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 12

Is That Child Friends... with a Robot? Taking a Look from hte 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.

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.

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.

COUNCIL ON COMMUNICATIONS AND MEDIA. (2016). Media and Young Minds. Pediatrics, 138(5), e20162591.

Cristia, A., & Seidl, A. (2015). Parental Reports on Touch Screen Use in Early Childhood. PLOS ONE, 10(6), e0128338.

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.

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.

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.

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.

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.

Rideout, V. (2013).  Zero to Eight: Children’s Media Use in America 2013; Common Sense                     Media. Available at:           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.

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.

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.

Strasburger, V. C., Jordan, A. B., & Donnerstein, E. (2012). Children, Adolescents, and the Media: Pediatric Clinics of North America, 59(3), 533–587.

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.

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.

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.

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.

Ferrari, M., Rice, C., & McKenzie, K. (2015). ACE Pathways Project: Therapeutic catharsis in digital storytelling. Psychiatric Services (Washington, DC), 66(5), 556–556.

Given, L. M. (2008). Lived Experience. In The SAGE Encyclopedia of Qualitative Research Methods. SAGE Publications, Inc.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.                                                

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


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),


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-


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.

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.

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.

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.

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.


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.

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.

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-


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.

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.

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),


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.


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-


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

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.

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

Economic Perspectives, 30(3), 133-140.

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.

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.

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.

Hanss, D., &, 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

Hanss, D., &, 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.

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.

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.

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.

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.

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.

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.


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

[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.

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.

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–


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.

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.

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),


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.

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-


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,


Van Strien, T., & Koenders, P. G. (2012). How do life style factors relate to general health

and overweight? Appetite, 58(1), 265-270.

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.


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.

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.

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.

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),


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.

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.

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.


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.


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.


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.


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.


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.<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.


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.


Edwards, D. A., Whalen, R. E., & Nadler, R. D. (1968). Induction of estrus: Estrogen-progesterone interactions. Physiology & Behavior, 3(1), 29–33.


Ertman, N., Andreano, J. M., & Cahill, L. (2011). Progesterone at encoding predicts subsequent emotional memory. Learning & Memory, 18(12), 759–763.


Fanselow, M. S., & Dong, H.-W. (2010). Are the Dorsal and Ventral Hippocampus Functionally Distinct Structures? Neuron, 65(1), 7–19.


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.


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.


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.


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.


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.


Goldstein, J. M. (2005). Hormonal Cycle Modulates Arousal Circuitry in Women Using Functional Magnetic Resonance Imaging. Journal of Neuroscience, 25(40), 9309–9316.


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.


LeDoux, J. E. (1993). Emotional memory systems in the brain. Behavioural Brain Research, 58(1), 69–79.


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.


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.


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.


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.


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.


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.


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.


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.


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.


Pletzer, B. (2019). Sex Hormones and Gender Role Relate to Gray Matter Volumes in Sexually Dimorphic Brain Areas. Frontiers in Neuroscience, 13, 592.


Pletzer, B., Harris, T., & Hidalgo-Lopez, E. (2018). Subcortical structural changes along the menstrual cycle: Beyond the hippocampus. Scientific Reports, 8(1), 16042.


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.


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.


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.


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.


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.


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.


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.


Sitruk-Ware, R. (2006). New progestagens for contraceptive use. Human Reproduction Update, 12(2), 169–178.


Skovlund, C. W., Mørch, L. S., Kessing, L. V., & Lidegaard, Ø. (2016). Association of Hormonal Contraception With Depression. JAMA Psychiatry, 73(11), 1154–1162.


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.


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.

United Nations. (2019). Contraceptive Use by Method 2019: Data Booklet. UN.


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. 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.


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.

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:

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:

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:

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:

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:

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] Available at: 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

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.

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.

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.

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.

 Gallace, A., & Spence, C. (2011). Tactile aesthetics: towards a definition of its characteristics and neural correlates. Social Semiotics, 21(4), 569–589.

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.

Kawabata, H., & Zeki, S. (2004). Neural Correlates of Beauty. Journal of Neurophysiology, 91(4), 1699–1705.

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.

Monet, C. (1900). The Artist’s Garden at Giverny [Painting].[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.

The neurobiology of beauty | Semir Zeki | TEDxUCL. (2012, July 2). [Video]. YouTube.

Zeki, S., & Chén, O. Y. (2020). The Bayesian‐Laplacian brain. European Journal of Neuroscience, 51(6), 1441–1462.

Zeki, S., Chén, O. Y., & Romaya, J. P. (2018). The Biological Basis of Mathematical Beauty. Frontiers in Human Neuroscience, 12, 23–50.

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.

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.

Allman, M. J., & Meck, W. H. (2012). Pathophysiological distortions in time perception and timed performance. Brain, 135(3), 656–677.

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.

Blom, J. D. (2016). Alice in Wonderland syndrome A systematic review. Neurology: Clinical Practice. Lippincott Williams and Wilkins.

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.

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.

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.

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.

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.

Freedman, B. J. (1974). The Subjective Experience of Perceptual and Cognitive Disturbances in Schizophrenia. Archives of General Psychiatry, 30(3), 333.

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.

Ghaemi, S. N. (2007). Feeling and time: The phenomenology of mood disorders, depressive realism, and existential psychotherapy. Schizophrenia Bulletin, 33(1), 122–130.

Gibbon, J., Church, R. M., & Meck, W. H. (1984). Scalar Timing in Memory. Annals of the New York Academy of Sciences.

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.

Jones, C. R. G., & Jahanshahi, M. (2011). Dopamine Modulates Striato-Frontal Functioning during Temporal Processing. Frontiers in Integrative Neuroscience, 5, 70.

Kitamura, T., & Kumar, R. (1982). Time passes slowly for patients with depressive state. Acta Psychiatrica Scandinavica, 65(6), 415–420.

Kuhs, H. (1991). Time experience in melancholia: A comparison between findings based on phenomenology and experimental psychology. Comprehensive Psychiatry, 32(4), 324–329.

Lake, J. I. (2016). Recent advances in understanding emotion-driven temporal distortions. Current Opinion in Behavioral Sciences, 8, 214–219.

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.

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.

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.

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.

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.

Perdices, M. (2018). The Alice in Worderland Syndrome. Neuropsychological Rehabilitation, 28(2), 189–198.

Rao, S. M., Mayer, A. R., & Harrington, D. L. (2001). The evolution of brain activation during temporal processing. Nature Neuroscience.

Ratcliffe, M. (2012). Varieties of temporal experience in depression. Journal of Medicine and Philosophy (United Kingdom), 37(2), 114–138.

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.

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.

Shammas, M. K. (2020). The Curious Case of the Fast Feelers: A Reflection on Alice in Wonderland Syndrome. Pediatric Neurology.

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.

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.

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.

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.

Thönes, S., & Oberfeld, D. (2015). Time perception in depression: A meta-analysis. Journal of Affective Disorders, 175, 359–372.

Treisman, M. (1963). Temporal discrimination and the indifference interval. Implications for a model of the “internal clock”. Psychological Monographs.

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.

Tysk, L. (1984b). Time perception and affective disorders. Perceptual and Motor Skills, 58(2), 455–464.

Üstün, S., Kale, E. H., & Çiçek, M. (2017). Neural networks for time perception and working memory. Frontiers in Human Neuroscience.

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.

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.

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.

Wahl, O. F., & Sieg, D. (1980). Time estimation among schizophrenics. Perceptual and Motor Skills, 50(2), 535–541.

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.

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.

Zakay, D. (2014). Psychological time as information: the case of boredom. Frontiers in Psychology, 5(AUG), 917.


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. 

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.

Borsboom, D. (2013, November 20). Theoretical amnesia. Open Science Collaboration Blog.

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.

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.

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.

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. 

The Royal Society. (1985).The public understanding of science, Available at:

Van Rooij, I. (2020). Beyond the Crisis in Psychology. Distinguished Lorentz Fellow talk, Netherlands Institute for Advanced Study in the Humanities and Social Sciences.

Wright, G., & Sanders, J.  Diversity and inclusion: key for open science. IOP Publishing. 

Yong, E. (2012, May 16). Replication studies: Bad copy. Nature News Feature.

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.

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.

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.

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.

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.

Cole, S., Donoghue, T., Gao, R., & Voytek, B. (2019). NeuroDSP : A package for neural digital signal processing. 4, 2018–2020.

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.

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.

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.

Gao, R. D., Peterson, E. J., & Voytek, B. (2017). Inferring Synaptic Excitation/Inhibition Balance from Field Potentials. BioRxiv, 1–31.

Haller, M., Donoghue, T., Peterson, E., Varma, P., & Sebastian, P. (2018). Parameterizing neural power spectra. BioRxiv.

He, B. J. (2015). Scale-free brain activity: past, present and future Biyu. Trends Cogn Sci., 18(9), 480–487.

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.

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.

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.

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.

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.

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).

Roberts, J. A., Boonstra, T. W., & Breakspear, M. (2015). The heavy tail of the human brain. Current Opinion in Neurobiology, 31, 164–172.

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.

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.

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.

Waschke, L., Wöstmann, M., & Obleser, J. (2017). States and traits of neural irregularity in the age-varying human brain. Scientific Reports, 7(1), 17381.

Wen, H., & Liu, Z. (2016). Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal. Brain Topography, 29(1), 13–26.

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 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 🙂