

McAuley, E., & Rudolph, D. (1995). Physical Activity, Aging, and Psychological Well-Being. Journal of 50

Aging and Physical Activity, 3(1), 67–96. https://doi.org/10.1123/japa.3.1.67

Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology (pp. xii, 266). The MIT Press.

Mehta, A. (1999). Embodied Discourse: On gender and fear of violence. Gender, Place & Culture, 6(1), 67–84. https://doi.org/10.1080/09663699925150

Mennis, J., Mason, M., & Ambrus, A. (2018). Urban greenspace is associated with reduced psychological stress among adolescents: A Geographic Ecological Momentary Assessment (GEMA) analysis of activity space. Landscape and Urban Planning, 174, 1–9. https://doi.org/10.1016/j.landurbplan.2018.02.008

Mittelstaedt, M.-L., & Glasauer, S. (1991). Idiothetic navigation in gerbils and humans. Zool. Jb. Physiol, 95(427–435), 212.

Montague, M., & Bayne, T. (2017). Cognitive Phenomenology. Oxford University Press. Mulckhuyse, M., & Theeuwes, J. (2010). Unconscious attentional orienting to exogenous cues: A review of the literature. Acta Psychologica, 134(3), 299–309. https://doi.org/10.1016/j.actpsy.2010.03.002

Mullan, E. (2003). Do you think that your local area is a good place for young people to grow up? The effects of traffic and car parking on young people’s views. Health & Place, 9(4), 351–360. https://doi.org/10.1016/S1353-8292(02)00069-2

Näätänen, R. (1982). Processing negativity: An evoked-potential reflection. Psychological Bulletin, 92(3), 605–640. https://doi.org/10.1037/0033-2909.92.3.605

Nadel, L. (1991). The hippocampus and space revisited. Hippocampus, 1(3), 221–229. https://doi.org/10.1002/hipo.450010302

Nakamura, R., & Fujii, E. (1992). A comparative study on the characteristics of electroencephalogram inspecting a hedge and a concrete block fence. Journal of the Japenese Institute of Landscape Architects, 55, 139–144.

Nasar, J. L. (1989). Perception, Cognition, and Evaluation of Urban Places. In I. Altman & E. H. Zube (Eds.), Public Places and Spaces (pp. 31–56). Springer US. https://doi.org/10.1007/978-1-4684-5601-1_3

Neale, C., Aspinall, P., Roe, J., Tilley, S., Mavros, P., Cinderby, S., Coyne, R., Thin, N., & Thompson, C. W. (2020). The impact of walking in different urban environments on brain activity in older people. Cities & Health, 4(1), 94–106. https://doi.org/10.1080/23748834.2019.1619893

Negami, H. R., Mazumder, R., Reardon, M., & Ellard, C. G. (2018). Field analysis of psychological effects of urban design: A case study in Vancouver. Cities & Health, 2(2), 106–115. https://doi.org/10.1080/23748834.2018.1548257

Niedermeyer, E., & Lopes da Silva, F. H. (2005). Electroencephalography: Basic principles, clinical applications, and related fields.


Nisbet, E. K., & Zelenski, J. M. (2011). Underestimating Nearby Nature: Affective Forecasting Errors Obscure the Happy Path to Sustainability. Psychological Science. https://doi.org/10.1177/0956797611418527

Nold, C. (2009). Emotional cartography: Technologies of the self. In C. Nold (Ed.), Emotional Cartorgaphy (Vol. 1). Softhook.

Ohly, H., White, M. P., Wheeler, B. W., Bethel, A., Ukoumunne, O. C., Nikolaou, V., & Garside, R. (2016). Attention Restoration Theory: A systematic review of the attention restoration potential of exposure to natural environments. Journal of Toxicology and Environmental Health, Part B, 19(7), 305–343. https://doi.org/10.1080/10937404.2016.1196155

Olbrich, E., & Achermann, P. (2005). Analysis of oscillatory patterns in the human sleep EEG using a novel detection algorithm. Journal of Sleep Research, 14(4), 337–346. https://doi.org/10.1111/j.1365-2869.2005.00475.x

Pandey, J. (1990). The Environment, Culture, and Behavior. In R. Brislin (Ed.), Applied Cross-Cultural Psychology. SAGE.

Pezawas, L., Meyer-Lindenberg, A., Drabant, E. M., Verchinski, B. A., Munoz, K. E., Kolachana, B. S., Egan, M. F., Mattay, V. S., Hariri, A. R., & Weinberger, D. R. (2005). 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: A genetic susceptibility mechanism for depression. Nature Neuroscience, 8(6), 828–834. https://doi.org/10.1038/nn1463

Radcliff, E., Crouch, E., & Strompolis, M. (2018, February 21). Rural–urban differences in exposure to adverse childhood experiences among South Carolina adults. https://doi.org/10.22605/RRH4434

Resch, B. (2013). People as Sensors and Collective Sensing-Contextual Observations Complementing Geo-Sensor Network Measurements. In J. M. Krisp (Ed.), Progress in Location-Based Services (pp. 391–406). Springer. https://doi.org/10.1007/978-3-642-34203-5_22

Resch, B., Summa, A., Zeile, P., & Strube, M. (2016). Citizen-Centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm. Urban Planning, 1(2), 114–127. https://doi.org/10.17645/up.v1i2.617

Reuderink, B., Mühl, C., & Poel, M. (2012). Valence, arousal and dominance in the EEG during game play. International Journal of Autonomous and Adaptive Communications Systems, 6(1), 45–62. https://doi.org/10.1504/IJAACS.2013.050691

Rietveld, E., & Kiverstein, J. (2014). A Rich Landscape of Affordances. Ecological Psychology, 26(4), 325–352. https://doi.org/10.1080/10407413.2014.958035

Rodaway, P. (2002). Sensuous Geographies: Body, Sense and Place. Routledge. Roe, J. J., Aspinall, P. A., Mavros, P., & Coyne, R. (2013). Engaging the brain: The impact of natural versus urban scenes using novel EEG methods in an experimental setting. Environ Sci, 1(2), 93–104.

Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145–172. https://doi.org/10.1037/0033-295X.110.1.145

Russell, J. A., Weiss, A., & Mendelsohn, G. A. (1989). Affect Grid: A single-item scale of pleasure and arousal. Journal of Personality and Social Psychology, 57(3), 493–502. https://doi.org/10.1037/0022-3514.57.3.493

Salvidegoitia, M. P., Jacobsen, N., Bauer, A.-K. R., Griffiths, B., Hanslmayr, S., & Debener, S. (2019). 52

Out and about: Subsequent memory effect captured in a natural outdoor environment with smartphone EEG. Psychophysiology, 56(5), e13331. https://doi.org/10.1111/psyp.13331 Sandelowski, M. (1995). Sample size in qualitative research. Research in Nursing & Health, 18(2), 179–183. https://doi.org/10.1002/nur.4770180211

Scanlon, J. E. M., Redman, E. X., Kuziek, J. W. P., & Mathewson, K. E. (2020). A ride in the park: Cycling in different outdoor environments modulates the auditory evoked potentials. International Journal of Psychophysiology, 151, 59–69. https://doi.org/10.1016/j.ijpsycho.2020.02.016

Schulze, L., Schulze, A., Renneberg, B., Schmahl, C., & Niedtfeld, I. (2019). Neural Correlates of Affective Disturbances: A Comparative Meta-analysis of Negative Affect Processing in Borderline Personality Disorder, Major Depressive Disorder, and Posttraumatic Stress Disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(3), 220–232. https://doi.org/10.1016/j.bpsc.2018.11.004

Scott, B., Brandberg, M., & OÖhman, A. (2001). Measuring the negative mood component of stress experiences: Description and psychometric properties of a short adjective check–list of stress responses. Scandinavian Journal of Psychology, 42(1), 1–7. https://doi.org/10.1111/1467-9450.00208

Sedgwick, P. (2010). Multiple significance tests. BMJ, 340, c2963.

Sedgwick, P. (2012). Multiple significance tests: The Bonferroni correction. BMJ, 344. https://doi.org/10.1136/bmj.e509

Shapiro, L. (2019). Embodied Cognition. Routledge.

Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological Momentary Assessment. Annual Review of Clinical Psychology, 4(1), 1–32. https://doi.org/10.1146/annurev.clinpsy.3.022806.091415 Shoval, N., Schvimer, Y., & Tamir, M. (2018a). Real-Time Measurement of Tourists’ Objective and Subjective Emotions in Time and Space. Journal of Travel Research, 57(1), 3–16. https://doi.org/10.1177/0047287517691155

Shoval, N., Schvimer, Y., & Tamir, M. (2018b). Tracking technologies and urban analysis: Adding the emotional dimension. Cities, 72, 34–42. https://doi.org/10.1016/j.cities.2017.08.005 Siemer, M. (2005). Mood-congruent cognitions constitute mood experience. Emotion, 5(3), 296. Smith, D. W. (2018). Phenomenology. In E. Zalta N. (Ed.), The Stanford Encyclopedia of Philosophy (Summer 2018 Edition). https://plato.stanford.edu/archives/sum2018/entries/phenomenology/ Staudigl, T., & Hanslmayr, S. (2013). Theta Oscillations at Encoding Mediate the Context-Dependent Nature of Human Episodic Memory. Current Biology, 23(12), 1101–1106. https://doi.org/10.1016/j.cub.2013.04.074

Sturm, V. E., Datta, S., Roy, A. R. K., Sible, I. J., Kosik, E. L., Veziris, C. R., Chow, T. E., Morris, N. A., Neuhaus, J., Kramer, J. H., Miller, B. L., Holley, S. R., & Keltner, D. (2020). Big smile, small self: Awe walks promote prosocial positive emotions in older adults. Emotion, No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/emo0000876

Tellegen, A. (1985). Structures of mood and personality and their relevance to assessing anxiety, with an emphasis on self-report. In Anxiety and the anxiety disorders (pp. 681–706).

Lawrence Erlbaum Associates, Inc.

Tomasello, M. (2009). Constructing a Language. Harvard University Press.

Tsunetsugu, Y., Miyazaki, Y., & Sato, H. (2005). Visual effects of interior design in actual-size living rooms on physiological responses. Building and Environment, 40(10), 1341–1346. https://doi.org/10.1016/j.buildenv.2004.11.026

Tyng, C. M., Amin, H. U., Saad, M. N. M., & Malik, A. S. (2017). The Influences of Emotion on Learning and Memory. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.01454 Ulrich, R. S. (1981). Natural Versus Urban Scenes: Some Psychophysiological Effects. Environment and Behavior, 13(5), 523–556. https://doi.org/10.1177/0013916581135001

Ulrich, R. S. (1983). Aesthetic and Affective Response to Natural Environment. In I. Altman & J. F. Wohlwill (Eds.), Behavior and the Natural Environment (pp. 85–125). Springer US. https://doi.org/10.1007/978-1-4613-3539-9_4

Ulrich, R. S., Simons, R. F., Losito, B. D., Fiorito, E., Miles, M. A., & Zelson, M. (1991). Stress recovery during exposure to natural and urban environments. Journal of Environmental Psychology, 11(3), 201–230. https://doi.org/10.1016/S0272-4944(05)80184-7

United Nations Department of Economic and Social Affairs Population Division. (2018). The World’s Cities in 2018—Data Booklet. https://www.un.org/en/events/citiesday/assets/pdf/the_worlds_cities_in_2018_data_booklet. pdf

van Someren, M. W., Barnard, Y. F., & Sandberg, J. A. C. (1994). The Think Aloud Method: A practical Guide to Modelling Cognitive Processes. Academic Press.

Västfjäll, D., & Gärling, T. (2007). Validation of a Swedish short self-report measure of core affect. Scandinavian Journal of Psychology, 48(3), 233–238. https://doi.org/10.1111/j.1467-9450.2007.00595.x

Velarde, M. D., Fry, G., & Tveit, M. (2007). Health effects of viewing landscapes – Landscape types in environmental psychology. Urban Forestry & Urban Greening, 6(4), 199–212. https://doi.org/10.1016/j.ufug.2007.07.001

Wasfi, R. A., Dasgupta, K., Eluru, N., & Ross, N. A. (2016). Exposure to walkable neighbourhoods in urban areas increases utilitarian walking: Longitudinal study of Canadians. Journal of Transport & Health, 3(4), 440–447. https://doi.org/10.1016/j.jth.2015.08.001 Watson, D. (2000). Mood and Temperament. Guilford Press.

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063

Weiner, B. (1985). ‘Spontaneous’ causal thinking. Psychological Bulletin, 97(1), 74–84. https://doi.org/10.1037/0033-2909.97.1.74

Weinreb, A. R., & Rofè, Y. (2013). Mapping feeling: An approach to the study of the emotional response to the built environment and landscape. Journal of Architectural and Planning Research, 30(2), 127–145. JSTOR.

Wexler, M., Kosslyn, S. M., & Berthoz, A. (1998). Motor processes in mental rotation. Cognition, 68(1), 77–94. https://doi.org/10.1016/S0010-0277(98)00032-8

Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636. https://doi.org/10.3758/BF03196322

Wolf, K. L., Lam, S. T., McKeen, J. K., Richardson, G. R. A., van den Bosch, M., & Bardekjian, A. C. (2020). Urban Trees and Human Health: A Scoping Review. International Journal of Environmental Research and Public Health, 17(12), 4371. https://doi.org/10.3390/ijerph17124371

Yi’En, C. (2014). Telling Stories of the City: Walking Ethnography, Affective Materialities, and Mobile Encounters. Space and Culture, 17(3), 211–223. https://doi.org/10.1177/1206331213499468 Zeile, P., Resch, B., Exner, J.-P., & Sagl, G. (2015). Urban Emotions: Benefits and Risks in Using Human Sensory Assessment for the Extraction of Contextual Emotion Information in Urban Planning. In S. Geertman, Jr. Ferreira Joseph, R. Goodspeed, & J. Stillwell (Eds.), Planning Support Systems and Smart Cities (pp. 209–225). Springer International Publishing. https://doi.org/10.1007/978-3-319-18368-8_11

Zeile, P., Resch, B., Loidl, M., Petutschnig, A., & Dörrzapf, L. (2016). Urban Emotions and Cycling Experience – enriching traffic planning for cyclists with human sensor data. GI_Forum 2016, Volume 4, 204–216. https://doi.org/10.1553/giscience2016_01_s204

Zhao, G., Ye, J., Li, Z., & Xue, S. (2017). How and why do Chinese urban students outperform their rural counterparts? China Economic Review, 45, 103–123. https://doi.org/10.1016/j.chieco.2017.06.006

Zhu, Q., & Bingham, G. P. (2011). Human readiness to throw: The size–weight illusion is not an illusion when picking the best objects to throw. Evolution and Human Behavior, 32(4), 288–293. https://doi.org/10.1016/j.evolhumbehav.2010.11.005

Zuckerman, M., & Lubin, B. (1965). Manual for the Multiple Affect Adjective Checklist. Educational and Industrial Testing Service.


Calming Down on (a) Doomsday: An Interview with Dr Susan Clayton

American Psychiatric Association. (2020). Majority of US adults believe climate change is most important issue today. Retrieved 29 November 2021, from https://www.apa.org/news/press/releases/2020/02/climate-change

Callendar, G. (1938). The artificial production of carbon dioxide and its influence on temperature. Quarterly Journal Of The Royal Meteorological Society, 64(275),          223-240. doi: 10.1002/qj.49706427503

Church, J. (2001). How Fast Are Sea Levels Rising?. Science, 294(5543), 802-803. doi: 10.1126/science.1065714

Clayton, S., Manning, C. M., Krygsman, K., & Speiser, M. (2017). Mental health and our changing climate: impacts, implications, and guidance. American Psychological Association, and ecoAmerica. https://www.apa.org/news/press/releases/2017/03/mental-health-climate.pdf.

Costello, A., Abbas, M., Allen, A., Ball, S., Bell, S., & Bellamy, R. et al. (2009). Managing the health effects of climate change. The Lancet, 373(9676), 1693-1733. doi: 10.1016/s0140-6736(09)60935-1

IPCC. (2021, August). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou, Eds.). Cambridge University Press. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Full_Report.pdf

Palter, J. (2015). The Role of the Gulf Stream in European Climate. Annual Review Of Marine Science, 7(1), 113-137. doi: 10.1146/annurev-marine-010814-015656

Rowland, F. (2006). Stratospheric ozone depletion. Philosophical Transactions Of The Royal Society B: Biological Sciences, 361(1469), 769-790. doi: 10.1098/rstb.2005.1783

Weart, S. (2011). Global warming: How skepticism became denial. Bulletin of the Atomic Scientists, 67(1), 41–50. doi: 10.1177/0096340210392966

Smith, L., Sheng, Y., Forster, R., Steffen, K., Frey, K., & Alsdorf, D. (2003). Melting of small Arctic ice caps observed from ERS scatterometer time series. Geophysical Research Letters, 30(20). doi: 10.1029/2003gl017641

Letter-colour consistency but not conscious awareness of synesthetic colours is necessary when defining grapheme-colour synesthesia

Supplementary Material

Appendix A (Dutch questionnaire) Appendix A.1 (Experience with picking colours for letters)

1. Tijdens het uitvoeren van het experiment wist ik zeker welke kleur een letter zou moeten hebben.

2. De kleuren die ik met letters associeer zijn generieke kleuren (bijv. “rood, maar om het even welk type rood”) en niet een specifieke kleurtint (bijv. “deze exacte kleur rood”).

3. Als ik mij een letter probeer voor te stellen in een andere kleur dan de ‘juiste’ kleur, kan ik niet anders dan tegelijkertijd ook aan die ‘juiste’ kleur denken.

4. De kleur associaties die ik heb bij letters voelen meer als ‘weten’ dan als ‘zien’.

5. Ik ervaar kleuren met letters, zelfs als ik er niet aan denk (bijvoorbeeld tijdens het lezen van een boek).

6. De kleuren die ik met letters associeer gebruik ik niet doelbewust (bijvoorbeeld om een boodschappenlijstje te onthouden).

7. Tijdens het experiment had ik het gevoel dat ik gokte welke kleur een letter zou moeten hebben.

8. De kleuren die ik aan letters associeer zijn specifieke kleurschakeringen (bijv. “deze exacte kleur bruin”), niet slechts een generieke kleurcategorie (bijv. “bruin, om het even welk type bruin”).

9. Ik kan gemakkelijk een letter in elke mogelijke kleur voorstellen, zonder interferentie te ervaren van de ‘juiste’ kleur.

10. Mijn ervaring van kleuren bij de letters voelt als ‘zien’ (in plaats van enkel ervaren als ‘weten’).

11. Ik ervaar de geassocieerde kleuren bij letters alleen als ik doelbewust nadenk over de kleur die ze hebben.

12. Ik gebruik de kleuren die ik met letters associeer doelbewust (bijvoorbeeld om iemands naam te onthouden).


Appendix A.2 (Grapheme-colour synesthesia; Eagleman et al., 2007)

1. Bepaalde letters hebben voor mij altijd een bepaalde kleur (bijvoorbeeld, de letter “J” is oranje)


Appendix A.3 (PA questionnaire; Rouw & Scholte, 2007)

1. Wanneer ik naar een bepaalde letter kijk, dan zie ik een specifieke kleur.

2. Wanneer ik naar een bepaalde letter kijk, verschijnt de bijbehorende kleur alleen in mijn gedachten en niet ergens buiten mijn hoofd (zoals op het papier).

3. Wanneer ik naar een bepaalde letter kijk, komt daarvan de bijbehorende synesthetische kleur in mijn gedachten maar op het papier verschijnt enkel de kleur waarin de letter gedrukt is (bijv. een zwarte letter tegen een witte achtergrond).

4. Het is alsof de kleur zich daadwerkelijk op het papier bevindt waarop de letter gedrukt staat.

5. De figuur zelf heeft geen kleur maar ik ben ervan bewust dat deze geassocieerd is met een specifieke kleur.

6. De kleur is als het ware geprojecteerd op de letter.

7. Ik zie letters niet letterlijk in een kleur maar heb een sterk gevoel dat ik weet welke kleur bij een bepaalde letter hoort.

8. De kleur bevindt zich niet op het papier maar zweeft in de ruimte.

9. De kleur heeft dezelfde vorm als de letter.

10. Ik zie de kleur van een letter alleen in mijn hoofd.

11. Ik zie de synesthetische kleur heel duidelijk in nabijheid van de stimulus (bijv. erop of erachter of er overheen).

12. Wanneer ik naar een bepaalde letter kijk, verschijnt de bijbehorende kleur ergens buiten mijn hoofd (zoals op het papier).


Appendix A.4 (Difference synesthetic colours with “real” colours)

1. De synesthetische kleurervaring lijkt sterk op een echte waarneming.

2. Een letter kan een bepaalde synesthetische kleur hebben, maar ik denk nooit per ongeluk dat die letter ook echt die kleur heeft.

3. Het waarnemen van een synesthetische kleur is duidelijk anders dan het waarnemen van een echte kleur (in de buitenwereld).

4. Door de synesthetische ervaring kan ik me soms vergissen, ik denk dan even dat het in de werkelijke buitenwereld aanwezig is.


Appendix A.5 (Brighter, sharper, more powerful)

1. Wat is meer helder, een synesthetische kleur of een echte kleur?

2. Wat is scherper, een synesthetische kleur of een echte kleur?

3. Wat is een krachtiger ervaring, een synesthetische kleurervaring of een echte kleur zien?


Appendix A.6 (CLAN; Rothen, Tsakanikos, Meier, & Ward, 2013)

1. Ik ervaar zelfs synesthetische kleuren wanneer ik niet specifiek aandacht aan hen besteed (bijvoorbeeld als ik een boek lees).

2. Ik zie de synesthetische kleuren op het computerscherm (of heel dichtbij het scherm).

3. Het voelt alsof ik de kleuren actief moet opbrengen, in plaats van dat de kleuren vanzelf komen.

4. Ik ervaar de synesthetische kleuren op verschillende locaties tegelijkertijd (bijvoorbeeld zowel op het scherm als letterlijk in mijn hoofd, of een andere combinatie).

5. Ik ervaar alleen de synesthetische kleuren van letters als ik denk aan hoe ze een kleur hebben.

6. Wanneer ik snel naar de pagina van een boek kijk verschijnen de synesthetische kleuren voordat ik doorheb wat de letters/woorden zijn.

7. Mijn synesthetische kleuren waren sterker in het verleden (d.w.z. jaren geleden).

8. Ik probeer om mijn synesthetische kleuren doelbewust (opzettelijk) te gebruiken in mijn dagelijks leven.

9. De synesthetische kleuren verschijnen automatisch zonder dat ik daar moeite voor hoef te doen.

10. Ik kan wijzen naar de locatie van de synesthetische kleuren.

11. Mijn synesthetische kleuren zijn niet in intensiteit veranderd over de jaren heen.

12. Ik gebruik mijn synesthetische kleuren doelbewust voor het onthouden van reeksen van getallen (bijvoorbeeld pincodes of telefoonnummers).

13. Ik “zie” geen kleuren wanneer ik naar letters kijk.

14. Ik gebruik mijn synesthetische kleuren om datums te onthouden en afspraken te plannen (bijvoorbeeld 28.05.2020).

15. Mijn synesthetische kleuren waren zwakker in het verleden (d.w.z. jaren geleden).

16. De kleur lijkt op het scherm te zijn, waar de letter geprint is.


Appendix A.7 (Different forms of synesthesia)

1. Nummers hebben voor mij een kleur (bijv. ‘de 3 is geel’)

2. Letters hebben voor mij een kleur (bijv. de C is blauw)

3. Letters hebben een geslacht (bijv. ‘B is vrouwelijk’)

4. Letters hebben een persoonlijkheid (bijv. ‘G is vriendelijk en sociaal’)

5. Geluiden roepen een kleur op (bijv. ‘Vioolmuziek is oranje’, of ‘jouw stem is geel’)

6. Dagen, maanden of jaartallen hebben een locatie in de ruimte (bijv. ‘januari staat diagonaal rechts van februari’)

7. Nummers hebben een locatie in de ruimte (bijv. ‘de 3 staat vlak achter de 4’)

8. Dagen van de week, maanden of jaartallen hebben een kleur (bijv. ‘februari is donkerpaars’) 


Arnold, D. H., Wegener, S. V., Brown, F., & Mattingley, J. B. (2012). Precision of synesthetic color matching resembles that for recollected colors rather than physical colors. Journal of Experimental Psychology: Human Perception and Performance, 38(5), 1078. 

Asher, J. E., Lamb, J. A., Brocklebank, D., Cazier, J. B., Maestrini, E., Addis, L., … & Monaco, A. P. (2009). A whole-genome scan and fine-mapping linkage study of auditory-visual synesthesia reveals evidence of linkage to chromosomes 2q24, 5q33, 6p12, and 12p12. The American Journal of Human Genetics, 84(2), 279-285. 

Banissy, M. J., Walsh, V., & Ward, J. (2009). Enhanced sensory perception in synaesthesia. Experimental brain research, 196(4), 565-571. 

Barnett, K. J., Finucane, C., Asher, J. E., Bargary, G., Corvin, A. P., Newell, F. N., & Mitchell, K. J. (2008). Familial patterns and the origins of individual differences in synaesthesia. Cognition, 106(2), 871-893. 

Bargary, G., & Mitchell, K. J. (2008). Synaesthesia and cortical connectivity. Trends in neurosciences, 31(7), 335-342. 

Blake, R., Palmeri, T. J., Marois, R., & Kim, C. Y. (2005). On the perceptual reality of synesthetic color. Synesthesia: Perspectives from cognitive neuroscience, 47-73. 

Brang, D., & Ahn, E. (2019). Double-blind study of visual imagery in grapheme-color synesthesia. Cortex, 117, 89-95. 

Carmichael, D. A., Down, M. P., Shillcock, R. C., Eagleman, D. M., & Simner, J. (2015). Validating a standardised test battery for synesthesia: Does the Synesthesia Battery reliably detect synesthesia?. Consciousness and Cognition, 33, 375-385. 

Chalmers, D. J. (1995). Facing up to the problem of consciousness. J. Conscious. Stud. 2, 200–219. 

Chiou, R., & Rich, A. N. (2014). The role of conceptual knowledge in understanding synaesthesia: Evaluating 

contemporary findings from a “hub-and-spokes” perspective. Frontiers in Psychology, 5, 105. 

Chiou, R., Rich, A. N., Rogers, S., & Pearson, J. (2018). Exploring the functional nature of synaesthetic colour: Dissociations from colour perception and imagery. Cognition, 177, 107-121. 

Chun, C. A., & Hupé, J. M. (2016). Are synesthetes exceptional beyond their synesthetic associations? A systematic comparison of creativity, personality, cognition, and mental imagery in synesthetes and controls. British Journal of Psychology, 107(3), 397-418. 

Cohen Kadosh, R., Henik, A., Catena, A., Walsh, V., & Fuentes, L. J. (2009). Induced cross-modal synaesthetic experience without abnormal neuronal connections. Psychological Science, 20(2), 258-265. 

Colizoli, O., Murre, J. M., & Rouw, R. (2014). Defining (trained) grapheme-color synesthesia. Frontiers in human neuroscience, 8, 368. 

Cytowic, R. E. (1997). Synaesthesia: Phenomenology and neuropsychology – a review of current knowledge. In S. Baron‐Cohen & J. E. Harrison (Eds.), Synaesthesia: Classic and contemporary readings (pp. 17–42). Oxford : Blackwell. 

Dixon, M. J., Smilek, D., Cudahy, C., & Merikle, P. M. (2000). Five plus two equals yellow. Nature, 406(6794), 365-365. 

Dixon, M. J., Smilek, D., & Merikle, P. M. (2004). Not all synaesthetes are created equal: Projector versus associator synaesthetes. Cognitive, Affective, & Behavioral Neuroscience, 4(3), 335-343. 

Eagleman, D. M. (2012). Synaesthesia in its protean guises. British Journal of Psychology, 103(1), 16-19. 

Eagleman, D. M., Kagan, A. D., Nelson, S. S., Sagaram, D., & Sarma, A. K. (2007). A standardized test battery for the study of synesthesia. Journal of neuroscience methods, 159(1), 139-145. 

Edquist, J., Rich, A. N., Brinkman, C., & Mattingley, J. B. (2006). Do synaesthetic colours act as unique features in visual search?. Cortex, 42(2), 222-231. 

Forest, T. A., Lichtenfeld, A., Alvarez, B., & Finn, A. S. (2019). Superior learning in synesthetes: Consistent grapheme-color associations facilitate statistical learning. Cognition, 186, 72-81. 

Hänggi, J., Wotruba, D., & Jäncke, L. (2011). Globally altered structural brain network topology in grapheme-color synesthesia. Journal of Neuroscience, 31(15), 5816-5828. 

Hoo, K. A., Tvarlapati, K. J., Piovoso, M. J., & Hajare, R. (2002). A method of robust multivariate outlier replacement. Computers & chemical engineering, 26(1), 17-39. 

Hupé, J. M., & Dojat, M. (2015). A critical review of the neuroimaging literature on synesthesia. Frontiers in human neuroscience, 9, 103. 

IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp. 

Jansari, A. S., Spiller, M. J., & Redfern, S. (2006). Number synaesthesia: When hearing “four plus five” looks like gold. Cortex, 42(2), 253-258. 

Kim, C. Y., & Blake, R. (2005). Watercolor illusion induced by synesthetic colors. Perception, 34(12), 1501-1507. 

Kim, C. Y., Blake, R., Palmeri, T. J., Marois, R., & Whetsell, W. (2003). Synesthetic colors act like real colors and interact with real colors. Journal of Vision, 3(9), 620-620. 

De Lange, F. P., Heilbron, M., & Kok, P. (2018). How do expectations shape perception?. Trends in cognitive sciences, 22(9), 764-779. 

van Leeuwen, T. M., Singer, W., & Nikolić, D. (2015). The merit of synesthesia for consciousness research. Frontiers in psychology, 6, 1850. 

Lynall, M. E., & Blakemore, C. (2013). What synesthesia isn’t. The Oxford Handbook of Synesthesia, 959-98. 

Marks, D. F. (1973). Visual imagery differences in the recall of pictures. British journal of Psychology, 64(1), 17-24. 

Mattingley, J. B. (2009). Attention, automaticity, and awareness in synesthesia. Annals of the New York Academy of Sciences, 1156(1), 141-167. 

Mattingley, J. B., Rich, A. N., Yelland, G., & Bradshaw, J. L. (2001). Unconscious priming eliminates automatic binding of colour and alphanumeric form in synaesthesia. Nature, 410(6828), 580. 

Maurer, D., & Mondloch, C. J. (2005). Neonatal synesthesia: A reevaluation. Synesthesia: Perspectives from cognitive neuroscience, 193-213. 

McGurk, H., & MacDonald, J. (1976). Hearing lips and seeing voices. Nature, 264(5588), 746-748. 

Meier, B., & Rothen, N. (2009). Training grapheme-colour associations produces a synaesthetic Stroop effect, but not a conditioned synaesthetic response. Neuropsychologia, 47(4), 1208-1211. 

Meier, B., & Rothen, N. (2013). Synaesthesia and memory. Oxford handbook of synaesthesia, 692-706. 

Mena, B., José, M., Alarcón, R., Arnau Gras, J., Bono Cabré, R., & Bendayan, R. (2017). Non-normal data: Is ANOVA still a valid option?. Psicothema, 2017, vol. 29, num. 4, p. 552-557. 

Nijboer, T. C., Satris, G., & Van der Stigchel, S. (2011). The influence of synesthesia on eye movements: no synesthetic pop-out in an oculomotor target selection task. Consciousness and cognition, 20(4), 1193-1200. 

Nikolić, D., Lichti, P., & Singer, W. (2007). Color opponency in synaesthetic experiences. Psychological Science, 18(6), 481-486. 

Nixon, R. M., Wonderling, D., & Grieve, R. D. (2010). Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared. Health economics, 19(3), 316-333. 

O’Callaghan, C. (2008). Seeing what you hear: Cross‐modal illusions and perception. Philosophical Issues, 18(1), 316-338. 

Palmeri, T. J., Blake, R., Marois, R., Flanery, M. A., & Whetsell, W. (2002). The perceptual reality of synesthetic colors. Proceedings of the National Academy of Sciences, 99(6), 4127-4131. 

The output for this paper was generated using Qualtrics software, Version 072020 of Qualtrics. Copyright © 2020 Qualtrics. Qualtrics and all other Qualtrics product or service names are registered trademarks or trademarks of Qualtrics, Provo, UT, USA. https://www.qualtrics.com 

Ramachandran, V. S., & Azoulai, S. (2006). Synesthetically induced colors evoke apparent-motion perception. Perception, 35(11), 1557-1560. 

Ramachandran, V. S., & Hubbard, E. M. (2001). Psychophysical investigations into the neural basis of synaesthesia. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268(1470), 979-983. 

Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological bulletin, 114(3), 510. 

Reisberg, D., Pearson, D. G., & Kosslyn, S. M. (2003). Intuitions and introspections about imagery: The role of imagery experience in shaping an investigator’s theoretical views. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 17(2), 147-160. 

Root, N. B., Rouw, R., Asano, M., Kim, C. Y., Melero, H., Yokosawa, K., & Ramachandran, V. S. (2018). Why is the synesthete’s “A” red? Using a five-language dataset to disentangle the effects of shape, sound, semantics, and ordinality on inducer–concurrent relationships in grapheme-color synesthesia. cortex, 99, 375-389. 

Rouw, R., Case, L., Gosavi, R., & Ramachandran, V. (2014). Color associations for days and letters across different languages. Frontiers in psychology, 5, 369. 

Rouw, R., & Root, N. B. (2019). Distinct colours in the ‘synaesthetic colour palette’. Philosophical Transactions of the Royal Society B, 374(1787), 20190028. 

Rouw, R., & Scholte, H. S. (2007). Increased structural connectivity in grapheme-color synesthesia. Nature neuroscience, 10(6), 792-797. 

Rouw, R., & Scholte, H. S. (2010). Neural basis of individual differences in synesthetic experiences. Journal of Neuroscience, 30(18), 6205-6213. 

Rouw, R., Scholte, H. S., & Colizoli, O. (2011). Brain areas involved in synaesthesia: a review. Journal of neuropsychology, 5(2), 214-242. 

Rothen, N., & Meier, B. (2014). Acquiring synaesthesia: insights from training studies. Frontiers in human neuroscience, 8, 109. 

Rothen, N., Meier, B., & Ward, J. (2012). Enhanced memory ability: insights from synaesthesia. Neuroscience & Biobehavioral Reviews, 36(8), 1952-1963. 

Rothen, N., Seth, A. K., Witzel, C., & Ward, J. (2013). Diagnosing synaesthesia with online colour pickers: maximising sensitivity and specificity. Journal of neuroscience methods, 215(1), 156-160. 

Sagiv, N., Heer, J., & Robertson, L. (2006). Does binding of synesthetic color to the evoking grapheme require attention?. Cortex, 42(2), 232-242. 

Simner, J. (2012). Defining synaesthesia. British journal of psychology, 103(1), 1-15. 

Simner, J. (2013). Why are there different types of synesthete?. Frontiers in Psychology, 4, 558. 

Simner, J., Mulvenna, C., Sagiv, N., Tsakanikos, E., Witherby, S. A., Fraser, C., … & Ward, J. (2006). Synaesthesia: The 

prevalence of atypical cross-modal experiences. Perception, 35(8), 1024-1033. 

Simner, J., & Hubbard, E. M. (Eds.). (2013). Oxford handbook of synesthesia. Oxford University Press. 

Spiller, M. J., Harkry, L., McCullagh, F., Thoma, V., & Jonas, C. (2019). Exploring the relationship between grapheme colour-picking consistency and mental imagery. Philosophical Transactions of the Royal Society B, 374(1787), 20190023. 

Stein, B. E., & Stanford, T. R. (2008). Multisensory integration: current issues from the perspective of the single neuron. Nature Reviews Neuroscience, 9(4), 255-266. 

Steven, Megan. S. 2004. Neuroimaging of multisensory processing and synaesthesia. DPhil thesis, University of Oxford. 

Ward, J. (2013). Synesthesia. Annual review of psychology, 64, 49-75. 

Ward, J. (2019). Individual differences in sensory sensitivity: A synthesizing framework and evidence from normal variation and developmental conditions. Cognitive neuroscience, 10(3), 139-157. 

Ward, J., Hovard, P., Jones, A., & Rothen, N. (2013). Enhanced recognition memory in grapheme-color synaesthesia for different categories of visual stimuli. Frontiers in psychology, 4, 762. 

Ward, J., Jonas, C., Dienes, Z., & Seth, A. (2010). Grapheme-colour synaesthesia improves detection of embedded shapes, but without pre-attentive ‘pop-out’of synaesthetic colour. Proceedings of the Royal Society B: Biological Sciences, 277(1684), 1021-1026. 

Ward, J., Li, R., Salih, S., & Sagiv, N. (2007). Varieties of grapheme-colour synaesthesia: a new theory of phenomenological and behavioural differences. Consciousness and cognition, 16(4), 913-931. 

Ward, J., & Simner, J. (2003). Lexical-gustatory synaesthesia: linguistic and conceptual factors. Cognition, 89(3), 237-261. 

Watson, M. R., Chromý, J., Crawford, L., Eagleman, D. M., Enns, J. T., & Akins, K. A. (2017). The prevalence of synaesthesia depends on early language learning. Consciousness and Cognition, 48, 212-231. 

Weiss, F., Greenlee, M. W., & Volberg, G. (2018). Gray bananas and a red letter A—From synesthetic sensation to memory colors. i-Perception, 9(3), 2041669518777515. 

Witthoft, N., & Winawer, J. (2013). Learning, memory, and synesthesia. Psychological science, 24(3), 258-265. 

Wollen, K. A., & Ruggiero, F. T. (1983). Colored-letter synesthesia. Journal of Mental Imagery. 

Issue 12

Is That Child Friends... with a Robot? Taking a Look from the Uncanny Valley

— Original Piece

Barr, R. (2013). Memory Constraints on Infant Learning From Picture Books, Television, and Touchscreens. Child Development Perspectives, 7(4), 205–210. https://doi.org/10.1111/cdep.12041

Bedford, R., Saez de Urabain, I. R., Cheung, C. H. M., Karmiloff-Smith, A., & Smith, T. J. (2016). Toddlers’ Fine Motor Milestone Achievement Is Associated with Early Touchscreen Scrolling. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01108

Brink, K. A., Gray, K., & Wellman, H. M. (2019). Creepiness Creeps In: Uncanny Valley Feelings Are Acquired in Childhood. Child Development, 90(4), 1202–1214. https://doi.org/10.1111/cdev.12999

COUNCIL ON COMMUNICATIONS AND MEDIA. (2016). Media and Young Minds. Pediatrics, 138(5), e20162591. https://doi.org/10.1542/peds.2016-2591

Cristia, A., & Seidl, A. (2015). Parental Reports on Touch Screen Use in Early Childhood. PLOS ONE, 10(6), e0128338. https://doi.org/10.1371/journal.pone.0128338

MacDorman, K. F., & Ishiguro, H. (2006). The uncanny advantage of using androids in cognitive and social science research. Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems, 7(3), 297–337. https://doi.org/10.1075/is.7.3.03mac

Mejías, C. S., Echevarría, C., Nuñez, P., Manso, L., Bustos, P., Leal, S., & Parra, C. (2013).         Ursus: A robotic assistant for training of children with motor impairments. In Converging        Clinical and Engineering Research on Neurorehabilitation (pp. 249-253). Springer,          Berlin, Heidelberg.

Milligan, K., Astington, J. W., & Dack, L. A. (2007). Language and Theory of Mind: Meta-Analysis of the Relation Between Language Ability and False-belief Understanding. Child Development, 78(2), 622–646. https://doi.org/10.1111/j.1467-8624.2007.01018.x

Movellan, J., Eckhardt, M., Virnes, M., & Rodriguez, A. (2009). Sociable robot improves toddler vocabulary skills. Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction – HRI ’09, 307. https://doi.org/10.1145/1514095.1514189

Obaid, M., Baykal, G. E., Yantaç, A. E., & Barendregt, W. (2018). Developing a Prototyping Method for Involving Children in the Design of Classroom Robots. International Journal of Social Robotics, 10(2), 279–291. https://doi.org/10.1007/s12369-017-0450-7

Ricks, D. J., & Colton, M. B. (2010). Trends and considerations in robot-assisted autism therapy. 2010 IEEE International Conference on Robotics and Automation, 4354–4359. https://doi.org/10.1109/ROBOT.2010.5509327

Rideout, V. (2013).  Zero to Eight: Children’s Media Use in America 2013; Common Sense                     Media. Available at: https://www.commonsensemedia.org/research/zero-to-eight-           childrens-media-use-in-america-2013 (accessed May 18, 2021).

Serholt, S., Barendregt, W., Vasalou, A., Alves-Oliveira, P., Jones, A., Petisca, S., & Paiva, A. (2017). The case of classroom robots: Teachers’ deliberations on the ethical tensions. AI & SOCIETY, 32(4), 613–631. https://doi.org/10.1007/s00146-016-0667-2

Steckenfinger, S. A., & Ghazanfar, A. A. (2009). Monkey visual behavior falls into the uncanny valley. Proceedings of the National Academy of Sciences, 106(43), 18362–18366. https://doi.org/10.1073/pnas.0910063106

Stein, J.-P., & Ohler, P. (2017). Venturing into the uncanny valley of mind—The influence of mind attribution on the acceptance of human-like characters in a virtual reality setting. Cognition, 160, 43–50. https://doi.org/10.1016/j.cognition.2016.12.010

Strasburger, V. C., Jordan, A. B., & Donnerstein, E. (2012). Children, Adolescents, and the Media: Pediatric Clinics of North America, 59(3), 533–587. https://doi.org/10.1016/j.pcl.2012.03.025

Wellman, H. M. (2014). Making minds: How theory of mind develops. Oxford University Press.


‘My depression, your depression - same name, different story’: The use of digital storytelling in mental health science.

— Original Piece

Baker, F. A., Metcalf, O., Varker, T., & O’Donnell, M. (2018). A systematic review of the efficacy of creative arts therapies in the treatment of adults with PTSD. Psychological Trauma: Theory, Research, Practice, and Policy, 10(6), 643. https://doi.org/10.1037/tra0000353

Coleman, L., Ramm, J., & Cooke, R. (2010). The effectiveness of an innovative intervention aimed at reducing binge drinking among young people: Results from a pilot study. Drugs: Education, Prevention and Policy, 17(4), 413–430. https://doi.org/10.3109/09687630802572599

Cunsolo Willox, A., Harper, S. L., Edge, V. L., Storytelling, ‘My Word’, Lab, D. M., & Government, R. I. C. (2013). Storytelling in a digital age: Digital storytelling as an emerging narrative method for preserving and promoting indigenous oral wisdom. Qualitative Research, 13(2), 127–147.  https://doi.org/10.1177/1468794112446105

De Vecchi, N., Kenny, A., Dickson‐Swift, V., & Kidd, S. (2016). How digital storytelling is used in mental health: A scoping review. International Journal of Mental Health Nursing, 25(3), 183–193. https://doi.org/10.1111/inm.12206

Ferrari, M., Rice, C., & McKenzie, K. (2015). ACE Pathways Project: Therapeutic catharsis in digital storytelling. Psychiatric Services (Washington, DC), 66(5), 556–556. https://doi.org/10.1176/appi.ps.660505

Given, L. M. (2008). Lived Experience. In The SAGE Encyclopedia of Qualitative Research Methods. SAGE Publications, Inc. https://doi.org/10.4135/9781412963909

Lambert, J., & Hessler, B. (2018). Digital Storytelling: Capturing Lives, Creating Community. Routledge.

Lenette, C., & Boddy, J. (2013). Visual ethnography and refugee women: Nuanced understandings of lived experiences. Qualitative Research Journal. https://doi.org/10.1108/14439881311314621

Matthews, N., & Sunderland, N. (2013). Digital life-story narratives as data for policy makers and practitioners: Thinking through methodologies for large-scale multimedia qualitative datasets. Journal of Broadcasting & Electronic Media, 57(1), 97–114. https://doi.org/10.1080/08838151.2012.761703

Rice, C., Chandler, E., Harrison, E., Liddiard, K., & Ferrari, M. (2015). Project Re• Vision: Disability at the edges of representation. Disability & Society, 30(4), 513–527. https://doi.org/10.1080/09687599.2015.1037950

Richards, C. (2010). Opinion: Them and us in mental health services. The Psychologist, 23, 40–41.

Sawyer, C. B., & Willis, J. M. (2011). Introducing digital storytelling to influence the behavior of children and adolescents. Journal of Creativity in Mental Health, 6(4), 274–283. https://doi.org/10.1080/15401383.2011.630308

Shafir, T., Orkibi, H., Baker, F. A., Gussak, D., & Kaimal, G. (2020). Editorial: The State of the Art in Creative Arts Therapies. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00068

Sljivic, H., Sutherland, I., Stannard, C., Ioppolo, C., & Morrisby, C. (2021). Changing attitudes towards older adults: Eliciting empathy through digital storytelling. Gerontology & Geriatrics Education, 1–14. https://doi.org/10.1080/02701960.2021.1900838

Spector, R., Smojkis, M., & Chilton, E. H. (2011). Service user involvement in a ward staff training project: Participants’ experiences of making digital stories. Clinical Psychology Forum, 220, 49–53.

Stenhouse, R., Tait, J., Hardy, P., & Sumner, T. (2013). Dangling conversations: Reflections on the process of creating digital stories during a workshop with people with early-stage dementia. Journal of Psychiatric and Mental Health Nursing, 20(2), 134–141. https://doi.org/10.1111/j.1365-2850.2012.01900.x

Wexler, L., Gubrium, A., Griffin, M., & DiFulvio, G. (2013). Promoting positive youth development and highlighting reasons for living in Northwest Alaska through digital storytelling. Health Promotion Practice, 14(4), 617–623. https://doi.org/10.1177/1524839912462390

Willis, N., Frewin, L., Miller, A., Dziwa, C., Mavhu, W., & Cowan, F. (2014). “My story”—HIV positive adolescents tell their story through film. Children and Youth Services Review, 45, 129–136. https://doi.org/10.1016/j.childyouth.2014.03.029

Replication, stability and extension of the psychopathy symptomsymptom network: The core characteristics depend on whom you ask

— Research Project

Blair, J. (1995). A cognitive developmental approach to morality: Investigating the psychopath. Cognition, 57(1), 1-29.

Blair, J., Mitchell, D., & Blair, K. (2005). The Psychopath: Emotion and the Brain. Blackwell Publishing.

Borsboom, D., & Cramer, A. (2013). Network analysis: an integrative approach to the structure of psychopathology. Annu Rev Clin Psychol, 9, 91-121.

Boschloo, L., van Borkulo, C. D., Rhemtulla, M., Keyes, K. M., Borsboom, D., & Schoevers, R. A. (2015). The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders. PLoS One, 10(9), e0137621. doi:10.1371/journal.pone.0137621

Bringmann, L. F., Lemmens, L. H., Huibers, M. J., Borsboom, D., & Tuerlinckx, F. (2015). Revealing the dynamic network structure of the Beck Depression Inventory-II. Psychol Med, 45(4), 747-757. doi:10.1017/S0033291714001809

Christ, L. (2016). Towards a Network Model of Psychopathy: Lack of Empathy is Central to the Psychopathy Network in Criminal Offenders (Master’s thesis). University of Amsterdam, Amsterdam, the Netherlands.

Cleckley, H. (1941). The mask of sanity; an attempt to reinterpret the so-called psychopathic personality. JAMA, 117(6), 493. doi:10.1001/jama.1941.02820320085028

Coid, J., Yang, M., Ullrich, S., Roberts, A., & Hare, R. D. (2009). Prevalence and correlates of psychopathic traits in the household population of Great Britain. Int J Law Psychiatry, 32(2), 65-73. doi:10.1016/j.ijlp.2009.01.002

Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. J Res Pers, 54, 13-29. doi:10.1016/j.jrp.2014.07.003

Cramer, A., Borsboom, D., Aggen, S., & Kendler, K. (2012). The pathoplasticity of dysphoric episodes: differential impact of stressful life events on the pattern of depressive symptom inter-correlations. Psychol Med, 42(05), 957-965.

Dawel, A., O’Kearney, R., McKone, E., & Palermo, R. (2012). Not just fear and sadness: meta-analytic evidence of pervasive emotion recognition deficits for facial and vocal expressions in psychopathy. Neurosci Biobehav Rev, 36(10), 2288-2304.

Epskamp, S. (2015). bootnet: Bootstrap methods for various network estimation routines. Retrieved from https://cran.r-project.org/web/packages/bootnet/bootnet.pdf

Epskamp, S., Borsboom, D., & Fried, E. (2016). Estimating Psychological Networks and their Stability: a Tutorial Paper. arXiv preprint arXiv:1604.08462.

Epskamp, S., Cramer, A., Waldorp, L., Schmittmann, V., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. J Stat Softw, 48(4), 1-18.

Frick, P. J. (2004). The inventory of callous-unemotional traits. Unpublished rating scale.

Frick, P. J., Ray, J. V., Thornton, L. C., & Kahn, R. E. (2014). Can callous-unemotional traits enhance the understanding, diagnosis, and treatment of serious conduct problems in children and adolescents? A comprehensive review. Psychol Bull, 140(1), 1-57. doi:10.1037/a0033076

Fried, E. I., Epskamp, S., Nesse, R. M., Tuerlinckx, F., & Borsboom, D. (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. J Affect Disord, 189, 314-320. doi:10.1016/j.jad.2015.09.005

Fruchterman, T. M., & Reingold, E. M. (1991). Graph drawing by force directed placement. Softw Pract Exp, 21(11), 1129-1164.

Hanson, R. K., & Morton-Bourgon, K. E. (2005). The characteristics of persistent sexual offenders: a meta-analysis of recidivism studies. J Consult Clin Psychol, 73(6), 1154.

Hare, R. D. (1991). The Hare Psychopathy Checklist—Revised. Toronto: Multi-Health Systems.

Hare, R. D. (2003). The Hare Psychopathy Checklist—Revised (2nd ed.). Toronto: Multi-Health Systems.

Hare, R. D., & Neumann, G. S. (2005). The PCL-R Assessment of Psychopathy: Development, Structural Properties, and New Directions. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 58-88). Guilford Press.

Harpur, T. J., Hakstian, A. R., & Hare, R. D. (1988). Factor structure of the Psychopathy Checklist. J Consult Clin Psychol, 56(5), 741.

Jolliffe, D., & Farrington, D. P. (2004). Empathy and offending: A systematic review and meta-analysis. Aggress Violent Behav, 9(5), 441-476.

Levenson, M. R., Kiehl, K. A., & Fitzpatrick, C. M. (1995). Assessing psychopathic attributes in a noninstitutionalized population. J Pers Soc Psychol, 68(1), 151.

Lilienfeld, S. O., & Andrews, B. P. (1996). Development and preliminary validation of a self-report measure of psychopathic personality traits in noncriminal population. J Pers Assess, 66(3), 488-524.

Lilienfeld, S. O., & Fowler, K. A. (2005). The Self-Report Assessment of Psychopathy: Problems, Pitfalls, and Promises. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 107133). Guilford Press. Lilienfeld, S. O., & Widows, M. R. (2005). PPI-R: Psychopathic personality inventory revised: Professional

Manual: Psychological Assessment Resources, Incorporated.

Lykken, D. T. (1995). The antisocial personalities. Psychology Press.

Miller, J. D., Jones, S. E., & Lynam, D. R. (2011). Psychopathic traits from the perspective of self and informant reports: Is there evidence for a lack of insight? J Abnorm Psychol, 120(3), 758. 

Montagne, B., van Honk, J., Kessels, R. P., Frigerio, E., Burt, M., van Zandvoort, M. J., … & de Haan, E. H. (2005). Reduced efficiency in recognising fear in subjects scoring high on psychopathic personality characteristics. Pers Individ Dif, 38(1), 5-11.

Murphy, B., Lilienfeld, S., Skeem, J., & Edens, J. (2016, February 11). Are Fearless Dominance Traits Superfluous in Operationalizing Psychopathy? Incremental Validity and Sex Differences. Psychol Assess. Advance online publication. http://dx.doi.org/10.1037/pas0000288

Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Soc Networks, 32(3), 245-251.

Patrick, C. J. (2005). Back to the Future: Cleckley as a Guide to the Next Generation of Psychopathy Research. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 605-617). Guilford Press.

Poythress, N. G., Lilienfeld, S. O., Skeem, J. L., Douglas, K. S., Edens, J. F., Epstein, M., & Patrick, C. J. (2010). Using the PCL-R to help estimate the validity of two self-report measures of psychopathy with offenders. Assess, 17(2), 206-219. doi:10.1177/1073191109351715

R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from https://www.R-project.org/

Sellbom, M. (2011). Elaborating on the construct validity of the Levenson Self-Report Psychopathy Scale in incarcerated and non-incarcerated samples. Law Hum Behav, 35(6), 440-451.

Sherman, E. D., & Lynam, D. R. (in press). Psychopathy and Low Communion: An Overlooked and Underappreciated Core Feature.Personal Disord.

Skeem, J. L., & Cauffman, E. (2003). Views of the downward extension: comparing the Youth Version of the Psychopathy Checklist with the Youth Psychopathic traits Inventory. Behav Sci Law, 21(6), 737-770. doi:10.1002/bsl.563

Skeem, J. L., & Cooke, D. J. (2010). Is criminal behavior a central component of psychopathy? Conceptual directions for resolving the debate. Psychol Assess, 22(2), 433-445. doi:10.1037/a0008512

Sullivan, E. A., & Kosson, D. S. (2005). Ethnic and Cultural Variations in Psychopathy. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 437-458). Guilford Press.

Uzieblo, K., Verschuere, B., Van den Bussche, E., & Crombez, G. (2010). The validity of the Psychopathic Personality Inventory—Revised in a community sample. Assess, 17(3), 334-346. doi:10.1177/1073191109356544

Vachon, D. D., & Lynam, D. R. (2015). Fixing the problem with empathy development and validation of the affective and cognitive measure of empathy. Assess. doi:10.1177/1073191114567941

Vachon, D. D., Lynam, D. R., & Johnson, J. A. (2014). The (non) relation between empathy and aggression:

Surprising results from a meta-analysis. Psychol Bull, 140(3), 751. doi:10.1037/a0035236

van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W., Waldorp, L. J., & Schoevers, R. A. (2015). Association of Symptom Network Structure With the Course of Longitudinal Depression. JAMA Psychiatry, 72(12), 1219-1226. doi:10.1001/jamapsychiatry.2015.2079

Vize, C. E., Lynam, D. R., Lamkin, J., Miller, J. D., & Pardini, D. (2016). Identifying Essential Features of Juvenile Psychopathy in the Prediction of Later Antisocial Behavior Is There an Additive, Synergistic, or Curvilinear Role for Fearless Dominance? Clin Psychol Sci, 4(3) 572-590. doi:10.1177/2167702615622384

Waldman, I. D., & Rhee, S. H. (2006). Genetic and environmental influences on psychopathy and antisocial behavior. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 205-228). Guilford Press.

The Female Experience of Autism

— Original Piece

American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Arlington, VA: American Psychiatric Association, (2013).

Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). Journal Of  Autism And Developmental Disorders, 31(1), 5-17. doi: 10.1023/a:1005653411471


Baron-Cohen, S. (2010). Empathizing, systemizing, and the extreme male brain theory of autism. Sex Differences In The Human Brain, Their Underpinnings And Implications, 167-175. doi: 10.1016/b978-0-444-53630-3.00011-7


Baron-Cohen, S., Bowen, D., Holt, R., Allison, C., Auyeung, B., & Lombardo, M. et al. (2015). The “Reading the Mind in the Eyes” Test: Complete Absence of Typical Sex Difference in ~400 Men and Women with Autism. PLOS ONE, 10(8), e0136521. doi: 10.1371/journal.pone.0136521


Bishop, D. (2010). Overlaps Between Autism and Language Impairment: Phenomimicry or Shared Etiology?. Behavior Genetics, 40(5), 618-629. doi: 10.1007/s10519-010-9381-x


Cage, E., & Troxell-Whitman, Z. (2019). Understanding the Reasons, Contexts and Costs of Camouflaging for Autistic Adults. Journal Of Autism And Developmental Disorders49(5), 1899-1911. doi: 10.1007/s10803-018-03878-x


Cashin, A., Sci, D., & Barker, P. (2009). The Triad of Impairment in Autism Revisited. Journal Of Child And Adolescent Psychiatric Nursing, 22(4), 189-193. 

Gross, J., & John, O. (1997). Revealing feelings: Facets of emotional expressivity in self-reports, peer ratings, and behavior. Journal Of Personality And Social Psychology, 72(2), 435-448. doi: 10.1037/0022-3514.72.2.435


Haney, J. (2015). Autism, females, and the DSM-5: Gender bias in autism diagnosis. Social Work In Mental Health, 14(4), 396-407. doi: 10.1080/15332985.2015.1031858


Hull, L., Petrides, K., Allison, C., Smith, P., Baron-Cohen, S., Lai, M., & Mandy, W. (2017). “Putting on My Best Normal”: Social Camouflaging in Adults with Autism Spectrum Conditions. Journal Of Autism And Developmental Disorders, 47(8), 2519-2534. doi: 10.1007/s10803-017-3166-5


Kreiser, N., & White, S. (2013). ASD in Females: Are We Overstating the Gender Difference in Diagnosis?. Clinical Child And Family Psychology Review, 17(1), 67-84. doi: 10.1007/s10567-013-0148-9


Kung, K. (2020). Autistic traits, systemising, empathising, and theory of mind in transgender and non-binary adults. Molecular Autism, 11(1). doi: 10.1186/s13229-020-00378-7


Lai, M., Lombardo, M., Ruigrok, A., Chakrabarti, B., Auyeung, B., & Szatmari, P. et al. (2016). Quantifying and exploring camouflaging in men and women with autism. Autism, 21(6), 690-702. doi: 10.1177/1362361316671012


Lai, M., Lombardo, M., Chakrabarti, B., Ruigrok, A., Bullmore, E., & Suckling, J. et al. (2018).Neural self-representation in autistic women and association with ‘compensatory camouflaging’. Autism, 23(5), 1210-1223. doi: 10.1177/1362361318807159


Lavie N. (2005). Distracted and confused?: Selective attention under load. Trends in Cognitive Sciences, 9, 75–82. doi:10.1016/j.tics.2004.12.004


Lemon, J, M., Garago, B., Entticott, P, G., & Rinehart, N, J. (2011). Brief Report: Executive Functioning in Autism Spectrum Disorders: A Gender Comparison of Response Inhibition, J Autism Dev Discord, 41: 352-356. DOI: 10.1007/s10803-010-1039-2 

Loomes, R., Hull, L., & Mandy, W. (2017). What Is the Male-to-Female Ratio in Autism Spectrum Disorder? A Systematic Review and Meta-Analysis. Journal Of The American Academy Of Child & Adolescent Psychiatry, 56(6), 466-474. doi: 10.1016/j.jaac.2017.03.013


Lord, C., Risi, S., Lambrecht, L., Cook, Jr., E., Leventhal, B., & DiLavore, P. et al. (2000). Journal Of Autism And Developmental Disorders, 30(3), 205-223. doi:10.1023/a:1005592401947


Milner, V., McIntosh, H., Colvert, E., & Happé, F. (2019). A Qualitative Exploration of the Female Experience of Autism Spectrum Disorder (ASD). Journal Of Autism And Developmental Disorders, 49(6), 2389-2402. doi: 10.1007/s10803-019-03906-4

Miyake, A., Friedman, N., Emerson, M., Witzki, A., Howerter, A., & Wager, T. (2000). The  Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis. Cognitive Psychology, 41(1), 49-100. doi: 10.1006/cogp.1999.0734


Mottron et al. (2006) Mottron L, Dawson M, Soulières I, Hubert B, Burack J. Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders. 2006;36(1):27–43. doi: 10.1007/s10803-005-0040-7


Pearson, A., & Rose, K. (2021). A Conceptual Analysis of Autistic Masking: Understanding the Narrative of Stigma and the Illusion of Choice. Autism In Adulthood, 3(1), 52-60. doi: 10.1089/aut.2020.0043


Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a “theory of mind”?  Behavioural and Brain Sciences, 4, 515-526.


Remington, A., Swettenham, J., & Lavie, N. (2012). Lightening the load: Perceptual load impairs visual detection in typical adults but not in autism. Journal Of Abnormal Psychology, 121(2), 544-551. doi: 10.1037/a0027670

Ratto, A., Kenworthy, L., Yerys, B., Bascom, J., Wieckowski, A., & White, S. et al. (2017). What About the Girls? Sex-Based Differences in Autistic Traits and Adaptive Skills.     Journal Of Autism And Developmental Disorders, 48(5), 1698-1711. doi: 10.1007/s10803-017-3413-9

Robinson EB, Lichtenstein P, Anckarsater H, Happé F, Ronald A. (2013). Examining and interpreting the female protective effect against autistic behavior. Proceedings of the National Academy of Sciences, 110(13): 5258–5262.                                                          https://doi.org/10.1073/pnas.1211070110

Sandson, J., & Albert, M, L. (1984). Varieties of Preservation. Neuropsychologia 22, 715-732. 

Schuck, R., Flores, R., & Fung, L. (2019). Brief Report: Sex/Gender Differences in Symptomology and Camouflaging in Adults with Autism Spectrum Disorder. Journal   Of Autism And Developmental Disorders, 49(6), 2597-2604. doi: 10.1007/s10803-019-03998-y


South, M., Ozonoff, S., & Mcmahon, W. (2007). The relationship between executive functioning, central coherence, and repetitive behaviors in the high-functioning autism spectrum. Autism, 11(5), 437-451. doi: 10.1177/1362361307079606


Tiimo. (2019). The Art of Masking: Autistic Women who Mask [Image]. Retrieved from https://www.tiimoapp.com/blog/art-of-masking-women-with-autism/


Tomchek, S., & Dunn, W. (2007). Sensory Processing in Children With and Without Autism: A Comparative Study Using the Short Sensory Profile. American Journal Of Occupational Therapy, 61(2), 190-200. doi: 10.5014/ajot.61.2.190 

Turner, S., Beidel, D., Dancu, C., & Stanley, M. (1989). An empirically derived inventory to measure social fears and anxiety: The Social Phobia and Anxiety Inventory. Psychological Assessment: A Journal Of Consulting And Clinical Psychology, 1(1), 35-40. doi: 10.1037/1040-3590.1.1.35


Van der Meisen, A., Hurley, H., Bal, A, M., & de Vries, A, L, C. (2018). Prevalence of the Wish to be of the Opposite Gender in Adolescents and Adults with Autism Spectrum Disorder. Arch Sex Behav, 47(8): 2307-2317. DOI: 10.1007/s10508-018-1218-3

Willey LH. (2014). Pretending to Be Normal: Living with Asperger’s Syndrome (Autism Spectrum Disorder) Expanded Edition. Jessica Kingsley Publishers.

The impact of motivated reasoning on (un)sustainable food decisions and sketching new pathways for effective

— Literature Thesis

Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2007). The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. Journal of Environmental Psychology, 27(4),

265-276. https://doi.org/10.1016/j.jenvp.2007.08.002

Ang, C.-S., Chan, N.-N., & Singh, L. (2019). A comparison study of meat eaters and nonmeat

eaters on mind attribution and moral disengagement of animals. Appetite, 136 80-

  1. https://doi.org/10.1016/j.appet.2019.01.019

Baekgaard, M., Christensen, J., Dahlmann, C. M., Mathiasen, A., & Petersen, N. B. G.

(2019). The role of evidence in politics: Motivated reasoning and persuasion among

politicians. British Journal of Political Science, 49(3), 1117-1140.


Bandura, A. (1990). Selective activation and disengagement of moral control. Journal of

Social Issues, 46(1), 27-46. https://doi.org/10.1111/j.1540-4560.1990.tb00270.x

Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and

Human Decision Processes, 50(2), 248-287.


Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (1996). Mechanisms of moral

disengagement in the exercise of moral agency. Journal of Personality and Social

Psychology, 71(2), 364-374. https://doi.org/10.1037/0022-3514.71.2.364

Bandura, A. (1999). Moral disengagement in the perpetration of inhumanities. Personality

and Social Psychology Review, 3(3), 193-209.


Bastian, B., Loughnan, S., Haslam, N., & Radke, H. R. M. (2012). Don’t mind meat? The

denial of mind to animals used for human consumption. Personality and Social

Psychology Bulletin, 38(2), 247-256. https://doi.org/10.1177/0146167211424291

Bustamante, A., & Chaux, E. (2014). Reducing moral disengagement mechanisms: A

comparison of two interventions. Journal of Latino/Latin American Studies, 6(1), 52-54.


Campbell-Arvai, V., Arvai, J., & Kalof, L. (2014). Motivating sustainable food choices: The

role of nudges, value orientation, and information provision. Environment and Behavior,

46(4), 453-475. https://doi.org/10.1177/0013916512469099

Carrigan, M., & Attalla, A. (2001). The myth of the ethical consumer – do ethics matter in

purchase behaviour? Journal of Consumer Marketing, 18(7), 560-578.


Cialdini, R. B. (2003). Crafting normative messages to protect the environment. Current

Directions in Psychological Science, 12(4), 105-109. https://doi.org/10.1111/1467-


Cialdini, R. B., Demaine, L. J., Sagarin, B. J., Barrett, D. W., Rhoads, K., & Winter, P. L.

(2006). Managing social norms for persuasive impact. Social influence, 1(1), 3-15.


Cialdini, R. B., & Trost, M. R. (1998). Social influence: Social norms, conformity, and

compliance. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social

psychology (4th ed., Vol. 2, pp. 151–192). Boston: McGraw-Hill.

Clonan, A., Wilson, P., Swift, J. A., Leibovici, D. G., & Holdsworth, M. (2015). Red and

processed meat consumption and purchasing behaviours and attitudes: Impacts for

human health, animal welfare and environmental sustainability. Public Health Nutrition,

18 (13), 2446-2456. https://doi.org/10.1017/s1368980015000567

De Bakker, E., & Dagevos, H. (2012). Reducing meat consumption in today’s consumer

society: Questioning the citizen-consumer gap. Journal of Agricultural and

Environmental Ethics, 25(6), 877-894. https://doi.org/10.1007/s10806-011-9345-z

Demarque, C., Charalambides, L., Hilton, D. J., & Waroquier, L. (2015). Nudging

sustainable consumption: The use of descriptive norms to promote a minority behavior in

a realistic online shopping environment. Journal of Environmental Psychology, 43, 166-

  1. https://doi.org/10.1016/j.jenvp.2015.06.008

Detert, J. R., Trevi.o, L. K., & Sweitzer, V. L. (2008). Moral disengagement in ethical

decision making: A study of antecedents and outcomes. Journal of Applied Psychology,

93(2), 374-391. https://doi.org/10.1037/0021-9010.93.2.374

Diaconeasa, M. C., Popescu, G., & Boboc, D. (2019). Sustainable Food Consumption in the

Web of Science Abstracts. Economic Computation and Economic Cybernetics Studies

and Research, 53(1), 299-307. https://doi.org/10.24818/18423264/

Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011). Partitioning default effects:

Why people choose not to choose. Journal of Experimental Psychology: Applied, 17(4),

332–341. https://doi.org/10.1037/a0024354

Ditto, P. H., Pizarro, D. A., & Tannenbaum, D. (2009). Motivated moral reasoning. In B. H.

Ross (Series Ed.) & D. M. Bartels, C. W. Bauman, L. J. Skitka, & D. L. Medin

(Eds.), Psychology of learning and motivation: Moral judgment and decision making

(Vol. 50, pp. 307-338). San Diego, CA: Academic Press. https://doi.org/10.1016/S0079-


Dowsett, E., Semmler, C., Bray, H., Ankeny, R. A., & Chur-Hansen, A. (2018). Neutralising

the meat paradox: Cognitive dissonance, gender, and eating animals. Appetite, 123, 280-

  1. https://doi.org/10.1016/j.appet.2018.01.005

Enax, L., Krajbich, I., & Weber, B. (2016). Salient nutrition labels increase the integration of

health attributes in food decision-making. Judgment and Decision making, 11(5), 460-

  1. Retrieved from http://journal.sjdm.org/16/16620/jdm16620.pdf

Enax, L., Krapp, V., Piehl, A., & Weber, B. (2015). Effects of social sustainability signalling

on neural valuation signals and taste-experience of food products. Frontiers in

Behavioral Neuroscience, 9, 247. https://doi.org/10.3389/fnbeh.2015.00247

Epley, N., & Gilovich, T. (2016). The mechanics of motivated reasoning. Journal of

Economic Perspectives, 30(3), 133-140. https://doi.org/10.1257/jep.30.3.133

Festinger, L. (1957). A theory of cognitive dissonance (Vol. 2). Stanford university press.

Gilovich, T., & Ross, L. (2016). The wisest one in the room: How you can benefit from social

psychology’s most powerful insights. New York, NY: Free Press.

Gra.a, J., Calheiros, M. M., & Oliveira, A. (2014). Moral disengagement in harmful but

cherished food practices? An exploration into the case of meat. Journal of Agricultural

and Environmental Ethics, 27(5), 749-765. https://doi.org/10.1007/s10806-014-9488-9

Gra.a, J., Calheiros, M. M., & Oliveira, A. (2015). Attached to meat? (Un)Willingness and

intentions to adopt a more plant-based diet. Appetite, 95, 113-125.


Gra.a, J., Calheiros, M. M., & Oliveira, A. (2016). Situating moral disengagement:

Motivated reasoning in meat consumption and substitution. Personality and Individual

Differences, 90, 353-364. https://doi.org/10.1016/j.paid.2015.11.042

Gra.a, J., Oliveira, A., & Calheiros, M. M. (2015). Meat, beyond the plate. Data-driven

hypotheses for understanding consumer willingness to adopt a more plant-based diet.

Appetite, 90, 80-90. https://doi.org/10.1016/j.appet.2015.02.037

Hanss, D., & B.hm, G. (2010). Can I make a difference? The role of general and domainspecific

self-efficacy in sustainable consumption decisions. Umweltpsychologie, 14(2),

46-74. Retrieved from http://hdl.handle.net/1956/6238

Hanss, D., & B.hm, G. (2013). Promoting purchases of sustainable groceries: An

intervention study. Journal of Environmental Psychology, 33, 53-67.


Harmon‐Jones, E., Amodio, D. M., & Harmon‐Jones, C. (2009). Action‐based model of

dissonance: A review, integration, and expansion of conceptions of cognitive conflict. In

  1. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 41, pp. 119-166).

Burlington: Academic Press. https://doi.org/10.1016/S0065-2601(08)00403-6

Harmon-Jones, E., & Harmon-Jones, C. (2002). Testing the action-based model of cognitive

dissonance: The effect of action orientation on postdecisional attitudes. Personality and

Social Psychology Bulletin, 28(6), 711-723. https://doi.org/10.1177/0146167202289001

Hart, P. S., & Nisbet, E. C. (2012). Boomerang effects in science communication: How

motivated reasoning and identity cues amplify opinion polarization about climate

mitigation policies. Communication Research, 39(6), 701–723.


Hedin, B., Katzeff, C., Eriksson, E., & Pargman, D. (2019). A systematic review of digital

behaviour change interventions for more sustainable food consumption. Sustainability,

11(9), 2638. https://doi.org/10.3390/su11092638

Kahan, D. M. (2013). Ideology, motivated reasoning, and cognitive reflection: An

experimental study. Judgment and Decision making, 8(4), 407-424.


Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk.

Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185

Kitayama, S., Chua, H. F., Tompson, S., & Han, S. (2013). Neural mechanisms of

dissonance: An fMRI investigation of choice justification. NeuroImage, 69, 206-212.


K.bberling, V., & Wakker, P. P. (2005). An index of loss aversion. Journal of Economic

Theory, 122(1), 119-131. https://doi.org/10.1016/j.jet.2004.03.009

K.ster, E. P. (2009). Diversity in the determinants of food choice: A psychological

perspective. Food Quality and Preference, 20(2), 70-82.


Kumar, B., Manrai, A. K., & Manrai, L. A. (2017). Purchasing behaviour for

environmentally sustainable products: A conceptual framework and empirical study.

Journal of Retailing and Consumer Services, 34, 1-9.


Kunda, Z. (1990). The case for motivated reasoning. Psychological bulletin, 108(3), 480-498.


Lally, P., & Gardner, B. (2013). Promoting habit formation. Health Psychology Review,

7(sup1), S137-S158. https://doi.org/10.1080/17437199.2011.603640

Linder, N. S., Uhl, G., Fliessbach, K., Trautner, P., Elger, C. E., & Weber, B. (2010). Organic

labeling influences food valuation and choice. NeuroImage, 53(1), 215-220.


Loughnan, S., Haslam, N., & Bastian, B. (2010). The role of meat consumption in the denial

of moral status and mind to meat animals. Appetite, 55(1), 156-159.


Meulenberg, M. T. G. (2003). ‘Consument en burger’, betekenis voor de markt van

landbouwproducten en voedingsmiddelen. Tijdschrift voor sociaalwetenschappelijk

onderzoek van de landbouw, 18(1), 43-54. Retrieved from


Nemecek, T., Jungbluth, N., i Canals, L. M., & Schenck, R. (2016). Environmental impacts

of food consumption and nutrition: Where are we and what is next?. The International

Journal of Life Cycle Assessment, 21(5), 607-620. https://doi.org/10.1007/s11367-016-


O’Connor, E. L., Sims, L., & White, K. M. (2017). Ethical food choices: Examining people’s

Fair Trade purchasing decisions. Food Quality and Preference, 60, 105-112.


Ong, A. S. J., Frewer, L. J., & Chan, M. -Y. (2017). Cognitive dissonance in food and

nutrition – A conceptual framework. Trends in Food Science & Technology, 59, 60-69.


Pronin, E., Gilovich, T., & Ross, L. (2004). Objectivity in the eye of the beholder: Divergent

perceptions of bias in self versus others. Psychological review, 111(3), 781-799


Ritchie, H. & Roser, M. (2020, January 15). Environmental impacts of food production. Our

World in Data. Retrieved from https://ourworldindata.org/environmental-impacts-offood

[Online Resource]

Robinson, R., & Smith, C. (2002). Psychosocial and demographic variables associated with

consumer intention to purchase sustainably produced foods as defined by the Midwest

Food Alliance. Journal of nutrition education and behavior, 34(6), 316-325.


Rothgerber, H. (2014). Efforts to overcome vegetarian-induced dissonance among meat

eaters. Appetite, 79, 32-41. https://doi.org/10.1016/j.appet.2014.04.003

Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2007). The

constructive, destructive, and reconstructive power of social norms. Psychological

Science, 18(5), 429-434. https://doi.org/10.1111/j.1467-9280.2007.01917.x

Smith, N. C., Goldstein, D. G., & Johnson, E. J. (2013). Choice without awareness: Ethical

and policy implications of defaults. Journal of Public Policy & Marketing, 32(2), 159–

  1. https://doi.org/10.1509/jppm.10.114

Spaargaren, G., van Koppen, C. S. A. K., Janssen, A. M., Hendriksen, A., & Kolfschoten, C.

  1. (2013). Consumer responses to the carbon labelling of food: A real life experiment in a

canteen practice. Sociologia Ruralis, 53(4), 432-453. https://doi.org/10.1111/soru.12009

Staats, H., van Leeuwen, E., & Wit, A. (2000). A longitudinal study of informational

interventions to save energy in an office building. Journal of Applied Behavior Analysis,

33(1), 101-104. https://doi.org/10.1901/jaba.2000.33-101

Steg, L., & Vlek, C. (2009). Encouraging pro-environmental behaviour: An integrative

review and research agenda. Journal of Environmental Psychology, 29(3), 309-317.


St.ckli, S., Dorn, M., & Liechti, S. (2018). Normative prompts reduce consumer food waste

in restaurants. Waste Management, 77, 532-536.


Sunstein, C. R. (2014). Nudging: A very short guide. Journal of Consumer Policy, 37(4),

583-588. https://doi.org/10.1007/s10603-014-9273-1

Symmank, C., Mai, R., Hoffmann, S., Stok, F. M., Renner, B., Lien, N., & Rohm, H. (2017).

Predictors of food decision making: A systematic interdisciplinary mapping (SIM)

review. Appetite, 110, 25–35. https://doi.org/10.1016/j.appet.2016.11.023

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth,

and happiness. Yale University Press.

The World Bank (2003). World Development Report 2003: Sustainable development in a

dynamic world – transforming institutions, growth and quality of life, New York: Oxford

University Press for the World Bank.

Th.gersen, J. (2010). Country differences in sustainable consumption: The case of organic

food. Journal of Macromarketing, 30(2), 171–185.


Tsang, J.-A. (2002). Moral rationalization and the integration of situational factors and

psychological processes in immoral behavior. Review of General Psychology, 6(1), 25-

  1. https://doi.org/10.1037/1089-2680.6.1.25

Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A referencedependent

model. The Quarterly Journal of Economics, 106(4), 1039-1061.


Van Kleef, E., Seijdell, K., Vingerhoeds, M. H., de Wijk, R. A., & van Trijp, H. C. M. (2018).

The effect of a default-based nudge on the choice of whole wheat bread. Appetite, 121,

179-185. https://doi.org/10.1016/j.appet.2017.11.091

Van Strien, T., & Koenders, P. G. (2012). How do life style factors relate to general health

and overweight? Appetite, 58(1), 265-270. https://doi.org/10.1016/j.appet.2011.10.001

Verain, M. C. D., Bartels, J., Dagevos, H., Sijtsema, S. J., Onwezen, M. C., & Antonides, G.

(2012). Segments of sustainable food consumers: A literature review. International

Journal of Consumer Studies, 36(2), 123-132. https://doi.org/10.1111/j.1470-


Vermeir, I., & Verbeke, W. (2006). Sustainable food consumption: Exploring the consumer

“attitude–behavioral intention” gap. Journal of Agricultural and Environmental Ethics,

19(2), 169-194. https://doi.org/10.1007/s10806-005-5485-3

Vermeir, I., & Verbeke, W. (2008). Sustainable food consumption among young adults in

Belgium: Theory of planned behaviour and the role of confidence and values. Ecological

economics, 64(3), 542-553. https://doi.org/10.1016/j.ecolecon.2007.03.007

Verplanken, B., & Roy, D. (2015). 15. Consumer habits and sustainable consumption. In L.

Reisch & J. Thogersen (Eds.) Handbook of research on sustainable consumption (pp.

243-253). Cheltenham, UK: Edward Elgar Publishing Ltd.

Verplanken, B., & Roy, D. (2016). Empowering interventions to promote sustainable

lifestyles: Testing the habit discontinuity hypothesis in a field experiment. Journal of

Environmental Psychology, 45, 127-134. https://doi.org/10.1016/j.jenvp.2015.11.008

Vinnari, M., & Vinnari, E. (2014). A framework for sustainability transition: The case of

plant-based diets. Journal of agricultural and environmental ethics, 27(3), 369-396.


WCED (World Commission on Environment and Development) (1987). Our Common

Future, Brundtland Report, Oxford: Oxford University Press.

Weatherell, C., Tregear, A., & Allinson, J. (2003). In search of the concerned consumer: UK

public perceptions of food, farming and buying local. Journal of Rural Studies, 19(2),

233-244. https://doi.org/10.1016/s0743-0167(02)00083-9

Westen, D., Blagov, P. S., Harenski, K., Kilts, C., & Hamann, S. (2006). Neural bases of

motivated reasoning: An fMRI study of emotional constraints on partisan political

judgment in the 2004 US presidential election. Journal of Cognitive Neuroscience,

18(11), 1947-1958. https://doi.org/10.1162/jocn.2006.18.11.1947

Wilkinson, T. M. (2013). Nudging and manipulation. Political Studies, 61(2), 341-355.


Appendix A

Details of Graca et al. (2014), discussed in 2.2.2 Moral disengagement and loss aversion in sustainable food decision making.

During these group interviews, participants discussed the impacts of meat production and consumption, and the possibility of changing behaviour (Graca et al., 2014). Furthermore, using moral disengagement was expected to minimise the willingness to consider a change of habits (Graca et al., 2014).

Appendix B

Details of Verplanken and Roy (2016), discussed in 3.1.1 Behaviour change interventions.

After controlling for past behaviour, habit strength, personal norms, and intentions, the intervention promoting sustainable behaviours was more effective among the group of participants that recently relocated (Verplanken & Roy, 2016). Probably, due to old habits that were disturbed, participants became more sensitive to new information when recently relocated (Verplanken & Roy, 2016).

Appendix C

Details of Hanss and Bohm (2013), discussed in 3.1.2 Informational interventions.

The intervention consisted of four steps: the first step increased awareness of environmental and socio-economic problems; the second taught participants about human actions as the leading causes for problems; the third was aiming to strengthen self-efficacy concerning contributing to sustainable development directly; and the final part focused on strengthening self-efficacy with regard to indirectly contributing to sustainable development (Hanss & Bohm, 2013).

Appendix D

Details of Demarque et al. (2015), discussed in Use of social norms.

An example of a weak descriptive norm used is: “For your information, 9% of previous participants purchased one ecological product’. A strong descriptive norm was either: “For your information, 70% of previous participants purchased at least one ecological product” or “For your information, on average, previous participants purchased at least two ecological products.” (Demarque et al., 2015).

Appendix E

Details of Campbell-Arvai et al. (2014), discussed in Increase ease and convenience.

Four different menus were shown to participants: 1) a default menu presenting only appealing or unappealing meat-free meal options, 2) a default+information menu containing additional information about the effect of reducing eating meat on environmental impact, 3) an information menu, 4) or a more conventional menu presenting both meat-free and nonvegetarian meals (Campbell-Arvai et al., 2014).

Disparities of People of Color in Psychedelic Medicine

— Original Piece

Carhart-Harris, R. L., Bolstridge, M., Day, C. M. J., Rucker, J., Watts, R., Erritzoe, D. E., … Nutt, D. J. (2018). Psilocybin with psychological support for treatment-resistant depression: Six-month follow-up. Psychopharmacology, 235(2), 399-408.

Dos Santos, R. G., Bouso, J. C., & Hallak, J. E. (2019). Serotonergic hallucinogens/psychedelics could be promising treatments for depressive and anxiety disorders in end-stage cancer. BMC Psychiatry, 19(1), 1-4.

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). Most people are not WEIRD. Nature, 466(7302), 29-29.

Krediet, E., Bostoen, T., Breeksema, J., van Schagen, A., Passie, T., & Vermetten, E. (2020). Reviewing the potential of psychedelics for the treatment of PTSD. International Journal of Neuropsychopharmacology, 23(6), 385-400.

Michaels, T. I., Purdon, J., Collins, A., & Williams, M. T. (2018). Inclusion of people of color in psychedelic-assisted psychotherapy: A review of the literature. BMC Psychiatry, 18(1), 1-14.

Tófoli, L. F., & de Araujo, D. B. (2016). Treating addiction: Perspectives from EEG and imaging studies on psychedelics. International Review of Neurobiology, 129, 157-185.

Warner, J. (2021, May 1). Psychiatry Confronts Its Racist Past, and Tries to Make Amends. The New York Times. https://www.nytimes.com/2021/04/30/health/psychiatry-racism-black-americans.html

Williams, M. T., Malcoun, E., & Nouri, L. B. (2015). Assessment of posttraumatic stress disorder with African Americans. In Guide to psychological assessment with African Americans (pp. 163-182). Springer, New York, NY.

Exogenous hormones in the pill may modulate gray matter volumes in the brain

— Research Project

Amat, J. A., Bansal, R., Whiteman, R., Haggerty, R., Royal, J., & Peterson, B. S. (2008). Correlates of intellectual ability with morphology of the hippocampus and amygdala in healthy adults. Brain and Cognition, 66(2), 105–114. https://doi.org/10.1016/j.bandc.2007.05.009


Barth, C., Steele, C. J., Mueller, K., Rekkas, V. P., Arélin, K., Pampel, A., Burmann, I., Kratzsch, J., Villringer, A., & Sacher, J. (2016). In-vivo Dynamics of the Human Hippocampus across the Menstrual Cycle. Scientific Reports, 6(1), 32833. https://doi.org/10.1038/srep32833


Bezemer, I. D., Verhamme, K. M. C., Gini, R., Mosseveld, M., Rijnbeek, P. R., Trifirò, G., Sturkenboom, M. C. J. M., Beest, F. J. A. P., & Herings, R. M.

  1. (2016). Use of oral contraceptives in three European countries: A population-based multi-database study. The European Journal of Contraception & Reproductive Health Care, 21(1), 81–87. https://doi.org/10.3109/13625187.2015.1102220


Boron, W. F., & Boulpaep, E. L. (2016). Medical Physiology. Elsevier Health Sciences.


Brinton, R. D., Thompson, R. F., Foy, M. R., Baudry, M., Wang, J., Finch, C. E., Morgan, T. E., Pike, C. J., Mack, W. J., Stanczyk, F. Z., & Nilsen, J. (2008). Progesterone receptors: Form and function in brain. Frontiers in Neuroendocrinology, 29(2), 313–339. https://doi.org/10.1016/j.yfrne.2008.02.001


Buckner, R. L., Head, D., Parker, J., Fotenos, A. F., Marcus, D., Morris, J. C., & Snyder, A. Z. (2004). A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. NeuroImage, 23(2), 724–738. https://doi.org/10.1016/j.neuroimage.2004.06.018


Corrigan, J. D., & Hinkeldey, N. S. (1987). Relationships between Parts A and B of the Trail Making Test. Journal of Clinical Psychology, 43(4), 402–409. https://doi.org/10.1002/1097-4679(198707)43:4<402::AID-JCLP2270430411>3.0.CO;2-E


De Bondt, T., Jacquemyn, Y., Van Hecke, W., Sijbers, J., Sunaert, S., & Parizel, P. M. (2013). Regional gray matter volume differences and sex-hormone correlations as a function of menstrual cycle phase and hormonal contraceptives use. Brain Research, 1530, 22–31. https://doi.org/10.1016/j.brainres.2013.07.034


Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage,31(3), 968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021


Edwards, D. A., Whalen, R. E., & Nadler, R. D. (1968). Induction of estrus: Estrogen-progesterone interactions. Physiology & Behavior, 3(1), 29–33. https://doi.org/10.1016/0031-9384(68)90027-9


Ertman, N., Andreano, J. M., & Cahill, L. (2011). Progesterone at encoding predicts subsequent emotional memory. Learning & Memory, 18(12), 759–763. https://doi.org/10.1101/lm.023267.111


Fanselow, M. S., & Dong, H.-W. (2010). Are the Dorsal and Ventral Hippocampus Functionally Distinct Structures? Neuron, 65(1), 7–19. https://doi.org/10.1016/j.neuron.2009.11.031


Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A.,

Makris, N., Rosen, B., & Dale, A. M. (2002). Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain. Neuron, 33(3), 341–355. https://doi.org/10.1016/S0896-6273(02)00569-X


Ge, Y., Grossman, R. I., Babb, J. S., Rabin, M. L., Mannon, L. J., & Kolson, D. L. (2002). Age-Related Total Gray Matter and White Matter Changes in Normal Adult Brain. Part I: Volumetric MR Imaging Analysis. American Journal of Neuroradiology, 23(8), 1327–1333.


Gingnell, M., Engman, J., Frick, A., Moby, L., Wikström, J., Fredrikson, M., & Sundström-Poromaa, I. (2013). Oral contraceptive use changes brain activity and mood in women with previous negative affect on the pill—A double-blinded, placebo-controlled randomized trial of a levonorgestrel-containing combined oral contraceptive. Psychoneuroendocrinology, 38(7), 1133–1144. https://doi.org/10.1016/j.psyneuen.2012.11.006


Giovagnoli, A. R., Mascheroni, S., Simoncelli, M., Laiacona, M., & Capitani, E. (1996). Trail Making Test: Normative values from287 normal adult controls. Italian Journal of Neurological Sciences, 17, 305–309. https://doi.org/10.1007/BF01997792


Gogos, A., Wu, Y. C., Williams, A. S., & Byrne, L. K. (2014). The Effects of Ethinylestradiol and Progestins (“the pill”) on Cognitive Function in Pre-menopausal Women. Neurochemical Research, 39(12), 2288–2300. https://doi.org/10.1007/s11064-12014-1444-6


Goldin, C., & Katz, L. F. (2002). The Power of the Pill: Oral Contraceptives and Women’s Career and Marriage Decisions. Journal of Political Economy, 110(4), 730–770. https://doi.org/10.1086/340778


Goldstein, J. M. (2005). Hormonal Cycle Modulates Arousal Circuitry in Women Using Functional Magnetic Resonance Imaging. Journal of Neuroscience, 25(40), 9309–9316. https://doi.org/10.1523/JNEUROSCI.2239-05.2005


Hertel, J., König, J., Homuth, G., Van der Auwera, S., Wittfeld, K., Pietzner, M., Kacprowski, T., Pfeiffer, L., Kretschmer, A., Waldenberger, M., Kastenmüller, G., Artati, A., Suhre, K., Adamski, J., Langner, S., Völker, U., Völzke, H., Nauck, M., Friedrich, N., & Grabe, H. J. (2017). Evidence for Stress-like Alterations in the HPA-Axis in Women Taking Oral Contraceptives. Scientific Reports, 7(1), 14111. https://doi.org/10.1038/s41598-017-13927-7


LeDoux, J. E. (1993). Emotional memory systems in the brain. Behavioural Brain Research, 58(1), 69–79. https://doi.org/10.1016/0166-4328(93)90091-4


Lisofsky, N., Mårtensson, J., Eckert, A., Lindenberger, U., Gallinat, J., & Kühn, S. (2015). Hippocampal volume and functional connectivity changes during the female menstrual cycle. NeuroImage, 118, 154–162. https://doi.org/10.1016/j.neuroimage.2015.06.012


Lisofsky, N., Riediger, M., Gallinat, J., Lindenberger, U., & Kühn, S. (2016). Hormonal contraceptive use is associated with neural and affective changes in healthy young women. NeuroImage, 134, 597–606. https://doi.org/10.1016/j.neuroimage.2016.04.042


McEwen, B. (2002). Estrogen actions throughout the brain. Recent progress in hormone research, 57, 357-384.


Montoya, E. R., & Bos, P. A. (2017). How Oral Contraceptives Impact Social-Emotional Behavior and Brain Function. Trends in Cognitive Sciences, 21(2), 125–136. https://doi.org/10.1016/j.tics.2016.11.005


Nielsen, S. E., Ertman, N., Lakhani, Y. S., & Cahill, L. (2011). Hormonal contraception usage is associated with altered memory for an emotional story. Neurobiology of Learning and Memory, 96(2), 378–384. https://doi.org/10.1016/j.nlm.2011.06.013


O’Brien, K. R., Kober, T., Hagmann, P., Maeder, P., Marques, J., Lazeyras, F., Krueger, G., & Roche, A. (2014). Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE. PLOS ONE, 9(6), e99676. https://doi.org/10.1371/journal.pone.0099676


Ossewaarde, L., Wingen, G. A. van, Rijpkema, M., Bäckström, T., Hermans, E. J., & Fernández, G. (2013). Menstrual cycle-related changes in amygdala morphology are associated with changes in stress sensitivity. Human Brain Mapping, 34(5), 1187–1193. https://doi.org/10.1002/hbm.21502


Österlund, M., G.J.M. Kuiper, G., Gustafsson, J.-Å., & Hurd, Y. L. (1998). Differential distribution and regulation of estrogen receptor-α _and -β _mRNA within the female rat brain1First published on the World Wide Web on 10 December 1997.1. Molecular Brain Research, 54(1), 175–180. https://doi.org/10.1016/S0169-328X(97)00351-3


Packard, M. G., & Teather, L. A. (1997). Intra-hippocampal estradiol infusion enhances memory in ovariectomized rats. NeuroReport, 8(14), 3009–3013.


Petersen, N., & Cahill, L. (2015). Amygdala reactivity to negative stimuli is influenced by oral contraceptive use. Social Cognitive and Affective Neuroscience, 10(9), 1266–1272. https://doi.org/10.1093/scan/nsv010


Petersen, N., Touroutoglou, A., Andreano, J. M., & Cahill, L. (2015). Oral contraceptive pill use is associated with localized decreases in cortical thickness. Human Brain Mapping, 36(7), 2644–2654. https://doi.org/10.1002/hbm.22797


Pletzer, B. (2019). Sex Hormones and Gender Role Relate to Gray Matter Volumes in Sexually Dimorphic Brain Areas. Frontiers in Neuroscience, 13, 592. https://doi.org/10.3389/fnins.2019.00592


Pletzer, B., Harris, T., & Hidalgo-Lopez, E. (2018). Subcortical structural changes along the menstrual cycle: Beyond the hippocampus. Scientific Reports, 8(1), 16042. https://doi.org/10.1038/s41598-018-34247-4


Pletzer, B., Harris, T., & Hidalgo-Lopez, E. (2019). Previous contraceptive treatment relates to grey matter volumes in the hippocampus and basal ganglia. Scientific Reports, 9(1), 11003. https://doi.org/10.1038/s41598-019-47446-4


Pletzer, B., Harris, T.-A., Scheuringer, A., & Hidalgo-Lopez, E. (2019). The cycling brain: Menstrual cycle related fluctuations in hippocampal and fronto-striatal activation and connectivity during cognitive tasks. Neuropsychopharmacology, 44(11), 1867–1875. https://doi.org/10.1038/s41386-019-0435-3


Pletzer, B., Kronbichler, M., Aichhorn, M., Bergmann, J., Ladurner, G., & Kerschbaum, H. H. (2010). Menstrual cycle and hormonal contraceptive use modulate human brain structure. Brain Research, 1348, 55–62. https://doi.org/10.1016/j.brainres.2010.06.019


Protopopescu, X., Butler, T., Pan, H., Root, J., Altemus, M., Polanecsky, M., McEwen, B., Silbersweig, D., & Stern, E. (2008). Hippocampal structural changes across the menstrual cycle. Hippocampus, 18(10), 985–988. https://doi.org/10.1002/hipo.20468


Rabe, T., Nitsche, D. C., & Runnebaum, B. (1997). The effects of monophasic and triphasic oral contraceptives on ovarian function and endometrial thickness. The European Journal of Contraception & Reproductive Health Care, 2(1), 39–51. https://doi.org/10.1080/13625189709049933


Salvagno, G. L., Danese, E., & Lippi, G. (2017). Preanalytical variables for liquid chromatography-mass spectrometry (LC-MS) analysis of human blood specimens. Clinical Biochemistry, 50(10), 582–586. https://doi.org/10.1016/j.clinbiochem.2017.04.012


Sander, D., Grafman, J., & Zalla, T. (2003). The human amygdala: an evolved system for relevance detection. Reviews in the Neurosciences, 14(4), 303-316.


Schmidt, K. H., and Metzler, P. (1992). Wortschatztest: WST. Weinheim: Beltz.


Sheline, Y. I., Mittler, B. L., & Mintun, M. A. (2002). The hippocampus and depression. European Psychiatry, 17, 300–305. https://doi.org/10.1016/S0924-9338(02)00655-7


Sitruk-Ware, R. (2006). New progestagens for contraceptive use. Human Reproduction Update, 12(2), 169–178. https://doi.org/10.1093/humupd/dmi046


Skovlund, C. W., Mørch, L. S., Kessing, L. V., & Lidegaard, Ø. (2016). Association of Hormonal Contraception With Depression. JAMA Psychiatry, 73(11), 1154–1162. https://doi.org/10.1001/jamapsychiatry.2016.2387


Stadel, B. V., Sternthal, P. M., Schlesselman, J. J., Douglas, M. B., Hall, W. D., Kaul, L., & Ahluwalia, B. (1980). Variation of ethinylestradiol blood levels among healthy women using oral contraceptives. Fertility and Sterility, 33(3), 257–260. https://doi.org/10.1016/s0015-0282(16)44589-9


Stricker, R., Eberhart, R., Chevailler, M.-C., Quinn, F. A., Bischof, P., & Stricker, R. (2006). Establishment of detailed reference values for luteinizing hormone, follicle stimulating hormone, estradiol, and progesterone during different phases of the menstrual cycle on the Abbott ARCHITECT® analyzer. Clinical Chemistry and Laboratory Medicine (CCLM), 44(7), 883–887. https://doi.org/10.1515/CCLM.2006.160

United Nations. (2019). Contraceptive Use by Method 2019: Data Booklet. UN. https://doi.org/10.18356/1bd58a10-en


van Wingen, G. A., Ossewaarde, L., Bäckström, T., Hermans, E. J., & Fernández, G. (2011). Gonadal hormone regulation of the emotion circuitry in humans. Neuroscience, 191, 38–45. https://doi.org/10.1016/j.neuroscience.2011.04.042 13



van Wingen, G. A., van Broekhoven, F., Verkes, R. J., Petersson, K. M., Bäckström, T., Buitelaar, J. K., & Fernández, G. (2008). Progesterone selectively increases amygdala reactivity in women. Molecular Psychiatry, 13(3), 325–333. https://doi.org/10.1038/sj.mp.4002030


Woolley, C. S., & McEwen, B. S. (1993). Roles of estradiol and progesterone in regulation of hippocampal dendritic spine density during the estrous cycle in the rat. Journal of Comparative Neurology, 336(2), 293–306. https://doi.org/10.1002/cne.903360210

You’re (Not) What They Think You Are The Sense and Nonsense of Personality Tests

— Original Piece

Abood, N. (2019). Big Five Traits: A Critical Review.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). American Psychiatric Pub.

Arnau, R., Green, B., Rosen, D., Gleaves, D., & Melancon, J. (2003). Are Jungian preferences really categorical? An empirical investigation using taxometrical analysis. Personality and Individual Differences, 34, 233–251.

Assessment days. (2009, April 15). The Guardian. Retrieved on 10/05/21 from: https://www.theguardian.com/careers/assessment-days.

Costa, P. T., & McCrae, R. R. (1985). The NEO Personality Inventory manual. Odessa, FL: Psychological Assessment Resources.

Costa, P. T., & McCrae, R. R. (1992). The five-factor model of personality and its relevance to personality disorders. Journal of Personality Disorders, 6(4), 343–359. DOI:10.1521/pedi.1992.6.4.343.

DeYoung, C. G. (2010). Personality neuroscience and the biology of traits. Social and Personality Psychology Compass, 4(12), 1165–1180.

Easterbrook, M. J., Kuppens, T., & Manstead, A. (2020). Socioeconomic status and the structure of the self-concept. The British journal of social psychology, 59(1), 66–86. DOI:10.1111/bjso.12334

Essig, T. (2014). The Mysterious Popularity of the Meaningless Myers-Briggs (MBTI). Forbes. Retrieved on 08/05/21 from: https://www.forbes.com/sites/toddessig/2014/09/29/the-mysterious-popularity-of-the-meaningless-myers-briggs-mbti/?sh=71fc821b1c79.

Farrukh, M., Wei Ying, C., & Abdallah Ahmed, N. O. (2016). Organizational commitment: Does religiosity matter? Cogent Business and Management, 3(1).

Furnham, A., & Schofield, S. (1987). Accepting personality test feedback: A review of the Barnum effect. Current Psychology (New Brunswick, N.J.), 6(2), 162–178. DOI:10.1007/BF02686623.

Furnham A. (2020). Myers-Briggs Type Indicator (MBTI). In: Zeigler-Hill V., Shackelford T.K. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. DOI:10.1007/978-3-319-24612-3_50.

Galton, F. (1884). Measurement of character. Fortnightly Review, 42, 179–185.

Gardner, W. L. & Martinko, M. J. (1996). Using the Myers-Briggs Type Indicator to Study Managers: A Literature Review and Research Agenda. Journal of Management, 22(1), 45-83.

Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4(1), 26–42.

Gregory, R. J. (2014). Psychological Testing: History, Principles, and Applications, Global Edition: Vol. Seventh edition, Global edition. Pearson.

Hathaway, S. R. (1965). Personality inventories. In B. B. Wolman (Ed.). Handbook of clinical psychology (pp. 451–476). New York: McGraw-Hill.

Jung, C. G. (1969). The archetypes and the collective unconscious. Princeton University Press.

Martin, W. (2014). The Problem with using Personality Tests for Hiring. Harvard Business review. Retrieved on 08/05/21 from: https://hbr.org/2014/08/the-problem-with-using-personality-tests-for-hiring.

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396. DOI:10.1037/h0054346.

McCrae, R., & Costa, P. (1988). Reinterpreting the Myers-Briggs type indicator from the perspective of the five-factor model of personality. Journal of Personality, 57, 17–40.

Micheal, J. (2003). Using the Myers-Briggs Type Indicator as a Tool for Leadership Development? Apply With Caution. Journal of Leadership and Organizational Studies, 10(1). DOI:10.1177/107179190301000106.

Mostert, N. M. (2007). Diversity of the mind as the key to successful creativity at Unilever. Creativity and Innovation Management, 16(1), 93-100. DOI:10.1111/j.1467-8691.2007.00422.x.

Morgan CD., Murray HA. (1935) A Method for Investigating Fantasies: The Thematic Apperception Test. Arch NeurPsych, 34(2):289-306. DOI:10.1001/archneurpsyc.1935.02250200049005.

Müller, S. & Moshagen, M. (2019). Controlling for Response Bias in Self-Ratings of Personality: A Comparison of Impression Management Scales and the Overclaiming Technique. Journal of Personality Assessment, 101(3), 229-236. DOI:10.1080/00223891.2018.1451870.

Myers, I., & McCaulley, M. (1985). Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator. Palo Alto, CA: Consulting Psychologists.

Othman, A. K., Hamzah, M. I., & Hashim, N.( 2014). Conceptualizing the Islamic personality

model. Procedia: Social and Behavioral Sciences, 130, 114–119.

Querk, N. (2000). Essentials of Myers-Briggs type indicator assessment. New York: Wiley.

Roberge, M.E. & van Dick, R. (2010). Recognizing the benefits of diversity: When and how does diversity increase group performance? Human Resource Management Review, 10(4), 295-308. DOI:10.1016/j.hrmr.2009.09.002

Rubenzer, S. J., Faschingbauer, T. R., & Ones, D. S. (2000). Assessing the U.S. Presidents Using the Revised NEO Personality Inventory. Assessment (Odessa, Fla.), 7(4), 403–419. DOI:10.1177/107319110000700408.

Rorschach, H., Morgenthaler, W., Lemkau, P., & Oberholzer, E. (1942). Psychodiagnostics : a diagnostic test based on perception : including Rorschach’s paper The application of the form interpretation test (published posthumously by Emil Oberholzer) (2nd ed., rev. and enl). Hans Huber.

Saggino, A., & Kline, P. (1996). The location of the Myers-Briggs type indicator in personality factor space. Personality and Individual Differences, 63, 445–450.

Sandal, Musson, Helmreich & Gravdal. (2005). Social desirability bias in personality testing: Implications for astronaut selection. Acta Astronautica, 57, 634-641. DOI:10.1016/j.actaastro.2005.03.011.

Schiele, B. C.; Baker, A. B.; Hathaway, S. R. (1943). The Minnesota multiphasic personality inventory. Journal-Lancet (63): 292–297.

Woodworth, R. S. (1920). Personal data sheet. Chicago: Stoelting.

Issue 11

At the Intersection of Art and Neuroscience 

— Original Piece

Dikker, S., Montgomery, S., & Tunca, S. (2019). Using Synchrony-Based Neurofeedback in Search of Human Connectedness. Brain Art, 161–206. doi:10.1007/978-3-030-14323-7_6

Dikker, Suzanne; Michalareas, Georgios; Oostrik, Matthias; Serafimaki, Amalia; Kahraman, Hasibe Melda; Struiksma, Marijn E.; Poeppel, David (2020). Crowdsourcing neuroscience: inter-brain coupling during face-to-face interactions outside the laboratory. NeuroImage, (), 117436–.doi:10.1016/j.neuroimage.2020.117436






Use of prosody to mark information structure in autistic female and male adults with high-level language ability. 

— Research Article

Attwood, T. (2007). The complete guide to Asperger’s syndrome. London, UK: Jessica Kingsley Publishers.

Baron-Cohen, S. (2002) The extreme male brain theory of autism. Trends Cogn Sci 6: 248–254.

Baron-Cohen, S., & Wheelwright, S. (2004). The empathy quotient: An investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. J Autism Dev Discord, 34. 163-175.

Boersma, P., & Weenink, D. (2009). Praat: Doing Phonetics by Computer [Computer Program]. Version 5.1.07. Available at: http://www.praat.org/

Chen, A. (2009). “The phonetics of sentence-initial topic and focus in adult and child Dutch,” in Phonetics and Phonology: Interactions and Interrelations, eds M. Vigário, S. Frota, and M. J. Freitas (Amsterdam: Benjamins), 91–106.

Chen, A. (2011). Tuning information packaging: Intonational realization of topic and focus in child Dutch. Journal of Child Language, 38, 1055–1083.

DePape, A. M., Chen, A., Hall, G. B., & Trainor, L. J. (2012). Use of prosody and information structure in high functioning adults with autism in relation to language ability. Frontiers in psychology, 3, 72.

Diehl, J. J., Bennetto, L., Watson, D., Gunlogson, C., & McDonough, J. (2008). Resolving ambiguity: A psycholinguistic approach to understanding prosody processing in high-functioning autism. Brain and Language, 106, 144–152.

Doherty, R., Orimoto, W., Singelis, L., Theodore, M., Hatfield, E., & Hebb, J. (1995). Emotional contagion: gender and occupational differences. Psychology of Women Quarterly, 19, 355371.

Dunn, L. M., & Dunn, L. M. (1997). Peabody Picture Vocabulary Test, 3rd Edn. Circle Pines, MN: American Guidance Services.

Eigsti, I-M., de Merchena, A. B., Schuh, J. M. & Kelley, E. (2011). Language acquisition in autism spectrum disorders: A developmental review. Research in Autism Spectrum Disorders, 5, 681 – 191.

Elie, B & Chardon, G. (2018). Glottal/Supraglottal Source Separation in Fricatives Based on Non- Stationary Signal Subspace Estimation.

Gotham, K., Risi, S., Pickles, A., & Lord, C. (2006). The Autism Diagnostic Observation Schedule (ADOS). Journal of Autism and Developmental Disorders.

Green, H., & Tobin, Y. (2009). Prosodic analysis is difficult. . .but worth it: a study in high functioning autism. Int. J. Speech Lang. Pathol. 11, 308–315.

Head, A. M., McGillivray, J.A. & Stokes, M.A., (2014). Gender differences in emotionality and sociability in children with autism spectrum disorders. Mol Autism. 5:19.

Healthed Pty Ltd. (2018, August 25). Tony Attwood – Asperger Syndrome in Females, Autism Spectrum Disorder in Females. Retrieved from: https://vimeo.com/122940958

Kenny, L., Hattersley, C., Molins, B., Buckley, C., Povey, C., & Pellicano, E. (2015). Which terms should be used to describe autism? Perspectives from the UK autism community. Autism, 20(4), 442–462.

Kjelgaard, M., & Tager-Flusberg, H. (2001). An investigation of language impairment in autism: implications for genetic subgroups. Lang. Cogn. Process. 16, 287–308.

Lai, M. C., Lombardo, M. V., Pasdo, G., Ruigrok, A.N.V., Wheelwright, S.J. & Sadek, S.A. (2011). A Behavioral Comparison of Male and Female Adults with High Functioning Autism Spectrum Conditions. PLoS ONE 6(6): e20835.

Leekam, S. R., Libby, S.J., Wing, L. et al. (2002). The Diagnostic Interview for Social and Communication Disorders: Algorithms for ICD-10 childhood autism and Wing and Gould autistic spectrum disorders.Journal of Child Psychology and Psychiatry and Allied Disciplines. 43(3):327–42.

Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism diagnostic interview-revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J. Autism Dev. Disord. 24, 659–685.

Lord, C., Rutter, M., Goode, S., Heems-bergen, J., Jordan, H., Mawhood, L., and Schopler, E. (1989). Autism diagnostic observation schedule: a standardized observation of communicative and social behavior. J. Autism Dev. Disord. 19, 185–212.

McCann, J. & Peppé, S. (2003), Prosody in autism spectrum disorders: a critical review. International Journal of Language & Communication Disorders, 38: 325-350.

Nadig, A., & Shaw, H. (2011). Expressive prosody in high-functioning autism: increased pitch range and what it means to listeners. J. Autism Dev. Disord. 42: 499.

National Autistic Society (2015). What is autism? – | autism | Asperger syndrome |. [online] Autism.org.uk. Available at: http://www.autism.org.uk/about-autism/autism-and-asperger- syndrome-an-introduction/what-is-autism.aspx [Accessed 20 Jun. 2019].

Parish-Morris, J., Liberman, M. Y., Cieri, C., Herrington, J. D., Yerys, B. E., Bateman, L., … Schultz, R. T. (2017). Linguistic camouflage in girls with autism spectrum disorder. Molecular Autism, 8(1).

Paul, R., Augustyn, A., Klin, A. & Volkmar, F. R. (2005). Perception and production of prosody by speakers with autism spectrum disorders. Journal of Autism and Developmental Disorders. 205–220.

Paul, R., Shriberg, L. D., McSweeny, J., Cicchetti, D., Klin, A. & Volkmar, F. (2005). Brief report: Relations between prosodic performance and communication and socialization ratings in high functioning speakers with autism spectrum disorders. Journal of Autism and Developmental Disorders. 861–869.

Peppé, S., McCann, J., Gibbon, F. E., O’Hare, A., & Rutherford, M. (2006) Assessing prosodic and pragmatic ability in children with high-functioning autism. QMU Speech Science Research Centre Working Papers, WP-4.

Roach, P. (2000). Techniques for the Phonetic Description of Emotional Speech. In Proceedings of the ISCA Workshop on Speech and Emotion. Newcastle, Northern Ireland. September 2000 (pp 53-59).

The Speech and Language Store LLP. (2018). Receptive Language Assessment with Splingo (Version 4.5.5) [iPad Application Software]. Retrieved from http://itunes.apple.com

Wichmann, A., Dehé, N. & Barth-Weingarten, D., (2009). Where prosody meets pragmatics: research at the interface. Where Prosody meets Pragmatics. Bingley: Emerald, pp. 1-20.

Wing, L. & Gould, J. (1979). Severe impairments of social interaction and associated abnormalities in children: epidemiology and classification.Journal of autism and developmental disorders. 9(1):11–29.

Wynn, C. J., Borrie, S. A., & Sellers, T. P. (2018). Speech Rate Entrainment in Children and Adults With and Without Autism Spectrum Disorder. American Journal of Speech-Language Pathology, 27(3), 965.

Young, E.C., Diehl, J.J., Morris, D., Hyman, S.L. & Bennetto, L. (2005). The use of two language tests to identify pragmatic language problems in children with autism spectrum disorders. Language, Speech, and Hearing Services in Schools. 62–72. 

Neuroaesthetics: Grounded in Science or Merely Aesthetically Pleasing? 

— Original Piece

Armony, J., & Dolan, R. J. (2002). Modulation of spatial attention by fear-conditioned stimuli: an event-related fMRI study. Neuropsychologia, 40(7), 817–826. https://doi.org/10.1016/s0028-3932(01)00178-6

Capó, M. À., Cela-Conde, C. J., Munar, E., Rosselló, J., & Nadal, M. (2008). Towards a framework for the study of the neural correlates of aesthetic preference. Spatial Vision, 21(3–5), 379–396. https://doi.org/10.1163/156856808784532653

Cela-Conde, C. J., Marty, G., Munar, E., Nadal, M., & Burges, L. (2002). The “Style Scheme” Grounds Perception of Paintings. Perceptual and Motor Skills, 95(1), 91–100. https://doi.org/10.2466/pms.2002.95.1.91

Dougherty, D. D., Shin, L. M., Alpert, N. M., Pitman, R. K., Orr, S. P., Lasko, M., Macklin, M. L., Fischman, A. J., & Rauch, S. L. (1999). Anger in healthy men: a PET study using script-driven imagery. Biological Psychiatry, 46(4), 466–472. https://doi.org/10.1016/s0006-3223(99)00063

 Gallace, A., & Spence, C. (2011). Tactile aesthetics: towards a definition of its characteristics and neural correlates. Social Semiotics, 21(4), 569–589. https://doi.org/10.1080/10350330.2011.591998

Jacobs, R. H. A. H., Renken, R., & Cornelissen, F. W. (2012). Neural Correlates of Visual Aesthetics – Beauty as the Coalescence of Stimulus and Internal State. PLoS ONE, 7(2), e31248. https://doi.org/10.1371/journal.pone.0031248

Kawabata, H., & Zeki, S. (2004). Neural Correlates of Beauty. Journal of Neurophysiology, 91(4), 1699–1705. https://doi.org/10.1152/jn.00696.2003

Kedia, G., Mussweiler, T., Mullins, P., & Linden, D. E. J. (2013). The neural correlates of beauty comparison. Social Cognitive and Affective Neuroscience, 9(5), 681–688. https://doi.org/10.1093/scan/nst026

Monet, C. (1900). The Artist’s Garden at Giverny [Painting]. https://www.claude-monet.com/the-artists-garden-at-giverny.jsp#prettyPhoto[image2]/0/

Nadal, M., Marty, G., & Munar, E. (2006). The Search for Objective Measures of Aesthetic Judgment: The Case of Memory Traces. Empirical Studies of the Arts, 24(1), 95–106. https://doi.org/10.2190/5nj2-7f9j-487p-dcpw

The neurobiology of beauty | Semir Zeki | TEDxUCL. (2012, July 2). [Video]. YouTube. https://www.youtube.com/watch?v=NlzanAw0RP4

Zeki, S., & Chén, O. Y. (2020). The Bayesian‐Laplacian brain. European Journal of Neuroscience, 51(6), 1441–1462. https://doi.org/10.1111/ejn.14540

Zeki, S., Chén, O. Y., & Romaya, J. P. (2018). The Biological Basis of Mathematical Beauty. Frontiers in Human Neuroscience, 12, 23–50. https://doi.org/10.3389/fnhum.2018.00467

Zeki, S., Romaya, J. P., Benincasa, D. M. T., & Atiyah, M. F. (2014). The experience of mathematical beauty and its neural correlates. Frontiers in Human Neuroscience, 8, 34–55. https://doi.org/10.3389/fnhum.2014.00068

Psychedelics and the predictive mind: A review of the potential mechanisms that underpin the efficacy of psilocybin to treat depressive disorders. 

— Literature Thesis

Barrett, F.S., Johnson, M.W., Griffiths, R.R., 2015. Validation of the revised Mystical Experience Questionnaire in experimental sessions with psilocybin. J Psychopharmacol (Oxford) 29, 1182–1190. doi:10.1177/0269881115609019

Barrett, F.S., Robbins, H., Smooke, D., Brown, J.L., Griffiths, R.R., 2017. Qualitative and Quantitative Features of Music Reported to Support Peak Mystical Experiences during Psychedelic Therapy Sessions. Front. Psychol. 8, 1238. doi:10.3389/fpsyg.2017.01238

Bastos, A.M., Usrey, W.M., Adams, R.A., Mangun, G.R., Fries, P., Friston, K.J., 2012. Canonical microcircuits for predictive coding. Neuron 76, 695–711. doi:10.1016/j.neuron.2012.10.038

Beard, C., Millner, A.J., Forgeard, M.J.C., Fried, E.I., Hsu, K.J., Treadway, M.T., Leonard, C.V., Kertz, S.J., Björgvinsson, T., 2016. Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychol. Med. 46, 3359–3369. doi:10.1017/S0033291716002300

Beck, A.T., 1979. Cognitive therapy of depression. Guilford press.

Beliveau, V., Ganz, M., Feng, L., Ozenne, B., Højgaard, L., Fisher, P.M., Svarer, C., Greve, D.N., Knudsen, G.M., 2017. A High-Resolution In Vivo Atlas of the Human Brain’s Serotonin System. J. Neurosci. 37, 120–128. doi:10.1523/JNEUROSCI.2830-16.2016

Berkovich-Ohana, A., Dor-Ziderman, Y., Glicksohn, J., Goldstein, A., 2013. Alterations in the sense of time, space, and body in the mindfulness-trained brain: a neurophenomenologically-guided MEG study. Front. Psychol. 4, 912. doi:10.3389/fpsyg.2013.00912

Berlin, I., Givry-Steiner, L., Lecrubier, Y., Puech, A.J., 1998. Measures of anhedonia and hedonic responses to sucrose in depressive and schizophrenic patients in comparison with healthy subjects. Eur. Psychiatry 13, 303–309. doi:10.1016/S0924-9338(98)80048-5

Berman, M.G., Peltier, S., Nee, D.E., Kross, E., Deldin, P.J., Jonides, J., 2011. Depression, rumination and the default network. Soc. Cogn. Affect. Neurosci. 6, 548–555. doi:10.1093/scan/nsq080

Berridge, K.C., Robinson, T.E., 1998. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res. Brain Res. Rev. 28, 309–369. doi:10.1016/S0165-0173(98)00019-8

Bishop, S.R., 2002. What do we really know about mindfulness-based stress reduction? Psychosom. Med. 64, 71–83. doi:10.1097/00006842-200201000-00010

Borsboom, D., 2017. A network theory of mental disorders. World Psychiatry 16, 5–13. doi:10.1002/wps.20375

Borsboom, D., Cramer, A.O.J., 2013. Network analysis: an integrative approach to the structure of psychopathology. Annu. Rev. Clin. Psychol. 9, 91–121. doi:10.1146/annurev-clinpsy-050212-185608

Borsboom, D., Cramer, A.O.J., Schmittmann, V.D., Epskamp, S., Waldorp, L.J., 2011. The small world of psychopathology. PLoS ONE 6, e27407. doi:10.1371/journal.pone.0027407

Borsboom, D., Cramer, A., Kalis, A., 2019. Brain disorders? Not really… Why network structures block reductionism in psychopathology research. Behav. Brain Sci. 1–54. doi:10.1017/S0140525X17002266

Boschloo, L., van Borkulo, C.D., Borsboom, D., Schoevers, R.A., 2016. A prospective study on how symptoms in a network predict the onset of depression. Psychother. Psychosom. 85, 183–184. doi:10.1159/000442001

Brewer, J.A., Garrison, K.A., Whitfield-Gabrieli, S., 2013. What about the “Self” is Processed in the Posterior Cingulate Cortex? Front. Hum. Neurosci. 7, 647. doi:10.3389/fnhum.2013.00647

Brewer, J.A., Worhunsky, P.D., Gray, J.R., Tang, Y.-Y., Weber, J., Kober, H., 2011. Meditation experience is associated with differences in default mode network activity and connectivity. Proc Natl Acad Sci USA 108, 20254–20259. doi:10.1073/pnas.1112029108

Broyd, S.J., Demanuele, C., Debener, S., Helps, S.K., James, C.J., Sonuga-Barke, E.J.S., 2009. Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci. Biobehav. Rev. 33, 279–296. doi:10.1016/j.neubiorev.2008.09.002

Bruineberg, J., Kiverstein, J., Rietveld, E., 2016. The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective. Synthese 195, 1–28. doi:10.1007/s11229-016-1239-1

Bylsma, L.M., Morris, B.H., Rottenberg, J., 2008. A meta-analysis of emotional reactivity in major depressive disorder. Clin. Psychol. Rev. 28, 676–691. doi:10.1016/j.cpr.2007.10.001

Carhart-Harris, R.L., 2018. The entropic brain – revisited. Neuropharmacology 142, 167–178. doi:10.1016/j.neuropharm.2018.03.010

Carhart-Harris, R.L., Bolstridge, M., Day, C.M.J., Rucker, J., Watts, R., Erritzoe, D.E., Kaelen, M., Giribaldi, B., Bloomfield, M., Pilling, S., Rickard, J.A., Forbes, B., Feilding, A., Taylor, D., Curran, H.V., Nutt, D.J., 2018. Psilocybin with psychological support for treatment-resistant depression: six-month follow-up. Psychopharmacology (Berl) 235, 399–408. doi:10.1007/s00213-017-4771-x

Carhart-Harris, R.L., Bolstridge, M., Rucker, J., Day, C.M.J., Erritzoe, D., Kaelen, M., Bloomfield, M., Rickard, J.A., Forbes, B., Feilding, A., Taylor, D., Pilling, S., Curran, V.H., Nutt, D.J., 2016a. Psilocybin with psychological support for treatment-resistant depression: an open-label feasibility study. Lancet Psychiatry 3, 619–627. doi:10.1016/S2215-0366(16)30065-7

Carhart-Harris, R.L., Erritzoe, D., Williams, T., Stone, J.M., Reed, L.J., Colasanti, A., Tyacke, R.J., Leech, R., Malizia, A.L., Murphy, K., Hobden, P., Evans, J., Feilding, A., Wise, R.G., Nutt, D.J., 2012. Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin. Proc Natl Acad Sci USA 109, 2138–2143. doi:10.1073/pnas.1119598109

Carhart-Harris, R.L., Friston, K.J., 2010. The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas. Brain 133, 1265–1283. doi:10.1093/brain/awq010

Carhart-Harris, R.L., Friston, K.J., 2019. REBUS and the anarchic brain: toward a unified model of the brain action of psychedelics. Pharmacol. Rev. 71, 316–344. doi:10.1124/pr.118.017160

Carhart-Harris, R.L., Goodwin, G.M., 2017. The therapeutic potential of psychedelic drugs: past, present, and future. Neuropsychopharmacology 42, 2105–2113. doi:10.1038/npp.2017.84

Carhart-Harris, R.L., Kaelen, M., Whalley, M.G., Bolstridge, M., Feilding, A., Nutt, D.J., 2015. LSD enhances suggestibility in healthy volunteers. Psychopharmacology (Berl) 232, 785–794. doi:10.1007/s00213-014-3714-z

Carhart-Harris, R.L., Leech, R., Hellyer, P.J., Shanahan, M., Feilding, A., Tagliazucchi, E., Chialvo, D.R., Nutt, D., 2014. The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs. Front. Hum. Neurosci. 8, 20. doi:10.3389/fnhum.2014.00020

Carhart-Harris, R.L., Muthukumaraswamy, S., Roseman, L., Kaelen, M., Droog, W., Murphy, K., Tagliazucchi, E., Schenberg, E.E., Nest, T., Orban, C., Leech, R., Williams, L.T., Williams, T.M., Bolstridge, M., Sessa, B., McGonigle, J., Sereno, M.I., Nichols, D., Hellyer, P.J., Hobden, P., Nutt, D.J., 2016b. Neural correlates of the LSD experience revealed by multimodal neuroimaging. Proc Natl Acad Sci USA 113, 4853–4858. doi:10.1073/pnas.1518377113

Carhart-Harris, R.L., Nutt, D.J., 2016. Question-based Drug Development for psilocybin – Authors’ reply. Lancet Psychiatry 3, 807. doi:10.1016/S2215-0366(16)30217-6

Chekroud, A.M., 2015. Unifying treatments for depression: an application of the Free Energy Principle. Front. Psychol. 6, 153. doi:10.3389/fpsyg.2015.00153

Chiesa, A., Malinowski, P., 2011. Mindfulness-based approaches: are they all the same? J. Clin. Psychol. 67, 404–424. doi:10.1002/jclp.20776

Chiesa, A., Serretti, A., 2009. Mindfulness-based stress reduction for stress management in healthy people: a review and meta-analysis. J. Altern. Complement. Med. 15, 593–600. doi:10.1089/acm.2008.0495

Chiesa, A., Serretti, A., 2011. Mindfulness based cognitive therapy for psychiatric disorders: a systematic review and meta-analysis. Psychiatry Res. 187, 441–453. doi:10.1016/j.psychres.2010.08.011

Clark, J.E., Watson, S., Friston, K.J., 2018. What is mood? A computational perspective. Psychol. Med. 48, 2277–2284. doi:10.1017/S0033291718000430

Costa Jr., P.T., Herbst, J.H., McCrae, R.R., Siegler, I.C., 2000. Personality at midlife: Stability, intrinsic maturation, and response to life events. Assessment 7, 365–378.

Cramer, A.O.J., van Borkulo, C.D., Giltay, E.J., van der Maas, H.L.J., Kendler, K.S., Scheffer, M., Borsboom, D., 2016. Major depression as a complex dynamic system. PLoS ONE 11, e0167490. doi:10.1371/journal.pone.0167490

Cramer, A.O.J., Waldorp, L.J., van der Maas, H.L.J., Borsboom, D., 2010. Comorbidity: a network perspective. Behav. Brain Sci. 33, 137–50; discussion 150. doi:10.1017/S0140525X09991567

Dichter, G.S., Smoski, M.J., Kampov-Polevoy, A.B., Gallop, R., Garbutt, J.C., 2010. Unipolar depression does not moderate responses to the Sweet Taste Test. Depress. Anxiety 27, 859–863. doi:10.1002/da.20690

Dombrowski, S.M., Hilgetag, C.C., Barbas, H., 2001. Quantitative architecture distinguishes prefrontal cortical systems in the rhesus monkey. Cereb. Cortex 11, 975–988. doi:10.1093/cercor/11.10.975

Donaldson, C., Lam, D., Mathews, A., 2007. Rumination and attention in major depression. Behav. Res. Ther. 45, 2664–2678. doi:10.1016/j.brat.2007.07.002

Dor-Ziderman, Y., Ataria, Y., Fulder, S., Goldstein, A., Berkovich-Ohana, A., 2016. Self-specific processing in the meditating brain: a MEG neurophenomenology study. Neurosci. Conscious. 2016, niw019. doi:10.1093/nc/niw019

Dor-Ziderman, Y., Berkovich-Ohana, A., Glicksohn, J., Goldstein, A., 2013. Mindfulness-induced selflessness: a MEG neurophenomenological study. Front. Hum. Neurosci. 7, 582. doi:10.3389/fnhum.2013.00582

Dori, G.A., Overholser, J.C., 1999. Depression, hopelessness, and self-esteem: accounting for suicidality in adolescent psychiatric inpatients. Suicide Life Threat. Behav. 29, 309–318.

Edwards, M.J., Adams, R.A., Brown, H., Pareés, I., Friston, K.J., 2012. A Bayesian account of “hysteria”. Brain 135, 3495–3512. doi:10.1093/brain/aws129

Farb, N.A.S., Segal, Z.V., Anderson, A.K., 2013. Mindfulness meditation training alters cortical representations of interoceptive attention. Soc. Cogn. Affect. Neurosci. 8, 15–26. doi:10.1093/scan/nss066

Feldman, H., Friston, K.J., 2010. Attention, uncertainty, and free-energy. Front. Hum. Neurosci. 4, 215. doi:10.3389/fnhum.2010.00215

Felleman, D.J., Van Essen, D.C., 1991. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47. doi:10.1093/cercor/1.1.1

Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E., 2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 102, 9673–9678. doi:10.1073/pnas.0504136102

Freud, S., 1920. Resistance and supression., in: A General Introduction to Psychoanalysis. Horace Liveright, New York, pp. 248–261. doi:10.1037/10667-018

Fried, E.I., Epskamp, S., Nesse, R.M., Tuerlinckx, F., Borsboom, D., 2016. What are “good” depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. J. Affect. Disord. 189, 314–320. doi:10.1016/j.jad.2015.09.005

Fried, E.I., van Borkulo, C.D., Cramer, A.O.J., Boschloo, L., Schoevers, R.A., Borsboom, D., 2017. Mental disorders as networks of problems: A review of recent insights. Soc. Psychiatry Psychiatr. Epidemiol. 52, 1–10. doi:10.1007/s00127-016-1319-z

Friston, K., 2003. Learning and inference in the brain. Neural Netw. 16, 1325–1352. doi:10.1016/j.neunet.2003.06.005

Friston, K., 2005. A theory of cortical responses. Philos. Trans. R. Soc. Lond. B. Biol. Sci 360, 815–836. doi:10.1098/rstb.2005.1622

Friston, K., 2010. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138. doi:10.1038/nrn2787

Friston, K., Kilner, J., Harrison, L., 2006. A free energy principle for the brain. J. Physiol. Paris 100, 70–87. doi:10.1016/j.jphysparis.2006.10.001

Friston, K., Mattout, J., Kilner, J., 2011. Action understanding and active inference. Biol. Cybern. 104, 137–160. doi:10.1007/s00422-011-0424-z

Greicius, M.D., Flores, B.H., Menon, V., Glover, G.H., Solvason, H.B., Kenna, H., Reiss, A.L., Schatzberg, A.F., 2007. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol. Psychiatry 62, 429–437. doi:10.1016/j.biopsych.2006.09.020

Greicius, M.D., Supekar, K., Menon, V., Dougherty, R.F., 2009. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb. Cortex 19, 72–78. doi:10.1093/cercor/bhn059

Griffiths, R.R., Johnson, M.W., Carducci, M.A., Umbricht, A., Richards, W.A., Richards, B.D., Cosimano, M.P., Klinedinst, M.A., 2016. Psilocybin produces substantial and sustained decreases in depression and anxiety in patients with life-threatening cancer: A randomized double-blind trial. J Psychopharmacol (Oxford) 30, 1181–1197. doi:10.1177/0269881116675513

Griffiths, R.R., Johnson, M.W., Richards, W.A., Richards, B.D., McCann, U., Jesse, R., 2011. Psilocybin occasioned mystical-type experiences: immediate and persisting dose-related effects. Psychopharmacology (Berl) 218, 649–665. doi:10.1007/s00213-011-2358-5

Griffiths, R.R., Richards, W.A., McCann, U., Jesse, R., 2006. Psilocybin can occasion mystical-type experiences having substantial and sustained personal meaning and spiritual significance. Psychopharmacology (Berl) 187, 268–83; discussion 284. doi:10.1007/s00213-006-0457-5

Griffiths, R., Richards, W., Johnson, M., McCann, U., Jesse, R., 2008. Mystical-type experiences occasioned by psilocybin mediate the attribution of personal meaning and spiritual significance 14 months later. J Psychopharmacol (Oxford) 22, 621–632. doi:10.1177/0269881108094300

Grob, C.S., Danforth, A.L., Chopra, G.S., Hagerty, M., McKay, C.R., Halberstadt, A.L., Greer, G.R., 2011. Pilot study of psilocybin treatment for anxiety in patients with advanced-stage cancer. Arch. Gen. Psychiatry 68, 71–78. doi:10.1001/archgenpsychiatry.2010.116

Grossman, P., Niemann, L., Schmidt, S., Walach, H., 2004. Mindfulness-based stress reduction and health benefits. A meta-analysis. J. Psychosom. Res. 57, 35–43. doi:10.1016/S0022-3999(03)00573-7

Gururajan, A., Clarke, G., Dinan, T.G., Cryan, J.F., 2016. Molecular biomarkers of depression. Neurosci. Biobehav. Rev. 64, 101–133. doi:10.1016/j.neubiorev.2016.02.011

Gusnard, D.A., Akbudak, E., Shulman, G.L., Raichle, M.E., 2001. Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proc Natl Acad Sci USA 98, 4259–4264. doi:10.1073/pnas.071043098

Halberstadt, A.L., 2015. Recent advances in the neuropsychopharmacology of serotonergic hallucinogens. Behav. Brain Res. 277, 99–120. doi:10.1016/j.bbr.2014.07.016

Hartogsohn, I., 2016. Set and setting, psychedelics and the placebo response: An extra-pharmacological perspective on psychopharmacology. J Psychopharmacol (Oxford) 30, 1259–1267. doi:10.1177/0269881116677852

Hartogsohn, I., 2017. Constructing drug effects: A history of set and setting. Drug Science, Policy and Law 3, 205032451668332. doi:10.1177/2050324516683325

Hartogsohn, I., 2018. The Meaning-Enhancing Properties of Psychedelics and Their Mediator Role in Psychedelic Therapy, Spirituality, and Creativity. Front. Neurosci. 12, 129. doi:10.3389/fnins.2018.00129

Heeren, A., McNally, R.J., 2016. An integrative network approach to social anxiety disorder: The complex dynamic interplay among attentional bias for threat, attentional control, and symptoms. J. Anxiety Disord. 42, 95–104. doi:10.1016/j.janxdis.2016.06.009

Hendrie, C., Pickles, A., 2016. Psilocybin: panacea or placebo? Lancet Psychiatry 3, 805–806. doi:10.1016/S2215-0366(16)30103-1

Hood, R.W., 1975. The construction and preliminary validation of a measure of reported mystical experience. Journal for the scientific study of religion 29–41.

Hood, R.W., Morris, R.J., Watson, P.J., 1993. Further factor analysis of hood’s mysticism scale. Psychol. Rep. 73, 1176–1178. doi:10.2466/pr0.1993.73.3f.1176

Huang, Y., Rao, R.P.N., 2011. Predictive coding. Wiley Interdiscip. Rev. Cogn. Sci. 2, 580–593. doi:10.1002/wcs.142

Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D.S., Quinn, K., Sanislow, C., Wang, P., 2010. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167, 748–751. doi:10.1176/appi.ajp.2010.09091379

Kabat-Zinn, J., 1982. An outpatient program in behavioral medicine for chronic pain patients based on the practice of mindfulness meditation: theoretical considerations and preliminary results. Gen. Hosp. Psychiatry 4, 33–47. doi:10.1016/0163-8343(82)90026-3

Kabat-Zinn, J., 1990. Full catastrophe living: The program of the stress reduction clinic at the University of Massachusetts Medical Center. 264–273.

Kabat-Zinn, J., 2011. Some reflections on the origins of MBSR, skillful means, and the trouble with maps. Contemporary Buddhism 12, 281–306. doi:10.1080/14639947.2011.564844

Kaelen, M., Giribaldi, B., Raine, J., Evans, L., Timmerman, C., Rodriguez, N., Roseman, L., Feilding, A., Nutt, D., Carhart-Harris, R., 2018. The hidden therapist: evidence for a central role of music in psychedelic therapy. Psychopharmacology (Berl) 235, 505–519. doi:10.1007/s00213-017-4820-5

Kanai, R., Komura, Y., Shipp, S., Friston, K., 2015. Cerebral hierarchies: predictive processing, precision and the pulvinar. Philos. Trans. R. Soc. Lond. B. Biol. Sci 370. doi:10.1098/rstb.2014.0169

Kaptchuk, T.J., Kelley, J.M., Conboy, L.A., Davis, R.B., Kerr, C.E., Jacobson, E.E., Kirsch, I., Schyner, R.N., Nam, B.H., Nguyen, L.T., Park, M., Rivers, A.L., McManus, C., Kokkotou, E., Drossman, D.A., Goldman, P., Lembo, A.J., 2008. Components of placebo effect: randomised controlled trial in patients with irritable bowel syndrome. BMJ 336, 999–1003. doi:10.1136/bmj.39524.439618.25

Kelly, A.M.C., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., Milham, M.P., 2008. Competition between functional brain networks mediates behavioral variability. Neuroimage 39, 527–537. doi:10.1016/j.neuroimage.2007.08.008

Khan, A., Brown, W.A., 2015. Antidepressants versus placebo in major depression: an overview. World Psychiatry 14, 294–300. doi:10.1002/wps.20241

Khan, A., Faucett, J., Lichtenberg, P., Kirsch, I., Brown, W.A., 2012. A systematic review of comparative efficacy of treatments and controls for depression. PLoS ONE 7, e41778. doi:10.1371/journal.pone.0041778

Knill, D.C., Pouget, A., 2004. The Bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci. 27, 712–719. doi:10.1016/j.tins.2004.10.007

Kometer, M., Schmidt, A., Bachmann, R., Studerus, E., Seifritz, E., Vollenweider, F.X., 2012. Psilocybin biases facial recognition, goal-directed behavior, and mood state toward positive relative to negative emotions through different serotonergic subreceptors. Biol. Psychiatry 72, 898–906. doi:10.1016/j.biopsych.2012.04.005

Kraehenmann, R., Preller, K.H., Scheidegger, M., Pokorny, T., Bosch, O.G., Seifritz, E., Vollenweider, F.X., 2015. Psilocybin-Induced Decrease in Amygdala Reactivity Correlates with Enhanced Positive Mood in Healthy Volunteers. Biol. Psychiatry 78, 572–581. doi:10.1016/j.biopsych.2014.04.010

Kraehenmann, R., Schmidt, A., Friston, K., Preller, K.H., Seifritz, E., Vollenweider, F.X., 2016. The mixed serotonin receptor agonist psilocybin reduces threat-induced modulation of amygdala connectivity. Neuroimage Clin. 11, 53–60. doi:10.1016/j.nicl.2015.08.009

Krebs, T.S., Johansen, P.-Ø., 2012. Lysergic acid diethylamide (LSD) for alcoholism: meta-analysis of randomized controlled trials. J Psychopharmacol (Oxford) 26, 994–1002. doi:10.1177/0269881112439253

Kube, T., Schwarting, R., Rozenkrantz, L., Glombiewski, J.A., Rief, W., 2019. Distorted cognitive processes in major depression: A predictive processing perspective. Biol. Psychiatry. doi:10.1016/j.biopsych.2019.07.017

Kuyken, W., Byford, S., Taylor, R.S., Watkins, E., Holden, E., White, K., Barrett, B., Byng, R., Evans, A., Mullan, E., Teasdale, J.D., 2008. Mindfulness-based cognitive therapy to prevent relapse in recurrent depression. J. Consult. Clin. Psychol. 76, 966–978. doi:10.1037/a0013786

Lawson, R.P., Rees, G., Friston, K.J., 2014. An aberrant precision account of autism. Front. Hum. Neurosci. 8, 302. doi:10.3389/fnhum.2014.00302

Leary, T., Litwin, G.H., Metzner, R., 1963. Reactions to psilocybin administered in a supportive environment. J. Nerv. Ment. Dis. 137, 561–573.

Lebedev, A.V., Kaelen, M., Lövdén, M., Nilsson, J., Feilding, A., Nutt, D.J., Carhart-Harris, R.L., 2016. LSD-induced entropic brain activity predicts subsequent personality change. Hum. Brain Mapp. 37, 3203–3213. doi:10.1002/hbm.23234

Lebedev, A.V., Lövdén, M., Rosenthal, G., Feilding, A., Nutt, D.J., Carhart-Harris, R.L., 2015. Finding the self by losing the self: Neural correlates of ego-dissolution under psilocybin. Hum. Brain Mapp. 36, 3137–3153. doi:10.1002/hbm.22833

Leuchter, A.F., Hunter, A.M., Tartter, M., Cook, I.A., 2014. Role of pill-taking, expectation and therapeutic alliance in the placebo response in clinical trials for major depression. Br. J. Psychiatry 205, 443–449. doi:10.1192/bjp.bp.113.140343

Li, Y., Tong, S., Liu, D., Gai, Y., Wang, X., Wang, J., Qiu, Y., Zhu, Y., 2008. Abnormal EEG complexity in patients with schizophrenia and depression. Clin. Neurophysiol. 119, 1232–1241. doi:10.1016/j.clinph.2008.01.104

Ludwig, A.M., 1985. Cognitive processes associated with “spontaneous” recovery from alcoholism. J. Stud. Alcohol 46, 53–58. doi:10.15288/jsa.1985.46.53

Ludwig, A., Levine, J., Stark, L., Lazar, R., 1969. A clinical study of LSD treatment in alcoholism. AJP 126, 59–69. doi:10.1176/ajp.126.1.59

Lutz, A., Mattout, J., Pagnoni, G., 2019. The epistemic and pragmatic value of non-action: a predictive coding perspective on meditation. Curr. Opin. Psychol. 28, 166–171. doi:10.1016/j.copsyc.2018.12.019

Lutz, A., Slagter, H.A., Dunne, J.D., Davidson, R.J., 2008. Attention regulation and monitoring in meditation. Trends Cogn Sci (Regul Ed) 12, 163–169. doi:10.1016/j.tics.2008.01.005

Lutz, J., Brühl, A.B., Scheerer, H., Jäncke, L., Herwig, U., 2016. Neural correlates of mindful self-awareness in mindfulness meditators and meditation-naïve subjects revisited. Biol. Psychol. 119, 21–30. doi:10.1016/j.biopsycho.2016.06.010

Lyons, T., Carhart-Harris, R.L., 2018. More Realistic Forecasting of Future Life Events After Psilocybin for Treatment-Resistant Depression. Front. Psychol. 9, 1721. doi:10.3389/fpsyg.2018.01721

MacLean, K.A., Johnson, M.W., Griffiths, R.R., 2011. Mystical experiences occasioned by the hallucinogen psilocybin lead to increases in the personality domain of openness. J Psychopharmacol (Oxford) 25, 1453–1461. doi:10.1177/0269881111420188

Maclean, K.A., Leoutsakos, J.-M.S., Johnson, M.W., Griffiths, R.R., 2012. Factor Analysis of the Mystical Experience Questionnaire: A Study of Experiences Occasioned by the Hallucinogen Psilocybin. J. Sci. Study Relig. 51, 721–737. doi:10.1111/j.1468-5906.2012.01685.x

Maslow, A.H., 1962. Peak-experiences as acute identity-experiences., in: Toward a Psychology of Being. D Van Nostrand, Princeton, pp. 97–108. doi:10.1037/10793-007

Mason, M.F., Norton, M.I., Van Horn, J.D., Wegner, D.M., Grafton, S.T., Macrae, C.N., 2007. Wandering minds: the default network and stimulus-independent thought. Science 315, 393–395. doi:10.1126/science.1131295

Méndez, M.A., Zuluaga, P., Hornero, R., Gómez, C., Escudero, J., Rodríguez-Palancas, A., Ortiz, T., Fernández, A., 2012. Complexity analysis of spontaneous brain activity: effects of depression and antidepressant treatment. J Psychopharmacol (Oxford) 26, 636–643. doi:10.1177/0269881111408966

Metzinger, T.K., 2017. The Problem of Mental Action. Theoretical Philosophy/MIND Group – JGU Mainz. doi:10.15502/9783958573208

Miller, W.R., 2004. The phenomenon of quantum change. J. Clin. Psychol. 60, 453–460. doi:10.1002/jclp.20000

Millière, R., Carhart-Harris, R.L., Roseman, L., Trautwein, F.-M., Berkovich-Ohana, A., 2018. Psychedelics, Meditation, and Self-Consciousness. Front. Psychol. 9, 1475. doi:10.3389/fpsyg.2018.01475

Mroczek, D.K., Spiro, A., 2003. Modeling intraindividual change in personality traits: findings from the normative aging study. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 58, P153–P165. doi:10.1093/geronb/58.3.P153

Muthukumaraswamy, S.D., Carhart-Harris, R.L., Moran, R.J., Brookes, M.J., Williams, T.M., Errtizoe, D., Sessa, B., Papadopoulos, A., Bolstridge, M., Singh, K.D., Feilding, A., Friston, K.J., Nutt, D.J., 2013. Broadband cortical desynchronization underlies the human psychedelic state. J. Neurosci. 33, 15171–15183. doi:10.1523/JNEUROSCI.2063-13.2013

Nash, J.D., Newberg, A., Awasthi, B., 2013. Toward a unifying taxonomy and definition for meditation. Front. Psychol. 4, 806. doi:10.3389/fpsyg.2013.00806

Nichols, D.E., 2016. Psychedelics. Pharmacol. Rev. 68, 264–355. doi:10.1124/pr.115.011478

Nichols, D.E., Johnson, M.W., Nichols, C.D., 2017. Psychedelics as medicines: an emerging new paradigm. Clin. Pharmacol. Ther. 101, 209–219. doi:10.1002/cpt.557

Nolen-Hoeksema, S., 2000. The role of rumination in depressive disorders and mixed anxiety/depressive symptoms. J. Abnorm. Psychol. 109, 504–511. doi:10.1037/0021-843X.109.3.504

Nour, M.M., Evans, L., Nutt, D., Carhart-Harris, R.L., 2016. Ego-Dissolution and Psychedelics: Validation of the Ego-Dissolution Inventory (EDI). Front. Hum. Neurosci. 10, 269. doi:10.3389/fnhum.2016.00269

Nutt, D.J., King, L.A., Phillips, L.D., Independent Scientific Committee on Drugs, 2010. Drug harms in the UK: a multicriteria decision analysis. Lancet 376, 1558–1565. doi:10.1016/S0140-6736(10)61462-6

Oram, M., 2014. Efficacy and enlightenment: LSD psychotherapy and the Drug Amendments of 1962. J. Hist. Med. Allied Sci. 69, 221–250. doi:10.1093/jhmas/jrs050

Pagnoni, G., 2012. Dynamical properties of BOLD activity from the ventral posteromedial cortex associated with meditation and attentional skills. J. Neurosci. 32, 5242–5249. doi:10.1523/JNEUROSCI.4135-11.2012

Pagnoni, G., 2019. The contemplative exercise through the lenses of predictive processing: A promising approach. Prog. Brain Res. 244, 299–322. doi:10.1016/bs.pbr.2018.10.022

Pahnke, W.N., 1969. Psychedelic drugs and mystical experience. Int. Psychiatry Clin. 5, 149–162.

Palhano-Fontes, F., Andrade, K.C., Tofoli, L.F., Santos, A.C., Crippa, J.A.S., Hallak, J.E.C., Ribeiro, S., de Araujo, D.B., 2015. The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network. PLoS ONE 10, e0118143. doi:10.1371/journal.pone.0118143

Park, H.-J., Friston, K., 2013. Structural and functional brain networks: from connections to cognition. Science 342, 1238411. doi:10.1126/science.1238411

Passie, T., Seifert, J., Schneider, U., Emrich, H.M., 2002. The pharmacology of psilocybin. Addict. Biol. 7, 357–364. doi:10.1080/1355621021000005937

Petri, G., Expert, P., Turkheimer, F., Carhart-Harris, R., Nutt, D., Hellyer, P.J., Vaccarino, F., 2014. Homological scaffolds of brain functional  networks. J. R. Soc. Interface 11, 20140873. doi:10.1098/rsif.2014.0873

Pezard, L., Nandrino, J.L., Renault, B., el Massioui, F., Allilaire, J.F., Müller, J., Varela, F., Martinerie, J., 1996. Depression as a dynamical disease. Biol. Psychiatry 39, 991–999. doi:10.1016/0006-3223(95)00307-x

Piet, J., Hougaard, E., 2011. The effect of mindfulness-based cognitive therapy for prevention of relapse in recurrent major depressive disorder: a systematic review and meta-analysis. Clin. Psychol. Rev. 31, 1032–1040. doi:10.1016/j.cpr.2011.05.002

Quednow, B.B., Kometer, M., Geyer, M.A., Vollenweider, F.X., 2012. Psilocybin-induced deficits in automatic and controlled inhibition are attenuated by ketanserin in healthy human volunteers. Neuropsychopharmacology 37, 630–640. doi:10.1038/npp.2011.228

Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., 2001. A default mode of brain function. Proc Natl Acad Sci USA 98, 676–682. doi:10.1073/pnas.98.2.676

Ray, T.S., 2010. Psychedelics and the human receptorome. PLoS ONE 5, e9019. doi:10.1371/journal.pone.0009019

Rhemtulla, M., Fried, E.I., Aggen, S.H., Tuerlinckx, F., Kendler, K.S., Borsboom, D., 2016. Network analysis of substance abuse and dependence symptoms. Drug Alcohol Depend. 161, 230–237. doi:10.1016/j.drugalcdep.2016.02.005

Roseman, L., Leech, R., Feilding, A., Nutt, D.J., Carhart-Harris, R.L., 2014. The effects of psilocybin and MDMA on between-network resting state functional connectivity in healthy volunteers. Front. Hum. Neurosci. 8, 204. doi:10.3389/fnhum.2014.00204

Roseman, L., Nutt, D.J., Carhart-Harris, R.L., 2018. Quality of Acute Psychedelic Experience Predicts Therapeutic Efficacy of Psilocybin for Treatment-Resistant Depression. Front. Pharmacol. 8, 974. doi:10.3389/fphar.2017.00974

Ross, S., Bossis, A., Guss, J., Agin-Liebes, G., Malone, T., Cohen, B., Mennenga, S.E., Belser, A., Kalliontzi, K., Babb, J., Su, Z., Corby, P., Schmidt, B.L., 2016. Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. J Psychopharmacol (Oxford) 30, 1165–1180. doi:10.1177/0269881116675512

Rucker, J.J., Jelen, L.A., Flynn, S., Frowde, K.D., Young, A.H., 2016. Psychedelics in the treatment of unipolar mood disorders: a systematic review. J Psychopharmacol (Oxford) 30, 1220–1229. doi:10.1177/0269881116679368

Schartner, M.M., Carhart-Harris, R.L., Barrett, A.B., Seth, A.K., Muthukumaraswamy, S.D., 2017. Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin. Sci. Rep. 7, 46421. doi:10.1038/srep46421

Scheibner, H.J., Bogler, C., Gleich, T., Haynes, J.-D., Bermpohl, F., 2017. Internal and external attention and the default mode network. Neuroimage 148, 381–389. doi:10.1016/j.neuroimage.2017.01.044

Segal, Z.J., Williams, M.G., Teasdale, J.D., 2002. Mindfulness based cognitive therapy for depression: a new approach to preventing relapses. Guildford Press, New York.

Seth, A.K., 2013. Interoceptive inference, emotion, and the embodied self. Trends Cogn Sci (Regul Ed) 17, 565–573. doi:10.1016/j.tics.2013.09.007

Shanon, B., 2002. The antipodes of the mind: Charting the phenomenology of the ayahuasca experience. Oxford University Press, USA.

Sheline, Y.I., Barch, D.M., Donnelly, J.M., Ollinger, J.M., Snyder, A.Z., Mintun, M.A., 2001. Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol. Psychiatry 50, 651–658. doi:10.1016/s0006-3223(01)01263-x

Sheline, Y.I., Barch, D.M., Price, J.L., Rundle, M.M., Vaishnavi, S.N., Snyder, A.Z., Mintun, M.A., Wang, S., Coalson, R.S., Raichle, M.E., 2009. The default mode network and self-referential processes in depression. Proc Natl Acad Sci USA 106, 1942–1947. doi:10.1073/pnas.0812686106

Simon, R., Engström, M., 2015. The default mode network as a biomarker for monitoring the therapeutic effects of meditation. Front. Psychol. 6, 776. doi:10.3389/fpsyg.2015.00776

Snell, T.L., Simmonds, J.G., 2015. Mystical experiences in nature. Archive for the Psychology of Religion 37, 169–184. doi:10.1163/15736121-12341303

Sporns, O., 2014. Contributions and challenges for network models in cognitive neuroscience. Nat. Neurosci. 17, 652–660. doi:10.1038/nn.3690

Stace, W.T., 1960. Mysticism and philosophy. Research in politics and society.

Stewart-Williams, S., 2004. The placebo puzzle: putting together the pieces. Health Psychol. 23, 198–206. doi:10.1037/0278-6133.23.2.198

Swanson, L.R., 2018. Unifying theories of psychedelic drug effects. Front. Pharmacol. 9, 172. doi:10.3389/fphar.2018.00172

Thomas, K., Malcolm, B., Lastra, D., 2017. Psilocybin-Assisted Therapy: A Review of a Novel Treatment for Psychiatric Disorders. J. Psychoactive Drugs 49, 446–455. doi:10.1080/02791072.2017.1320734

Thompson, E., Lutz, A., Cosmelli, D., 2005. Neurophenomenology: an introduction for neurophilosophers, in: Brook, A., Akins, K. (Eds.), Cognition and the Brain: The Philosophy and Neuroscience Movement. Cambridge University Press, pp. 40–97. doi:10.1017/CBO9780511610608.003

Trigwell, J.L., Francis, A.J.P., Bagot, K.L., 2014. Nature Connectedness and Eudaimonic Well-Being: Spirituality as a Potential Mediator. Ecopsychology 6, 241–251. doi:10.1089/eco.2014.0025

van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B.W.J.H., Waldorp, L.J., Schoevers, R.A., 2015. Association of symptom network structure with the course of [corrected] depression. JAMA Psychiatry 72, 1219–1226. doi:10.1001/jamapsychiatry.2015.2079

Van Dam, N.T., van Vugt, M.K., Vago, D.R., Schmalzl, L., Saron, C.D., Olendzki, A., Meissner, T., Lazar, S.W., Kerr, C.E., Gorchov, J., Fox, K.C.R., Field, B.A., Britton, W.B., Brefczynski-Lewis, J.A., Meyer, D.E., 2018. Mind the hype: A critical evaluation and prescriptive agenda for research on mindfulness and meditation. Perspect. Psychol. Sci. 13, 36–61. doi:10.1177/1745691617709589

van den Heuvel, M.P., Sporns, O., 2011. Rich-club organization of the human connectome. J. Neurosci. 31, 15775–15786. doi:10.1523/JNEUROSCI.3539-11.2011

van den Heuvel, M., Mandl, R., Luigjes, J., Hulshoff Pol, H., 2008. Microstructural organization of the cingulum tract and the level of default mode functional connectivity. J. Neurosci. 28, 10844–10851. doi:10.1523/JNEUROSCI.2964-08.2008

van de Leemput, I.A., Wichers, M., Cramer, A.O.J., Borsboom, D., Tuerlinckx, F., Kuppens, P., van Nes, E.H., Viechtbauer, W., Giltay, E.J., Aggen, S.H., Derom, C., Jacobs, N., Kendler, K.S., van der Maas, H.L.J., Neale, M.C., Peeters, F., Thiery, E., Zachar, P., Scheffer, M., 2014. Critical slowing down as early warning for the onset and termination of depression. Proc Natl Acad Sci USA 111, 87–92. doi:10.1073/pnas.1312114110

van Elk, M., Aleman, A., 2017. Brain mechanisms in religion and spirituality: An integrative predictive processing framework. Neurosci. Biobehav. Rev. 73, 359–378. doi:10.1016/j.neubiorev.2016.12.031

Varnäs, K., Halldin, C., Hall, H., 2004. Autoradiographic distribution of serotonin transporters and receptor subtypes in human brain. Hum. Brain Mapp. 22, 246–260. doi:10.1002/hbm.20035

Vezoli, J., Falchier, A., Jouve, B., Knoblauch, K., Young, M., Kennedy, H., 2004. Quantitative analysis of connectivity in the visual cortex: extracting function from structure. Neuroscientist 10, 476–482. doi:10.1177/1073858404268478

Viol, A., Palhano-Fontes, F., Onias, H., de Araujo, D.B., Viswanathan, G.M., 2017. Shannon entropy of brain functional complex networks under the influence of the psychedelic Ayahuasca. Sci. Rep. 7, 7388. doi:10.1038/s41598-017-06854-0

Vollenweider, F.X., Kometer, M., 2010. The neurobiology of psychedelic drugs: implications for the treatment of mood disorders. Nat. Rev. Neurosci. 11, 642–651. doi:10.1038/nrn2884

Vollenweider, F.X., Vollenweider-Scherpenhuyzen, M.F., Bäbler, A., Vogel, H., Hell, D., 1998. Psilocybin induces schizophrenia-like psychosis in humans via a serotonin-2 agonist action. Neuroreport 9, 3897–3902. doi:10.1097/00001756-199812010-00024

Weber, E.T., Andrade, R., 2010. Htr2a Gene and 5-HT(2A) Receptor Expression in the Cerebral Cortex Studied Using Genetically Modified Mice. Front. Neurosci. 4. doi:10.3389/fnins.2010.00036

Wichers, M., Groot, P.C., Psychosystems, ESM Group, EWS Group, 2016. Critical slowing down as a personalized early warning signal for depression. Psychother. Psychosom. 85, 114–116. doi:10.1159/000441458

Wild, L.G., Flisher, A.J., Lombard, C., 2004. Suicidal ideation and attempts in adolescents: associations with depression and six domains of self-esteem. J. Adolesc. 27, 611–624. doi:10.1016/j.adolescence.2004.03.001

Xue, S.-W., Wang, D., Tan, Z., Wang, Y., Lian, Z., Sun, Y., Hu, X., Wang, X., Zhou, X., 2019. Disrupted brain entropy and functional connectivity patterns of thalamic subregions in major depressive disorder. Neuropsychiatr. Dis. Treat. 15, 2629–2638. doi:10.2147/NDT.S220743

Yon, D., de Lange, F.P., Press, C., 2019. The predictive brain as a stubborn scientist. Trends Cogn Sci (Regul Ed) 23, 6–8. doi:10.1016/j.tics.2018.10.003

Painting Hypotheses, Cooking Methods, and Composing Results: A Review on “Proust was a Neuroscientist” 

— Original Piece

Lehrer, J. (2012). Proust was a neuroscientist. Edinburgh: Canongate.

Time Distortions: A Review 

— Literature Thesis

Abe, K., Oda, N., Araki, R., & Igata, M. (1989). Macropsia, Micropsia, and Episodic Illusions in Japanese Adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 28(4), 493–496. https://doi.org/10.1097/00004583-198907000-00004

Allman, M. J., & Meck, W. H. (2012). Pathophysiological distortions in time perception and timed performance. Brain, 135(3), 656–677. https://doi.org/10.1093/brain/awr210

Bech, P. (1975). Depression: Influence on time estimation and time experience, 42–50.

Binswanger, L. (1960). Melancholie und Manie; phänomenologische Studien.

Blewett, A. E. (1992). Abnormal subjective time experience in depression. British Journal of Psychiatry, 161(AUG.), 195–200. https://doi.org/10.1192/bjp.161.2.195

Blom, J. D. (2016). Alice in Wonderland syndrome A systematic review. Neurology: Clinical Practice. Lippincott Williams and Wilkins. https://doi.org/10.1212/CPJ.0000000000000251

Bschor, T., Ising, M., Bauer, M., Lewitzka, U., Skerstupeit, M., Müller-Oerlinghausen, B., & Baethge, C. (2004). Time experience and time judgment in major depression, mania and healthy subjects. A controlled study of 93 subjects. Acta Psychiatrica Scandinavica, 109(3), 222–229. https://doi.org/10.1046/j.0001-690X.2003.00244.x

Carroll L. (1865). Alice’s Adventures in Wonderland (London: Ma). London: MacMillan and Co.

Clarke, S., Ivry, R., Grinband, J., Roberts, S., & Shimizu, N. (1996). Exploring the domain of the cerebellar timing system. Advances in Psychology,115(C), 257–280. https://doi.org/10.1016/S0166-4115(96)80063-X

Craig, A. D. (2009). Emotional moments across time: A possible neural basis for time perception in the anterior insula. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1525), 1933–1942. https://doi.org/10.1098/rstb.2009.0008

Davalos, D. B., Kisley, M. A., & Ross, R. G. (2003). Effects of interval duration on temporal processing in schizophrenia. Brain and Cognition, 52(3), 295–301. https://doi.org/10.1016/S0278-2626(03)00157-X

Elvevåg, B., McCormack, T., Gilbert, A., Brown, G. D. A., Weinberger, D. R., & Goldberg, T. E. (2003). Duration judgements in patients with schizophrenia. Psychological Medicine, 33(7), 1249–1261. https://doi.org/10.1017/S0033291703008122

Freedman, B. J. (1974). The Subjective Experience of Perceptual and Cognitive Disturbances in Schizophrenia. Archives of General Psychiatry, 30(3), 333. https://doi.org/10.1001/archpsyc.1974.01760090047008

Fuchs, T., & Van Duppen, Z. (2017). Time and Events: On the Phenomenology of Temporal Experience in Schizophrenia (Ancillary Article to EAWE Domain 2). Psychopathology, 50(1), 68–74. https://doi.org/10.1159/000452768

Ghaemi, S. N. (2007). Feeling and time: The phenomenology of mood disorders, depressive realism, and existential psychotherapy. Schizophrenia Bulletin, 33(1), 122–130. https://doi.org/10.1093/schbul/sbl061

Gibbon, J., Church, R. M., & Meck, W. H. (1984). Scalar Timing in Memory. Annals of the New York Academy of Sciences. https://doi.org/10.1111/j.1749-6632.1984.tb23417.x

Gibbon, J., Malapanits, C., Dale, C. L., & Gallistep, C. R. (1997). Toward a neurobiology of temporal cognition: advances and challenges. Current Opinion in Neurobiology, 7, 170–184.

Jaspers, K. (1997). General Psychopathology, Vol. 1. Johns Hopkins University Press.

Jia, Y., & Miao, Y. (2018). Evidence for the perception of time distortion during episodes of Alice in wonderland syndrome. Journal of Nervous and Mental Disease, 206(6), 473–475. https://doi.org/10.1097/NMD.0000000000000825

Jones, C. R. G., & Jahanshahi, M. (2011). Dopamine Modulates Striato-Frontal Functioning during Temporal Processing. Frontiers in Integrative Neuroscience, 5, 70. https://doi.org/10.3389/fnint.2011.00070

Kitamura, T., & Kumar, R. (1982). Time passes slowly for patients with depressive state. Acta Psychiatrica Scandinavica, 65(6), 415–420. https://doi.org/10.1111/j.1600-0447.1982.tb00865.x

Kuhs, H. (1991). Time experience in melancholia: A comparison between findings based on phenomenology and experimental psychology. Comprehensive Psychiatry, 32(4), 324–329. https://doi.org/10.1016/0010-440X(91)90081-M

Lake, J. I. (2016). Recent advances in understanding emotion-driven temporal distortions. Current Opinion in Behavioral Sciences, 8, 214–219. https://doi.org/10.1016/j.cobeha.2016.02.009

Liu, A. M., Liu, J. G., Liu, G. W., & Liu, G. T. (2014). “Alice in wonderland” syndrome: Presenting and follow-up characteristics. Pediatric Neurology, 51(3), 317–320. https://doi.org/10.1016/j.pediatrneurol.2014.04.007

Mangels, J. A., Ivry, R. B., & Shimizu, N. (1998). Dissociable contributions of the prefrontal and neocerebellar cortex to time perception. Cognitive Brain Research, 7(1), 15–39. https://doi.org/10.1016/S0926-6410(98)00005-6

Mizuno, M., Kashima, H., Chiba, H., Murakami, M., & Asai, M. (1998). “Alice in Wonderland” syndrome as a precursor of depressive disorder. Psychopathology, 31(2), 85–89. https://doi.org/10.1159/000029027

Naarden, T., Ter Meulen, B. C., Van Der Weele, S. I., & Blom, J. Di. (2019). Alice in wonderland syndrome as a presenting manifestation of Creutzfeldt-Jakob disease. Frontiers in Neurology, 10(MAY), 1–6. https://doi.org/10.3389/fneur.2019.00473

O’Toole, P., & Modestino, E. J. (2017). Alice in Wonderland Syndrome: A real life version of Lewis Carroll’s novel. Brain and Development, 39(6), 470–474. https://doi.org/10.1016/j.braindev.2017.01.004

Perdices, M. (2018). The Alice in Worderland Syndrome. Neuropsychological Rehabilitation, 28(2), 189–198. https://doi.org/10.1080/09602011.2016.1224191

Rao, S. M., Mayer, A. R., & Harrington, D. L. (2001). The evolution of brain activation during temporal processing. Nature Neuroscience. https://doi.org/10.1038/85191

Ratcliffe, M. (2012). Varieties of temporal experience in depression. Journal of Medicine and Philosophy (United Kingdom), 37(2), 114–138. https://doi.org/10.1093/jmp/jhs010

Sackett, A. M., Meyvis, T., Nelson, L. D., Converse, B. A., & Sackett, A. L. (2010). You’re having fun when time flies: The hedonic consequences of subjective time progression. Psychological Science, 21(1), 111–117. https://doi.org/10.1177/0956797609354832

Schmidt, H., McFarland, J., Ahmed, M., McDonald, C., & Elliott, M. A. (2011). Low-Level Temporal Coding Impairments in Psychosis: Preliminary Findings and Recommendations for Further Studies. Journal of Abnormal Psychology, 120(2), 476–482. https://doi.org/10.1037/a0023387

Shammas, M. K. (2020). The Curious Case of the Fast Feelers: A Reflection on Alice in Wonderland Syndrome. Pediatric Neurology. https://doi.org/10.1016/j.pediatrneurol.2020.06.004

Stanghellini, G., Ballerini, M., Presenza, S., Mancini, M., Northoff, G., & Cutting, J. (2017). Abnormal Time Experiences in Major Depression: An Empirical Qualitative Study. Psychopathology, 50(2), 125–140. https://doi.org/10.1159/000452892

Stanghellini, G., Ballerini, M., Presenza, S., Mancini, M., Raballo, A., Blasi, S., & Cutting, J. (2016). Psychopathology of Lived Time: Abnormal Time Experience in Persons with Schizophrenia. Schizophrenia Bulletin, 42(1), 45–55. https://doi.org/10.1093/schbul/sbv052

Teixeira, S., Machado, S., Paes, F., Velasques, B., Silva, J., Sanfim, A., … Arias-Carrion, O. (2013). Time Perception Distortion in Neuropsychiatric and Neurological Disorders. CNS & Neurological Disorders – Drug Targets, 12(5), 567–582. https://doi.org/10.2174/18715273113129990080

Tellenbach, H. (1980). Melancholy: history of the problem, endogeneity, typology, pathogenesis, clinical considerations (Vol. 9). Duquesne University Press.

Thoenes, S., & Oberfeld, D. (2017). Meta-analysis of time perception and temporal processing in schizophrenia: Differential effects on precision and accuracy. Clinical Psychology Review, 54(July 2016), 44–64. https://doi.org/10.1016/j.cpr.2017.03.007

Thönes, S., & Oberfeld, D. (2015). Time perception in depression: A meta-analysis. Journal of Affective Disorders, 175, 359–372. https://doi.org/10.1016/j.jad.2014.12.057

Treisman, M. (1963). Temporal discrimination and the indifference interval. Implications for a model of the “internal clock”. Psychological Monographs. https://doi.org/10.1037/h0093864

Tysk. (1990). Negative Schizophrenia ’, 1990.

Tysk, L. (1984a). A longitudinal study of time estimation in psychotic disorders. Perceptual and Motor Skills, 59(3), 779–789. https://doi.org/10.2466/pms.1984.59.3.779

Tysk, L. (1984b). Time perception and affective disorders. Perceptual and Motor Skills, 58(2), 455–464. https://doi.org/10.2466/pms.1984.58.2.455

Üstün, S., Kale, E. H., & Çiçek, M. (2017). Neural networks for time perception and working memory. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2017.00083

Vogel, D.H.V., Beeker, T., Haidl, T., Kupke, C., Heinze, M., & Vogeley, K. (2019). Disturbed time experience during and after psychosis. Schizophrenia Research: Cognition, 17(January), 100136. https://doi.org/10.1016/j.scog.2019.100136

Vogel, D.H.V., Falter-Wagner, C. M., Schoofs, T., Krämer, K., Kupke, C., & Vogeley, K. (2018). Flow and structure of time experience – concept, empirical validation and implications for psychopathology. Phenomenology and the Cognitive Sciences, 1–24. https://doi.org/10.1007/s11097-018-9573-z

Vogel, H.V., Krämer, K., Schoofs, T., Kupke, C., & Vogeley, K. (2018). Disturbed experience of time in depression—evidence from content analysis. Frontiers in Human Neuroscience, 12(February), 1–10. https://doi.org/10.3389/fnhum.2018.00066

Wahl, O. F., & Sieg, D. (1980). Time estimation among schizophrenics. Perceptual and Motor Skills, 50(2), 535–541. https://doi.org/10.2466/pms.1980.50.2.535

Weissenstein, A., Luchter, E., & Stefan Bittmann, M. A. (2014). Alice in Wonderland syndrome: A rare neurological manifestation with microscopy in a 6-year-old child. Journal of Pediatric Neurosciences. https://doi.org/10.4103/1817-1745.147612

Yokoyama, T., Okamura, T., Takahashi, M., Momose, T., & Kondo, S. (2017). A case of recurrent depressive disorder presenting with Alice in Wonderland syndrome: Psychopathology and pre- and post-treatment FDG-PET findings. BMC Psychiatry, 17(1), 4–9. https://doi.org/10.1186/s12888-017-1314-2

Zakay, D. (2014). Psychological time as information: the case of boredom. Frontiers in Psychology, 5(AUG), 917. https://doi.org/10.3389/fpsyg.2014.00917


Better Research Practices: Own Your Research Decisions 

— Original Piece

Image reference:

An instance of Open Science principles. This specific set of principles guides the Open Traits Network — a global initiative for sharing and integrating trait data across organisms. Adapted with permission from “Open Science principles for accelerating trait-based science across the Tree of Life,” by Gallagher, R. V., Falster, D. S., Maitner, B. et al., 2020, Nature ecology & evolution, 4(3), 294-303.




Azar, B. (2010, May). Are your findings ‘WEIRD’?. Monitor on Psychology, APA. https://www.apa.org/monitor/2010/05/weird 

Benedictus, R., Miedema, F., & Ferguson, M. W. (2016). Fewer numbers, better science. Nature, 538(7626), 453-455.

Berezow, A. (2012, July 13). Why psychology isn’t science. LA Times. https://www.latimes.com/opinion/la-xpm-2012-jul-13-la-ol-blowback-pscyhology-science-20120713-story.html

Borsboom, D. (2013, November 20). Theoretical amnesia. Open Science Collaboration Blog. http://osc.centerforopenscience.org/2013/11/20/theoretical-amnesia/

Carney, D. R., Cuddy, A. J., & Yap, A. J. (2010). Power posing: Brief nonverbal displays affect neuroendocrine levels and risk tolerance. Psychological science, 21(10), 1363-1368.

Carter, E. C., & McCullough, M. E. (2014). Publication bias and the limited strength model of self-control: has the evidence for ego depletion been overestimated?. Frontiers in psychology, 5, 823.

Dikker, S., Wan, L., Davidesco, I., Kaggen, L., Oostrik, M., McClintock, J., … & Poeppel, D. (2017). Brain-to-brain synchrony tracks real-world dynamic group interactions in the classroom. Current Biology, 27(9), 1375-1380.

Extreme Citizen Science (ExCiteS). (2020). UCL Department of Geography. https://www.geog.ucl.ac.uk/research/research-centres/excites

Gallagher, R., Falster, D., Maitner, B., Salguero-Gomez, R., Vandvik, V., Pearse, W., … & Andrew, S. (2019). The open traits network: Using open science principles to accelerate trait-based science across the tree of life.

Gerber, A. (2014). Science caught flat-footed: how academia struggles with open science communication. In Opening Science (pp. 73-80). Springer, Cham.

Gueren, C. (2015, January 8) This Is What An Orgasm Does To Your Brain. Buzzfeed.https://www.buzzfeed.com/caseygueren/your-brain-on-sex

Guest, O., & Martin, A. E. (2020). How computational modeling can force theory building in psychological science.

Gura, T. (2013). Citizen science: amateur experts. Nature, 496(7444), 259-261.

Hagger, M. S., Wood, C., Stiff, C., & Chatzisarantis, N. L. (2010). Ego depletion and the strength model of self-control: a meta-analysis. Psychological bulletin, 136(4), 495.

Hagger, M. S., Chatzisarantis, N. L., Alberts, H., Anggono, C. O., Batailler, C., Birt, A. R., … & Calvillo, D. P. (2016). A multilab preregistered replication of the ego-depletion effect. Perspectives on Psychological Science, 11(4), 546-573.

Job, V., Dweck, C. S., & Walton, G. M. (2010). Ego depletion—Is it all in your head? Implicit theories about willpower affect self-regulation. Psychological science, 21(11), 1686-1693.

Jogalekar, A. (2013, August 13). Is psychology a “real” science? Does it really matter?. Scientific American.https://blogs.scientificamerican.com/the-curious-wavefunction/is-psychology-a-e2809creale2809d-science-does-it-really-matter/

Kenens, J., Van Oudheusden, M., Yoshizawa, G., & Van Hoyweghen, I. (2020). Science by, with and for citizens: rethinking ‘citizen science’ after the 2011 Fukushima disaster. Palgrave Communications, 6(1), 1-8.

Keshavan, A., Yeatman, J. D., & Rokem, A. (2019). Combining citizen science and deep learning to amplify expertise in neuroimaging. Frontiers in neuroinformatics, 13, 29.

Lee, M. D., Criss, A. H., Devezer, B., Donkin, C., Etz, A., Leite, F. P., … & Vandekerckhove, J. (2019). Robust modeling in cognitive science. Computational Brain & Behavior, 2(3-4), 141-153.

Oberauer, K., & Lewandowsky, S. (2019). Addressing the theory crisis in psychology. Psychonomic bulletin & review, 26(5), 1596-1618.

Segall, M. H., Campbell, D. T., & Herskovits, M. J. (1966). The influence of culture on visual perception (p. 32). Indianapolis: Bobbs-Merrill.

Ranehill, E., Dreber, A., Johannesson, M., Leiberg, S., Sul, S., & Weber, R. A. (2015). Assessing the robustness of power posing: No effect on hormones and risk tolerance in a large sample of men and women. Psychological science, 26(5), 653-656.

Ransonhoff D, Ransonhoff R. (2001). Sensationalism in the media: when scientists and journalists may be complicit collaborators.  Eff Clin Pract, (4), 185-188.

Moin, S. (2020, February 27). Stop Talking About “Diversity” in Open Science. Open Science Foundation. https://osf.io/bcmna/ 

The Royal Society. (1985).The public understanding of science, Available at:http://royalsociety.org/policy/publications/1985/public-understanding-science.

Van Rooij, I. (2020). Beyond the Crisis in Psychology. Distinguished Lorentz Fellow talk, Netherlands Institute for Advanced Study in the Humanities and Social Sciences. https://youtu.be/aIqGT0VwVqk

Wright, G., & Sanders, J.  Diversity and inclusion: key for open science. IOP Publishing. https://ioppublishing.org/open-access-week-2019/inclusion-for-open-science/ 

Yong, E. (2012, May 16). Replication studies: Bad copy. Nature News Feature. https://www.nature.com/news/replication-studies-bad-copy-1.10634

Dissociating contributions of periodic and aperiodic neural activity in human visual working memory. 

— Research Project

1 - Supplementary Material

1.1 – Single trial power spectra

Single trial power spectra are in general quite noisy. Especially in this research, since there were limited time points due to the task design. Even though, the model was still able to fit the data with an average error of 0.237 over the participants that exhibit theta power. Furthermore, the error is not significantly different between the baseline period or the retention period, nor between good and poor performance, excluding that this is driving the results. Supplementary figure 1 & 2 show the fit of six single trials from a random participant for the retention period and the baseline period. The top row shows the three worst fit (highest error), and the bottom row the three best fits (lowest error). The error is calculated over the whole frequency range 2 to 40 Hz, and thus is not very informative to determine whether the model was able to capture a peak in the theta frequency range (4 – 7 Hz), since the theta frequency range is such a small portion of the whole frequency range. This becomes clear when comparing the top and bottom rows (supplementary figure 1 & 2).

Supplementary figure 1: Six single trials of good performance during the baseline period. These six single trials are from one random participant. The top row are the three worst fits, and in the bottom row are the three best fits. The black line is the single trial power spectrum. The blue line is the aperiodic fit and in red is the full model fit.

Supplementary figure 2: Six single trials of good performance during the retention period. These six single trials are from one random participant. The top row are the three worst fits, and in the bottom row are the three best fits. The black line is the single trial power spectrum. The blue line is the aperiodic fit and in red is the full model fit.

1.2 – Theta frequency ranges

As stated in the discussion (section 4.3), theta power has been described in a variety of different frequency ranges (Adam et al., 2015, 2018; Brzezicka et al., 2015; Jensen & Tesche, 2002). Using a frequency range from 4 to 7 Hz for finding peaks with FOOOF has a harder cut-off frequency than when using a band width filter with the same range. Because filters will pick up power from neighboring frequencies as well, whereas this is not the case with FOOOF. When using a range of 4 to 7 Hz with FOOOF, there was no significant difference in relative theta power between good and poor performance. However, expanding the theta range 1 Hz (4 – 8 Hz) gives different results (supplementary figure 3). Here, the relative power is higher for good performance, compared to poor performance (W = 122, p = 0.031, d = 0.595). Also, relative power is significantly increased from baseline during good performance (t(16) = 2.549, p = 0.021, d = 0.618), but not during poor performance. Thus, it seems most of the theta activity that explains behavior is in the higher frequencies within that range. So perhaps it would be better to define a frequency band based on the data (Jensen & Tesche, 2002).

Supplementary figure 3: Theta power measured between 4 and 8 Hz predicts performance. Participants in this group all exhibited some degree of theta power. A) Power spectra of the baseline period and good and poor performance during the retention period. B) Relative theta power is significantly increased compared to baseline. And is significantly higher than during poor performance.


Adam, K. C. S., Mance, I., Fukuda, K., & Vogel, E. K. (2015). The Contribution of Attentional Lapses to Individual Differences in Visual Working Memory Capacity. Journal of Cognitive Neuroscience, 27(8), 1601–1616. https://doi.org/10.1162/jocn

Adam, K. C. S., Robison, M. K., & Vogel, E. K. (2018). Contralateral Delay Activity Tracks Fluctuations in Working Memory Performance. Journal of Cognitive Neuroscience, 1–12. https://doi.org/10.1162/jocn_a_01233

Bender, M., Romei, V., & Sauseng, P. (2019). Slow Theta tACS of the Right Parietal Cortex Enhances Contralateral Visual Working Memory Capacity. Brain Topography, 32(3), 477–481. https://doi.org/10.1007/s10548-019-00702-2

Berger, H. (1929). Uber das Elektrenkephalogramm des Menschen. 278(1875).

Brzezicka, A., Kami, J., Reed, C. M., Chung, J. M., Mamelak, A. N., & Rutishauser, U. (2015). Working Memory Load-related Theta Power Decreases in Dorsolateral Prefrontal Cortex Predict Individual Differences in Performance. 1–18. https://doi.org/10.1162/jocn

Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012). The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes. Nat Rev Neurosci., 13(6), 407–420. https://doi.org/10.1038/nrn3241.The

Cole, S., Donoghue, T., Gao, R., & Voytek, B. (2019). NeuroDSP : A package for neural digital signal processing. 4, 2018–2020. https://doi.org/10.1101/302000

Colombo, M. A., Napolitani, M., Boly, M., Gosseries, O., Casarotto, S., Rosanova, M., … Sarasso, S. (2019). NeuroImage The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol , xenon , and ketamine. NeuroImage, 189(December 2018), 631–644. https://doi.org/10.1016/j.neuroimage.2019.01.024

Dave, S., Brothers, T. A., & Swaab, T. Y. (2018). 1 / f neural noise and electrophysiological indices of contextual prediction in aging. Brain Research, 1691, 34–43. https://doi.org/10.1016/j.brainres.2018.04.007

Frey, J. N., Ruhnau, P., & Weisz, N. (2015). Not so different after all : The same oscillatory processes support different types of attention. 1626, 183–197. https://doi.org/10.1016/j.brainres.2015.02.017

Gao, R. D., Peterson, E. J., & Voytek, B. (2017). Inferring Synaptic Excitation/Inhibition Balance from Field Potentials. BioRxiv, 1–31. http://dx.doi.org/10.1101/081125

Haller, M., Donoghue, T., Peterson, E., Varma, P., & Sebastian, P. (2018). Parameterizing neural power spectra. BioRxiv. http://dx.doi.org/10.1101/299859

He, B. J. (2015). Scale-free brain activity: past, present and future Biyu. Trends Cogn Sci., 18(9), 480–487. https://doi.org/10.1016/j.tics.2014.04.003.Scale-free

Herrmann, C. S., Strüber, D., Helfrich, R. F., & Engel, A. K. (2016). EEG oscillations : From correlation to causality. International Journal of Psychophysiology, 103, 12–21. https://doi.org/10.1016/j.ijpsycho.2015.02.003

JASP Team (2018). (Version[Computer software]

Jensen, O., & Tesche, C. D. (2002). Frontal theta activity in humans increases with memory load in a working memory task: Frontal theta increases with memory load. European Journal of Neuroscience, 15(8), 1395–1399. https://doi.org/10.1046/j.1460-9568.2002.01975.x

Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance : a review and analysis. Brain Research Reviews, 29, 169–195.

Leemburg, S., Gao, B., Cam, E., Sarnthein, J., & Bassetti, C. L. (2018). Power spectrum slope is related to motor function after focal cerebral ischemia in the rat. (August), 1–12. https://doi.org/10.1093/sleep/zsy132

Lombardi, F., Herrmann, H. J., & de Arcangelis, L. (2017). Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(4), 047402. https://doi.org/10.1063/1.4979043

Peterson, E. J., Rosen, B. Q., Campbell, A. M., Belger, A., & Voytek, B. (2017). 1 / f neural noise is a better predictor of schizophrenia than neural oscillations. BioRxiv. http://dx.doi.org/10.1101/113449

Pritchard, W. S. (1992). The Brain in Fractal Time : 1 / F-Like Power Spectrum Scaling of the Human Electroencephalogram. International Journal of Neuroscience, 1–2(66). https://doi.org/10.3109/00207459208999796

Roberts, J. A., Boonstra, T. W., & Breakspear, M. (2015). The heavy tail of the human brain. Current Opinion in Neurobiology, 31, 164–172. https://doi.org/10.1016/j.conb.2014.10.014

Sadaghiani, S., & Kleinschmidt, A. (2016). Brain Networks and α-Oscillations: Structural and Functional Foundations of Cognitive Control. Trends in Cognitive Sciences, 20(11), 805–817. https://doi.org/10.1016/j.tics.2016.09.004

Vogel, E. K., & Machizawa, M. G. (2004). Neural activity predicts individual differences in visual working memory Neural activity predicts individual differences in visual working memory capacity. Letters to Nature, 428(June), 748–751. https://doi.org/10.1038/nature02447

Voytek, X. B., Kramer, M. A., Case, J., Lepage, K. Q., Tempesta, Z. R., Knight, R. T., & Gazzaley, A. (2015). Age-Related Changes in 1 / f Neural Electrophysiological Noise. The Journal of Neuroscience, 35(38), 13257–13265. https://doi.org/10.1523/JNEUROSCI.2332-14.2015

Waschke, L., Wöstmann, M., & Obleser, J. (2017). States and traits of neural irregularity in the age-varying human brain. Scientific Reports, 7(1), 17381. https://doi.org/10.1038/s41598-017-17766-4

Wen, H., & Liu, Z. (2016). Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal. Brain Topography, 29(1), 13–26. https://doi.org/10.1007/s10548-015-0448-0

Issue 10

Structural Magnetic Resonance Imaging (MRI) and neuropsychological correlates in an elderly non-Western immigrant population 

— Research Project

Alzheimer’s Association (2014). Alzheimer’s Association Report: 2014 Alzheimers disease facts and figures. Alzheimer’s Dement, 14;10(2), 47-92. 

Katz, M. J., Lipton, R. B., Hall, C. B., Zimmerman, M. E., Sanders, A. E., Verghese, J., Dickson, D.W., & Derby, C. A. (2012). Age and sex specific prevalence and incidence of mild cognitive impairment, dementia and Alzheimer’s dementia in blacks and whites: A report from the Einstein Aging Study. Alzheimer disease and associated disorders, 26(4), 335. 

Adelman, S., Blanchard, M., Rait, G., Leavey, G., & Livingston, G. (2011). Prevalence of dementia in African–Caribbean compared with UK-born White older people: two-stage cross-sectional study. The British Journal of Psychiatry, 199(2), 119-125. 

Livingston, G., Leavey, G., Kitchen, G., Manela, M., Sembhi, S., & Katona, C. (2001). Mental health of migrant elders—the Islington study. The British Journal of Psychiatry, 179(4), 361-366. 

Parlevliet, J. L., Uysal‐Bozkir, Ö., Goudsmit, M., Campen, J. P., Kok, R. M., Riet, G., … & Rooij, S. E. (2016). Prevalence of mild cognitive impairment and dementia in older non‐western immigrants in the Netherlands: a cross‐sectional study. International journal of geriatric psychiatry, 31(9), 1040-1049. 

Goudsmit, M., Uysal-Bozkir, Ö., Parlevliet, J. L., van Campen, J. P., de Rooij, S. E., & Schmand, B. (2017). The Cross-Cultural Dementia Screening (CCD): A new neuropsychological screening instrument for dementia in elderly immigrants. Journal of clinical and experimental neuropsychology, 39(2), 163-172. 

Uitewaal, P. J. M., Manna, D. R., Bruijnzeels, M. A., Hoes, A. W., & Thomas, S. (2004). Prevalence of type 2 diabetes mellitus, other cardiovascular risk factors, and cardiovascular disease in Turkish and Moroccan immigrants in North West Europe: a systematic review. Preventive medicine, 39(6), 1068-1076. 

Ardila, A. (2005). Cultural values underlying psychometric cognitive testing. Neuropsychology review, 15(4), 185.

Zahodne, B. L., Manly J., Narkhede, A., Griffith, E. Y., DeCarli, C., Schupf, S. N., Mayeux, R. & Brickman, A. M. (2015). Structural MRI predictors of late-life cognition differ across African Americans, Hispanics, and Whites. Current Alzheimer Research, 12(7), 632-639. 

Jack Jr, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., … & Trojanowski, J. Q. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. The Lancet Neurology, 9(1), 119-128. 

Mungas, D., Reed, B. R., Farias, S. T., & DeCarli, C. (2009). Age and education effects on relationships of cognitive test scores with brain structure in demographically diverse older persons. Psychology and aging, 24(1), 116. 

ADNI Demographic Report. 2012 Retrieved from http://adni.loni.usc.edu/wp- content/uploads/ 2012/08/ADNI_Enroll_Demographics.pdf. 

Bindraban, N. R., van Valkengoed, I. G., Mairuhu, G., Holleman, F., Hoekstra, J. B., Michels, B. P., Koopmans, R.P., & Stronks, K. (2008). Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study. BMC public health, 8(1), 271. 

Agyemang, C., van Oeffelen, A. A., Norredam, M., Kappelle, L. J., Klijn, C. J., Bots, M.      L., Stronks K., & Vaartjes, I. (2014). Socioeconomic inequalities in stroke incidence among migrant groups: analysis of nationwide data. Stroke, 45(8), 2397-2403. 

Agyemang, C., Bindraban, N., Mairuhu, G., Van Montfrans, G., Koopmans, R., & Stronks, K. (2005). Prevalence, awareness, treatment, and control of hypertension among Black Surinamese, South Asian Surinamese and White Dutch in Amsterdam, The Netherlands: The SUNSET study. J Hypertens, 23(11), 1971-1977. 

Sahota, A., Yang, M., Gao, S., Hui, S. L., Baiyewu, O., Gureje, O., … & Hendrie, H. C. (1997). Apolipoprotein E—associated risk for Alzheimer’s disease in the African‐American population is genotype dependent. Annals of neurology, 42(4), 659- 661. 

Farrer, L. A., Cupples, L. A., Haines, J. L., Hyman, B., Kukull, W. A., Mayeux, R., … & Van Duijn, C. M. (1997). Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease: a meta-analysis. Jama, 278(16), 1349- 1356. 

El Kadmiri, N., Zaid, Y., Hamzi, K., Nadifi, S., Slassi, I., & El Moutawakil, B. (2014). Présentation clinique de cas marocains atteints de la maladie d’Alzheimer. L’Encéphale, 40(6), 481-486. 

Brickman, A. M., Schupf, N., Manly, J. J., Luchsinger, J. A., Andrews, H., Tang, M. X., … & Brown, T. R. (2008). Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan. Archives of neurology, 65(8), 1053-1061. 

Van der Wurff, F. B., Beekman, A. T. F., Dijkshoorn, H., Spijker, J. A., Smits, C. H. M., Stek, M. L., & Verhoeff, A. (2004). Prevalence and risk-factors for depression in elderly Turkish and Moroccan migrants in the Netherlands. Journal of affective disorders, 83(1), 33-41. 

Goudsmit, M., Uysal-Bozkir, Ö., Parlevliet, J. L., van Campen, J. P., de Rooij, S. E., & Schmand, B. (2017). The Cross-Cultural Dementia Screening (CCD): A new neuropsychological screening instrument for dementia in elderly immigrants. Journal of clinical and experimental neuropsychology, 39(2), 163-172. 

Storey, J. E., Rowland, J. T., Conforti, D. A., & Dickson, H. G. (2004). The Rowland universal dementia assessment scale (RUDAS): a multicultural cognitive assessment scale. International Psychogeriatrics, 16(1), 13-31. 

Bestuursdienst Den Haag. Stadsenquête Den Haag 2003. Doelgroepenmonitor. Den Haag Bestuursd Den Haag/Grote Steden Beleid. 2003; (september). 

Pasquier, F., Leys, D., Weerts, J. G., Mounier-Vehier, F., Barkhof, F., & Scheltens, P. (1996). Inter-and intraobserver reproducibility of cerebral atrophy assessment on MRI scans with hemispheric infarcts. European neurology, 36(5), 268-272. 

Scheltens, P. H., Leys, D., Barkhof, F., Huglo, D., Weinstein, H. C., Vermersch, P., … & Valk, J. (1992). Atrophy of medial temporal lobes on MRI in” probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. Journal of Neurology, Neurosurgery & Psychiatry, 55(10), 967-972. 

Fazekas, F., Chawluk, J. B., Alavi, A., Hurtig, H. I., & Zimmerman, R. A. (1987). MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. American journal of roentgenology, 149(2), 351-356. 

Koedam, E. L., Lehmann, M., van der Flier, W. M., Scheltens, P., Pijnenburg, Y. A., Fox, N., Barkhof, F., & Wattjes, M. P. (2011). Visual assessment of posterior atrophy development of a MRI rating scale. European radiology, 21(12), 2618-2625. 

Harper, L., Barkhof, F., Fox, N. C., & Schott, J. M. (2015). Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales. J Neurol Neurosurg Psychiatry, jnnp-2014. 

Ferreira, D., Cavallin, L., Larsson, E. M., Muehlboeck, J. S., Mecocci, P., Vellas, B., … & Simmons, A. (2015). Practical cut‐offs for visual rating scales of medial temporal, frontal and posterior atrophy in A lzheimer’s disease and mild cognitive impairment. Journal of internal medicine, 278(3), 277-290. 

van der Flier, W. M., van Straaten, E. C. W., Barkhof, F., Ferro, J. M., Pantoni, L., Basile, A. M., … & Schmidt, R. (2005). Medial temporal lobe atrophy and white matter hyperintensities are associated with mild cognitive deficits in non-disabled elderly people: the LADIS study. Journal of Neurology, Neurosurgery & Psychiatry, 76(11), 1497-1500. 

Frisoni, G. B., Fox, N. C., Jack Jr, C. R., Scheltens, P., & Thompson, P. M. (2010). The clinical use of structural MRI in Alzheimer disease. Nature Reviews Neurology, 6(2), 67. 

O’Brien, J. T., Paling, S., Barber, R., Williams, E. D., Ballard, C., McKeith, I. G., … & Fox, N. C. (2001). Progressive brain atrophy on serial MRI in dementia with Lewy bodies, AD, and vascular dementia. Neurology, 56(10), 1386-1388. 

Breteler, M. M., van Amerongen, N. M., van Swieten, J. C., Claus, J. J., Grobbee, D. E., van Gijn, J., … & van Harskamp, F. (1994). Cognitive correlates of ventricular enlargement and cerebral white matter lesions on magnetic resonance imaging. The Rotterdam Study. Stroke, 25(6), 1109-1115. 

Fox, N. C., Scahill, R. I., Crum, W. R., & Rossor, M. N. (1999). Correlation between rates of brain atrophy and cognitive decline in AD. Neurology, 52(8), 1687-1687. 

Prins, N. D., van Dijk, E. J., den Heijer, T., Vermeer, S. E., Jolles, J., Koudstaal, P. J., … & Breteler, M. M. (2005). Cerebral small-vessel disease and decline in information processing speed, executive function and memory. Brain, 128(9), 2034-2041. 

Fein, G., Di Sclafani, V., Tanabe, J., Cardenas, V., Weiner, M. W., Jagust, W. J., … &  Greenfield, T. (2000). Hippocampal and cortical atrophy predict dementia in subcortical ischemic vascular disease. Neurology, 55(11), 1626-1635. 

Jokinen, H., Kalska, H., Mäntylä, R., Ylikoski, R., Hietanen, M., Pohjasvaara, T., … & Erkinjuntti, T. (2005). White matter hyperintensities as a predictor of neuropsychological deficits post-stroke. Journal of Neurology, Neurosurgery & Psychiatry, 76(9), 1229-1233. 

Shim, Y. S., Youn, Y. C., Na, D. L., Kim, S. Y., Cheong, H. K., Moon, S. Y., … & Kang, H. (2011). Effects of medial temporal atrophy and white matter hyperintensities on the cognitive functions in patients with Alzheimer’s disease. European neurology, 66(2), 75- 82. 

Rami, L., Solé‐Padullés, C., Fortea, J., Bosch, B., Lladó, A., Antonell, A., … & Molinuevo, J. L. (2012). Applying the new research diagnostic criteria: MRI findings and neuropsychological correlations of prodromal AD. International journal of geriatric psychiatry, 27(2), 127-134. 

Pantel, J., Schönknecht, P., Essig, M., & Schröder, J. (2004). Distribution of cerebral atrophy assessed by magnetic resonance imaging reflects patterns of neuropsychological deficits in Alzheimer’s dementia. Neuroscience letters, 361(1-3), 17-20. 

Mielke, M. M., Okonkwo, O. C., Oishi, K., Mori, S., Tighe, S., Miller, M. I., … & Lyketsos, C. G. (2012). Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association, 8(2), 105-113. 

Goos, J. D., Kester, M. I., Barkhof, F., Klein, M., Blankenstein, M. A., Scheltens, P., &  van der Flier, W. M. (2009). Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition. Stroke, 40(11), 3455-3460. 

Zhang H, Sachdev PS, Wen W, et al. Neuroanatomical Correlates of Cognitive Performance in Late Life. Dement Geriatr Cogn Disord. 2011;32:216-226. doi:10.1159/000333372. 

Kloppenborg R. P., Nederkoorn P. J., Geerlings M. I., & van den Berg E. (2014). Presence and progression of white matter hyperintensities and cognition. Neurology, 82, 2127-2138. 

Papp, K. V., Kaplan, R. F., Springate, B., Moscufo, N., Wakefield, D. B., Guttmann, C. R., & Wolfson, L. (2014). Processing speed in normal aging: Effects of white matter hyperintensities and hippocampal volume loss. Aging, Neuropsychology, and Cognition, 21(2), 197-213. 

Smith, E. E., Salat, D. H., Jeng, J., McCreary, C. R., Fischl, B., Schmahmann, J. D., … & Greenberg, S. M. (2011). Correlations between MRI white matter lesion location and executive function and episodic memory. Neurology, 76(17), 1492-1499. 

Gorelick, P. B., Scuteri, A., Black, S. E., DeCarli, C., Greenberg, S. M., Iadecola, C., … & Petersen, R. C. (2011). Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 42(9), 2672-2713. 

Lehmann, M., Koedam, E. L., Barnes, J., Bartlett, J. W., Ryan, N. S., Pijnenburg, Y. A., … & Fox, N. C. (2012). Posterior cerebral atrophy in the absence of medial temporal lobe atrophy in pathologically-confirmed Alzheimer’s disease. Neurobiology of aging, 33(3), 627-e1. 

Smits, L. L., Tijms, B. M., Benedictus, M. R., Koedam, E. L., Koene, T., Reuling, I. E., … & van der Flier, W. M. (2014). Regional atrophy is associated with impairment in distinct cognitive domains in Alzheimer’s disease. Alzheimer’s & Dementia, 10(5), S299-S305. 

Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., … & Snyder, P. J. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association, 7(3), 270-279. 

McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., … & Mohs, R. C. (2011). The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association, 7(3), 263-269. 

Román, G. C., Tatemichi, T. K., Erkinjuntti, T., Cummings, J. L., Masdeu, J. C., Garcia, J. A., … & Moody, D. M. (1993). Vascular dementia Diagnostic criteria for research studies: report of the NINDS‐AIREN International Workshop. Neurology, 43(2), 250-250. 

Verhage F. Intelligence and Age; Research among the Dutch Aged 12 to 77 [in Dutch]. Assen, the Netherlands: Van Gorcum; 1964. 

Lindeboom, J., Schmand, B., Tulner, L., Walstra, G., & Jonker, C. (2002). Visual association test to detect early dementia of the Alzheimer type. Journal of Neurology, Neurosurgery & Psychiatry, 73(2), 126-133. 

Mulder, J., Bouma, A., & Lindeboom, J. (2012). Amsterdamse Dementie-Screeningstest (ADS-6). Bouma A, Mulder J, Lindeboom J, Schmand B (redactie). Handboek neuropsychologische diagnostiek, 2e druk. Amsterdam: Pearson Assessment and Information, 765-74. 

Wilson, B. A., Alderman, N., Burgess, P. W., Emslie, H., & Evans, J. (1996). Behavioural assessment of the dysexecutive syndrome. Thames Valley Test Company. 

Maring, W., Deelman, B.G. (1999). De Cognitieve Screening Test: kort en lang. Tijdschr Gerontol Geriatr, 30:205-211. 

Sheikh, J.I., & Yesavage, J.A. (1986). Geriatric Depression Scale (GDS) Recent evidence and development of a shorter version. Clin Gerontol, 5(12). 

Ganguli, M., Du, Y., Dodge, H. H., Ratcliff, G. G., & Chang, C. C. H. (2006). Depressive symptoms and cognitive decline in late life: a prospective epidemiological study. Archives of general psychiatry, 63(2), 153-160. 

Möller, C., van der Flier, W. M., Versteeg, A., Benedictus, M. R., Wattjes, M. P., Koedam, E. L., … & Vrenken, H. (2014). Quantitative regional validation of the visual rating scale for posterior cortical atrophy. European radiology, 24(2), 397-404. 

Marazziti, D., Consoli, G., Picchetti, M., Carlini, M., & Faravelli, L. (2010). Cognitive impairment in major depression. European journal of pharmacology, 626(1), 83-86. 

Effective connectivity from the Nucleus accumbens towards the frontal cortex during attentional focus 

— Research Project

Amirkhiabani, G., & Lovegrove, W. J. (1996). Role of eccentricity and size in the global precedence effect. Journal of Experimental Psychology: Human Perception and Performance, 22(6), 1434. 

Anticevic, A., Hu, S., Zhang, S., Savic, A., Billingslea, E., Wasylink, S., … & Bloch, M. H. (2014). Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder. Biological psychiatry, 75(8), 595-605. 

Banaschewski, T., Hollis, C., Oosterlaan, J., Roeyers, H., Rubia, K., Willcutt, E., & Taylor, E. (2005). Towards an understanding of unique and shared pathways in the psychopathophysiology of ADHD. Developmental science, 8(2), 132-140. 

Basso, M. R., Schefft, B. K., Ris, M. D., & Dember, W. N. (1996). Mood and global-local visual processing. Journal of the International Neuropsychological Society, 2(3), 249-255. 

Bouvet, L., Rousset, S., Valdois, S., & Donnadieu, S. (2011). Global precedence effect in audition and vision: Evidence for similar cognitive styles across modalities. Acta psychologica, 138(2), 329-335. 

Bruns, A., Eckhorn, R., Jokeit, H., & Ebner, A. (2000). Amplitude envelope correlation detects coupling among incoherent brain signals. Neuroreport, 11(7), 1509-1514. 

Buschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. science, 315(5820), 1860-1862. 

Chamberlain, S. R., Fineberg, N. A., Blackwell, A. D., Robbins, T. W., & Sahakian, B. J. (2006). Motor inhibition and cognitive flexibility in obsessive-compulsive disorder and trichotillomania. 

Cubillo, A., Halari, R., Smith, A., Taylor, E., & Rubia, K. (2012). A review of fronto-striatal and fronto-cortical brain abnormalities in children and adults with Attention Deficit Hyperactivity Disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attention. cortex, 48(2), 194-215. 

Denys, D., Mantione, M., Figee, M., van den Munckhof, P., Koerselman, F., Westenberg, H., … & Schuurman, R. (2010). Deep brain stimulation of the nucleus accumbens for treatment-refractory obsessive-compulsive disorder. Archives of general psychiatry, 67(10), 1061-1068. 

Feusner, J. D., Moody, T., Hembacher, E., Townsend, J., McKinley, M., Moller, H., & Bookheimer, S. (2010). Abnormalities of visual processing and frontostriatal systems in body dysmorphic disorder. Archives of general psychiatry, 67(2), 197-205. 

Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden the scope of attention and thought‐action repertoires. Cognition & emotion, 19(3), 313-332. 

Gasper, K., & Clore, G. L. (2002). Attending to the big picture: Mood and global versus local processing of visual information. Psychological science, 13(1), 34-40. 

Goto, Y., & Grace, A. A. (2005). Dopaminergic modulation of limbic and cortical drive of nucleus accumbens in goal- directed behavior. Nature neuroscience, 8(6), 805. 

Goto, Y., & Grace, A. A. (2008). Limbic and cortical information processing in the nucleus accumbens. Trends in neurosciences, 31(11), 552-558. 

Göttlich, M., Krämer, U. M., Kordon, A., Hohagen, F., & Zurowski, B. (2014). Decreased limbic and increased fronto‐ parietal connectivity in unmedicated patients with obsessive‐compulsive disorder. Human brain mapping, 35(11), 5617- 5632. 

Harmon-Jones, E., Gable, P., & Price, T. F. (2012). The influence of affective states varying in motivational intensity on cognitive scope. Frontiers in Integrative Neuroscience, 6, 73. 

Helfrich, R. F., Huang, M., Wilson, G., & Knight, R. T. (2017). Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception. Proceedings of the National Academy of Sciences, 114(35), 9457-9462. 

Hyafil, A., Summerfield, C., & Koechlin, E. (2009). Two mechanisms for task switching in the prefrontal cortex. Journal of Neuroscience, 29(16), 5135-5142. 

Kerwin, L., Hovav, S., Hellemann, G., & Feusner, J. D. (2014). Impairment in local and global processing and set- shifting in body dysmorphic disorder. Journal of psychiatric research, 57, 41-50. 

Klanker, M., Feenstra, M., & Denys, D. (2013). Dopaminergic control of cognitive flexibility in humans and animals. Frontiers in neuroscience, 7, 201. 

Lee, A. T., Vogt, D., Rubenstein, J. L., & Sohal, V. S. (2014). A class of GABAergic neurons in the prefrontal cortex sends long-range projections to the nucleus accumbens and elicits acute avoidance behavior. Journal of Neuroscience, 34(35), 11519-11525. 

Leung, R. C., & Zakzanis, K. K. (2014). Brief report: cognitive flexibility in autism spectrum disorders: a quantitative review. Journal of autism and developmental disorders, 44(10), 2628-2645. 

Liu, Y., Bengson, J., Huang, H., Mangun, G. R., & Ding, M. (2014). Top-down modulation of neural activity in anticipatory visual attention: control mechanisms revealed by simultaneous EEG-fMRI. Cerebral cortex, 26(2), 517- 529. 

Lobier, M., Siebenhühner, F., Palva, S., & Palva, J. M. (2014). Phase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions. Neuroimage, 85, 853-872. 

MATLAB and EEGLAB toolbox Release 2014b The MathWorks, Inc., Natick, Massachusetts, United States. 

McAlonan, G. M., Cheung, V., Cheung, C., Suckling, J., Lam, G. Y., Tai, K. S., … & Chua, S. E. (2004). Mapping the brain in autism. A voxel-based MRI study of volumetric differences and intercorrelations in autism. Brain, 128(2), 268- 276. 

McGeorge, A. J., & Faull, R. L. M. (1989). The organization of the projection from the cerebral cortex to the striatum in the rat. Neuroscience, 29(3), 503-537. 

Min, B. K., Kim, S. J., Park, J. Y., & Park, H. J. (2011). Prestimulus top-down reflection of obsessive-compulsive disorder in EEG frontal theta and occipital alpha oscillations. Neuroscience letters, 496(3), 181-185. 

Moritz, S., & Wendt, M. (2006). Processing of local and global visual features in obsessive-compulsive disorder. Journal of the International Neuropsychological Society, 12(4), 566-569. 

Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive psychology, 9(3), 353-383. 

Poirel, N., Pineau, A., & Mellet, E. (2008). What does the nature of the stimuli tell us about the Global Precedence Effect?. Acta psychologica, 127(1), 1-11. 

Rankins, D., Bradshaw, J. L., & Georgiou-Karistianis, N. (2005). Local–global processing in obsessive–compulsive disorder and comorbid Tourette’s syndrome. Brain and cognition, 59(1), 43-51. 

Rinehart, N. J., Bradshaw, J. L., Moss, S. A., Brereton, A. V., & Tonge, B. J. (2000). Atypical interference of local detail on global processing in high-functioning autism and Asperger’s disorder. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 41(6), 769-778. 

Romei, V., Thut, G., Mok, R. M., Schyns, P. G., & Driver, J. (2012). Causal implication by rhythmic transcranial magnetic stimulation of alpha frequency in feature‐based local vs. global attention. European Journal of Neuroscience, 35(6), 968-974. 

Russo, S. J., & Nestler, E. J. (2013). The brain reward circuitry in mood disorders. Nature Reviews Neuroscience, 14(9), 609. 

Sauseng, P., & Klimesch, W. (2008). What does phase information of oscillatory brain activity tell us about cognitive processes?. Neuroscience & Biobehavioral Reviews, 32(5), 1001-1013. 

Schachar, R., Mota, V. L., Logan, G. D., Tannock, R., & Klim, P. (2000). Confirmation of an inhibitory control deficit in attention-deficit/hyperactivity disorder. Journal of abnormal child psychology, 28(3), 227-235. 

Sesack, S. R., & Pickel, V. M. (1992). Prefrontal cortical efferents in the rat synapse on unlabeled neuronal targets of catecholamine terminals in the nucleus accumbens septi and on dopamine neurons in the ventral tegmental area. Journal of Comparative Neurology, 320(2), 145-160. 

Simon, D., Kaufmann, C., Müsch, K., Kischkel, E., & Kathmann, N. (2010). Fronto‐striato‐limbic hyperactivation in obsessive‐compulsive disorder during individually tailored symptom provocation. Psychophysiology, 47(4), 728-738. 

Soref, A., Dar, R., Argov, G., & Meiran, N. (2008). Obsessive–compulsive tendencies are associated with a focused information processing strategy. Behaviour Research and Therapy, 46(12), 1295-1299. 

Stelzel, C., Basten, U., Montag, C., Reuter, M., & Fiebach, C. J. (2010). Frontostriatal involvement in task switching depends on genetic differences in d2 receptor density. Journal of Neuroscience, 30(42), 14205-14212. 

Volberg, G., Kliegl, K., Hanslmayr, S., & Greenlee, M. W. (2009). EEG alpha oscillations in the preparation for global and local processing predict behavioral performance. Human Brain Mapping, 30(7), 2173-2183. 

de Wit, S., Watson, P., Harsay, H. A., Cohen, M. X., van de Vijver, I., & Ridderinkhof, K. R. (2012). Corticostriatal connectivity underlies individual differences in the balance between habitual and goal-directed action control. Journal of Neuroscience, 32(35), 12066-12075. 

Yehene, E., Meiran, N., & Soroker, N. (2008). Basal ganglia play a unique role in task switching within the frontal- subcortical circuits: evidence from patients with focal lesions. Journal of Cognitive Neuroscience, 20(6), 1079-1093. 

Yovel, I., Revelle, W., & Mineka, S. (2005). Who sees trees before forest? The obsessive-compulsive style of visual attention. Psychological science, 16(2), 123-129.

What happens to a troll in daylight? Interpersonal affect regulation and empathic characteristics in internet trolling 

— Research Project

Adam, A. E. (2009). The gender agenda in computer ethics. In K. Himma & H. T. Tavani (Eds.), Handbook of information & computer ethics (pp. 589–619). Hoboken, NJ: John Wiley.

Avenanti, A., Sirigu, A., & Aglioti, S. M. (2010). Racial bias reduces empathic sensorimotor resonance with other-race pain. Current Biology20(11), 1018-1022.

Berger, K. S. (2003). The Developing Person Through Childhood and Adolescence (6th ed.). New York, New York: Worth Publishers.

Buckels, E. E., Trapnell, P. D., Andjelovic, T., & Paulhus, D. L. (2018). Internet Trolling and Everyday Sadism: Parallel Effects on Pain Perception and Moral Judgment. Journal of personality.

Buckels, E. E., Trapnell, P. D., & Paulhus, D. L. (2014). Trolls just want to have fun. Personality and individual Differences67, 97-102.

Calkins, S. D., & Keane, S. P. (2009). Developmental origins of early antisocial behavior. Development and psychopathology21(4), 1095-1109.

Carrillo, M., Migliorati, F., Bruls, R., Han, Y., Heinemans, M., Pruis, I., … & Keysers, C. (2015). Repeated witnessing of conspecifics in pain: effects on emotional contagion. PloS one10(9)

Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. Journal of Personality and Social Psychology, 44(1), 113-126.

De Vignemont, F., & Singer, T. (2006). The empathic brain: how, when and why?. Trends in cognitive sciences10(10), 435-441.

Decety, J., Bartal, I. B., Uzefovsky, F., & Knafo-Noam, A. (2016). Empathy as a driver of prosocial behaviour: highly conserved neurobehavioural mechanisms across species. Philosophical transactions of the Royal Society of London. Series B, Biological sciences371(1686), 20150077.

Decety, J., & Lamm, C. (2006). Human empathy through the lens of social neuroscience. The scientific World journal6, 1146-1163.

Dynel, M. (2016). “Trolling is not stupid”: Internet trolling as the art of deception serving entertainment. Intercultural Pragmatics13(3), 353-381.

Eisenberg, N., & Fabes, R. A. (1990). Empathy: Conceptualization, measurement, and relation to prosocial behavior. Motivation and Emotion14(2), 131-149.

Fichman, P., & Sanfilippo, M. R. (2015). The bad boys and girls of cyberspace: How gender and context impact perception of and reaction to trolling. Social science computer review33(2), 163-180.

Hardaker, C. (2010). Trolling in asynchronous computer-mediated communication: From user discussions to academic definitions. Journal of Politeness Research. Language, Behaviour, Culture, 6(2), pp. 215-242.

Keysers, C., & Gazzola, V. (2009). Expanding the mirror: vicarious activity for actions, emotions, and sensations. Current opinion in neurobiology19(6), 666-671.

Lamm, C., Decety, J., & Singer, T. (2011). Meta-analytic evidence for common and distinct neural networks associated with directly experienced pain and empathy for pain. Neuroimage54(3), 2492-2502.

Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., … & Wolff, S. (2009). A brief history of the Internet. ACM SIGCOMM Computer Communication Review, 39(5), 22-31.

Lockwood, P. L., Apps, M. A., Valton, V., Viding, E., & Roiser, J. P. (2016). Neurocomputational mechanisms of prosocial learning and links to empathy. Proceedings of the National Academy of Sciences113(35), 9763-9768.

Lockwood, P. L., Seara-Cardoso, A., & Viding, E. (2014). Emotion regulation moderates the association between empathy and prosocial behavior. PloS one9(5), e96555.

MacDonald, G., & Leary, M. R. (2005). Why does social exclusion hurt? The relationship between social and physical pain. Psychological bulletin131(2), 202.

Miller, P. A., & Eisenberg, N. (1988). The relation of empathy to aggressive and externalizing/antisocial behavior. Psychological bulletin103(3), 324.

Mitsopoulou, E., & Giovazolias, T. (2015). Personality traits, empathy and bullying behaviour: A meta-analytic approach. Aggression and Violent Behavior, 21, 61–72. 

Niven, K., Totterdell, P., & Holman, D. (2009). A classification of controlled interpersonal affect regulation strategies. Emotion9(4), 498.

Niven, K., Totterdell, P., Stride, C. B., & Holman, D. (2011). Emotion Regulation of Others and Self (EROS): The development and validation of a new individual difference measure. Current Psychology30(1), 53-73.

Phillips, W. (2011). LOLing at tragedy: Facebook trolls, memorial pages and resistance to grief online. First Monday, 16(12), 1–14.

Phillips, W. (2015). This is why we can’t have nice things: Mapping the relationship between online trolling and mainstream culture. Cambridge, MA: MIT Press.

Reidy, D. E., Zeichner, A., & Seibert, L. A. (2011). Unprovoked aggression: Effects of psychopathic traits and sadism. Journal of personality79(1), 75-100.

Sest, N., & March, E. (2017). Constructing the cyber-troll: Psychopathy, sadism, and empathy. Personality and Individual Differences119, 69-72.

Singer, T., & Lamm, C. (2009). The social neuroscience of empathy. Annals of the New York Academy of Sciences1156(1), 81-96.

Singer, T., Seymour, B., O’doherty, J., Kaube, H., Dolan, R. J., & Frith, C. D. (2004). Empathy for pain involves the affective but not sensory components of pain. Science303(5661), 1157-1162.

Suler, J. (2004). The online disinhibition effect. Cyberpsychology & behavior7(3), 321-326.

What are the neuropsychological consequences of complying to the delivery of an order? 

— Research Project

Altemeyer, B. (1981). Right-wing authoritarianism. University of Manitoba press. 

Angst, J., Gamma, A., & Meyer, T. D. (2009). S22-03 Update on recent research with the hypomania checklist HCL-32. European Psychiatry, 24, S118. 

Bandura, A. (2006). Toward a psychology of human agency. Perspectives on psychological science 1 (2), 164-180. 

Caspar, Ioumpa, Keysers, & Gazzola (under revision) Obeying orders reduces vicarious brain activation towards victim’s pain 

Caspar, E. A., Cleeremans, A., & Haggard, P. (2018). Only giving orders? An experimental study of the sense of agency when giving or receiving commands. PloS one, 13(9), e0204027. 

Caspar, E. A., Christensen, J. F., Cleeremans, A., & Haggard, P. (2016). Coercion changes the sense of agency in the human brain. Current biology, 26(5), 585-592. 

Davis, M. H. (1980). A multidimensional approach to individual differences in empathy. JSAS Catalog of Selected Documents in Psychology, 10, 8 

Decety, J., & Lamm, C. (2006). Human empathy through the lens of social neuroscience. The scientific World journal, 6, 1146-1163. 

Dewey, J. A., & Knoblich, G. (2014). Do implicit and explicit measures of the sense of agency measure the same thing?. PloS one , 9 (10), e110118. 

Dunwoody, P. T., & Funke, F. (2016). The Aggression-Submission-Conventionalism Scale: Testing a new three factor measure of authoritarianism. 

Engbert, K., Wohlschläger, A., & Haggard, P. (2008). Who is causing what? The sense of agency is relational and efferent-triggered. Cognition , 107 (2), 693-704. 

Graham, J., Haidt, J., & Nosek, B. (2008). Moral Foundations Questionnaire, MFQ 30 revised in July 2008. Extracted, 8, 2008. 

Haggard, P., Clark, S., & Kalogeras, J. (2002). Voluntary action and conscious awareness. Nature neuroscience, 5(4), 382. 

Herrera, C. D. (2001). Ethics, deception, and ‘those Milgram experiments’. Journal of applied philosophy, 245-256. 

Hesp, C., Steenbeek, H. W., & Van Geert, P. L. (2019). Socio-emotional concern dynamics in a model of real-time dyadic interaction: parent-child play in autism. Frontiers in psychology , 10 , 1635. 

Hinne, M., Gronau, Q. F., van den Bergh, D., & Wagenmakers, E. J. (2019). A conceptual introduction to Bayesian Model Averaging. 

Jones, D. N., & Paulhus, D. L. (2014). Introducing the short dark triad (SD3) a brief measure of dark personality traits. Assessment, 21(1), 28-41. 

Keysers, C., & Gazzola, V. (2014). Hebbian learning and predictive mirror neurons for actions, sensations and emotions. Philosophical Transactions of the Royal Society B: Biological Sciences , 369 (1644), 20130175. 

Lamm, C., & Majdandžić, J. (2015). The role of shared neural activations, mirror neurons, and morality in empathy–A critical comment. Neuroscience Research, 90, 15-24. 

Lee, M. D., & Wagenmakers, E. J. (2014). Bayesian cognitive modeling: A practical course . Cambridge university press. 

Lepron, E., Causse, M., & Farrer, C. (2015). Responsibility and the sense of agency enhance empathy for pain. Proceedings of the Royal Society B: Biological Sciences, 282(1799), 20142288. 

Levenson, M. R., Kiehl, K. A., & Fitzpatrick, C. M. (1995). Assessing psychopathic attributes in a noninstitutionalized population. Journal of personality and social psychology , 68 (1), 151. 

Lockwood, P. L. (2016). The anatomy of empathy: Vicarious experience and disorders of social cognition. Behavioural brain research, 311, 255-266. 

Milgram, S. (1963). Behavioral study of obedience. The Journal of abnormal and social psychology, 67(4), 371. 

Milgram, S. (1974). Obedience to authority: An experimental view. New York: Harper & Row. 

Ortega, A., & Navarrete, G. (2017). Bayesian Hypothesis Testing: An Alternative to Null Hypothesis Significance Testing (NHST) in Psychology and Social Sciences. In Bayesian inference . IntechOpen. 

Poonian, S. K., & Cunnington, R. (2013). Intentional binding in self-made and observed actions. Experimental brain research , 229 (3), 419-427. 

Singer, T., & Lamm, C. (2009). The social neuroscience of empathy. Annals of the New York Academy of Sciences , 1156 (1), 81-96. 

Singer, T., Seymour, B., O’doherty, J., Kaube, H., Dolan, R. J., & Frith, C. D. (2004). Empathy for pain involves the affective but not sensory components of pain. Science, 303(5661), 1157-1162.

And that's the end of the references 🙂