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. https://doi.org/10.1111/cdep.12041

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

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

— Original Piece

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

— Research Project

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Manual: Psychological Assessment Resources, Incorporated.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Female Experience of Autism

— Original Piece

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

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

 

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

 

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

 

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

 

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

 

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

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

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

 

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

 

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

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

 

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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

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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

 

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

 

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

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

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

— Literature Thesis

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

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

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

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

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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 3.2.1.1 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 3.2.1.2 Increase ease and convenience.

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You’re (Not) What They Think You Are The Sense and Nonsense of Personality Tests

— Original Piece

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Issue 11

At the Intersection of Art and Neuroscience 

— Original Piece

Dikker, S., Montgomery, S., & Tunca, S. (2019). Using Synchrony-Based Neurofeedback in Search of Human Connectedness. Brain Art, 161–206. doi:10.1007/978-3-030-14323-7_6

Dikker, Suzanne; Michalareas, Georgios; Oostrik, Matthias; Serafimaki, Amalia; Kahraman, Hasibe Melda; Struiksma, Marijn E.; Poeppel, David (2020). Crowdsourcing neuroscience: inter-brain coupling during face-to-face interactions outside the laboratory. NeuroImage, (), 117436–.doi:10.1016/j.neuroimage.2020.117436

http://www.suzannedikker.net/

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

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

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

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Use of prosody to mark information structure in autistic female and male adults with high-level language ability. 

— Research Article

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Neuroaesthetics: Grounded in Science or Merely Aesthetically Pleasing? 

— Original Piece

Armony, J., & Dolan, R. J. (2002). Modulation of spatial attention by fear-conditioned stimuli: an event-related fMRI study. Neuropsychologia, 40(7), 817–826. https://doi.org/10.1016/s0028-3932(01)00178-6

Capó, M. À., Cela-Conde, C. J., Munar, E., Rosselló, J., & Nadal, M. (2008). Towards a framework for the study of the neural correlates of aesthetic preference. Spatial Vision, 21(3–5), 379–396. https://doi.org/10.1163/156856808784532653

Cela-Conde, C. J., Marty, G., Munar, E., Nadal, M., & Burges, L. (2002). The “Style Scheme” Grounds Perception of Paintings. Perceptual and Motor Skills, 95(1), 91–100. https://doi.org/10.2466/pms.2002.95.1.91

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Painting Hypotheses, Cooking Methods, and Composing Results: A Review on “Proust was a Neuroscientist” 

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Time Distortions: A Review 

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Better Research Practices: Own Your Research Decisions 

— Original Piece

Image reference:

An instance of Open Science principles. This specific set of principles guides the Open Traits Network — a global initiative for sharing and integrating trait data across organisms. Adapted with permission from “Open Science principles for accelerating trait-based science across the Tree of Life,” by Gallagher, R. V., Falster, D. S., Maitner, B. et al., 2020, Nature ecology & evolution, 4(3), 294-303.

 


 

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Dissociating contributions of periodic and aperiodic neural activity in human visual working memory. 

— Research Project

1 - Supplementary Material

1.1 – Single trial power spectra

Single trial power spectra are in general quite noisy. Especially in this research, since there were limited time points due to the task design. Even though, the model was still able to fit the data with an average error of 0.237 over the participants that exhibit theta power. Furthermore, the error is not significantly different between the baseline period or the retention period, nor between good and poor performance, excluding that this is driving the results. Supplementary figure 1 & 2 show the fit of six single trials from a random participant for the retention period and the baseline period. The top row shows the three worst fit (highest error), and the bottom row the three best fits (lowest error). The error is calculated over the whole frequency range 2 to 40 Hz, and thus is not very informative to determine whether the model was able to capture a peak in the theta frequency range (4 – 7 Hz), since the theta frequency range is such a small portion of the whole frequency range. This becomes clear when comparing the top and bottom rows (supplementary figure 1 & 2).

Supplementary figure 1: Six single trials of good performance during the baseline period. These six single trials are from one random participant. The top row are the three worst fits, and in the bottom row are the three best fits. The black line is the single trial power spectrum. The blue line is the aperiodic fit and in red is the full model fit.

Supplementary figure 2: Six single trials of good performance during the retention period. These six single trials are from one random participant. The top row are the three worst fits, and in the bottom row are the three best fits. The black line is the single trial power spectrum. The blue line is the aperiodic fit and in red is the full model fit.

1.2 – Theta frequency ranges

As stated in the discussion (section 4.3), theta power has been described in a variety of different frequency ranges (Adam et al., 2015, 2018; Brzezicka et al., 2015; Jensen & Tesche, 2002). Using a frequency range from 4 to 7 Hz for finding peaks with FOOOF has a harder cut-off frequency than when using a band width filter with the same range. Because filters will pick up power from neighboring frequencies as well, whereas this is not the case with FOOOF. When using a range of 4 to 7 Hz with FOOOF, there was no significant difference in relative theta power between good and poor performance. However, expanding the theta range 1 Hz (4 – 8 Hz) gives different results (supplementary figure 3). Here, the relative power is higher for good performance, compared to poor performance (W = 122, p = 0.031, d = 0.595). Also, relative power is significantly increased from baseline during good performance (t(16) = 2.549, p = 0.021, d = 0.618), but not during poor performance. Thus, it seems most of the theta activity that explains behavior is in the higher frequencies within that range. So perhaps it would be better to define a frequency band based on the data (Jensen & Tesche, 2002).

Supplementary figure 3: Theta power measured between 4 and 8 Hz predicts performance. Participants in this group all exhibited some degree of theta power. A) Power spectra of the baseline period and good and poor performance during the retention period. B) Relative theta power is significantly increased compared to baseline. And is significantly higher than during poor performance.

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Issue 10

Structural Magnetic Resonance Imaging (MRI) and neuropsychological correlates in an elderly non-Western immigrant population 

— Research Project

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Parlevliet, J. L., Uysal‐Bozkir, Ö., Goudsmit, M., Campen, J. P., Kok, R. M., Riet, G., … & Rooij, S. E. (2016). Prevalence of mild cognitive impairment and dementia in older non‐western immigrants in the Netherlands: a cross‐sectional study. International journal of geriatric psychiatry, 31(9), 1040-1049. 

Goudsmit, M., Uysal-Bozkir, Ö., Parlevliet, J. L., van Campen, J. P., de Rooij, S. E., & Schmand, B. (2017). The Cross-Cultural Dementia Screening (CCD): A new neuropsychological screening instrument for dementia in elderly immigrants. Journal of clinical and experimental neuropsychology, 39(2), 163-172. 

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

— Research Project

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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.

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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.

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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.

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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.

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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

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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. 

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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. 

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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. 

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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. 

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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. 

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And that's the end of the references 🙂