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.

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Table of Contents

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

http://www.suzannedikker.net/

http://www.suzannedikker.net/mutualwavemachine#mutualwavemachine

http://www.suzannedikker.net/art-science-education#mwm

https://www.moma.org/learn/moma_learning/marina-abramovic-marina-abramovic-the-artist-is-present-2010/

https://www.oostrik.net/

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

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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

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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

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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

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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

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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

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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

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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.

 


 

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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.

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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

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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. 

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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. 

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Effective connectivity from the Nucleus accumbens towards the frontal cortex during attentional focus 

— Research Project

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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. 

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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. 

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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. 

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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. 

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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. 

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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. 

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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. 

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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. 

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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 🙂