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Predicting Individual Differences in Risk Taking: What Can Affective Neuroscience Add?

Applicant Tisdall Loreen
Number 188172
Funding scheme Early Postdoc.Mobility
Research institution Department of Psychology Stanford University
Institution of higher education Institution abroad - IACH
Main discipline Psychology
Start/End 01.11.2019 - 30.04.2021
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Keywords (8)

Individual differences; Neural markers; Risk taking; Prediction; Basel-Berlin Risk Study; Human Connectome Project; Adolescent Brain Cognitive Development Study; Meta-analysis

Lay Summary (German)

Lead
Die Bereitschaft, Risiken einzugehen, ist ein adaptiver Bestandteil der menschlichen Entwicklung. Da dennoch für das Individuum und die Gesellschaft schwerwiegende negative Konsequenzen durch exzessives Eingehen von Risiken entstehen können, werden individuelle Unterschiede zur Intervention angezielt. Ein Ansatz zur Identifizierung von individuellen Unterschieden in der Risikobereitschaft ist die Untersuchung biologischer Prädiktoren, insbesondere von Gehirnmerkmalen.
Lay summary

Inhalt und Ziele des Forschungsprojekts 
In diesem Projekt wird anhand neuester neurowissenschaftlicher und statistischer Methoden untersucht, inwiefern Gehirnmerkmale als Prädiktoren für individuelle Unterschiede in der Risikobereitschaft genutzt werden können. In einem ersten Teil wird die bereits bestehende neurowissenschaftliche Literatur zum Thema systematisch gesichtet und meta-analytisch zusammengefasst. Hieraus resultiert die Erstellung einer umfassenden Datenbank, die es erlaubt, vorhandene Kenntnisse effizient, nach Kategorien geordnet aufzusuchen und als Basis für weitere Forschung zu nutzen. In einem zweiten Teil wird untersucht, inwiefern Merkmale von strukturellen Verbindungen zwischen Gehirnregionen zur Vorhersage von (unter anderem) Drogenkonsum genutzt werden können. Es werden drei umfangreiche, bereits bestehende Datensets genutzt, um neue empirische Erkenntnisse zur Rolle der Gehirnstruktur für die Risikobereitschaft zu gewinnen.

Wissenschaftlicher und gesellschaftlicher Kontext des Forschungsprojekts 
Wissenschaftlich gibt dieses Projekt neuen Aufschluss über die biologischen Grundlagen menschlicher Risikobereitschaft. Angesichts der weitreichenden individuellen und gesellschaftlichen Implikationen, welche die Nutzung von Gehirnmerkmalen als Prädiktoren von Risikobereitschaft mit sich bringen würde, trägt dieses Projekt dazu bei, dass die Evidenzbasis hierfür umfassend untersucht wird.

Direct link to Lay Summary Last update: 19.07.2019

Responsible applicant and co-applicants

Collaboration

Group / person Country
Types of collaboration
Spanlab (PI: Brian Knutson), Stanford University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Spanlab research colloquium Individual talk DiffRisk: Status update 05.05.2021 online, United States of America Tisdall Loreen;
Spanlab research colloquium Individual talk DiffRisk: Project introduction 03.03.2021 online, United States of America Tisdall Loreen;
Society for Neuroscience Global Connectome Event Poster Structural coherence of white-matter projections to the nucleus accumbens predicts relapse to stimulant drug use in humans 11.01.2021 online; Stanford, United States of America Tisdall Loreen;
Laboratory meeting (Karl Deisseroth group) Individual talk Predicting relapse to stimulant drug use from neural structural data: Status update 04.12.2020 online; Stanford, United States of America Tisdall Loreen;
Affective Seminar Individual talk Predicting relapse to stimulant use from neural data 22.10.2020 online; Stanford, United States of America Tisdall Loreen;
NeuroHealth Poster The structure of white-matter connections from the anterior insula to the nucleus accumbens predicts relapse to stimulant drug use 08.10.2020 online; Stanford, United States of America Tisdall Loreen;
Society for Neuroeconomics (vSNE) Poster Structural properties of frontostriatal fiber tracts are differentially predictive of addiction relapse but not diagnosis 07.10.2020 online; Stanford, United States of America Tisdall Loreen;
Psychology Colloquium Lightning Talk Individual talk Predicting relapse to stimulant use 05.10.2020 online; Stanford, United States of America Tisdall Loreen;
Spanlab research colloquium Individual talk DiffRelapse: Status Update 26.08.2020 online; Stanford, United States of America Tisdall Loreen;
Spanlab research colloquium Individual talk DiffRelapse: Project introduction 01.07.2020 online; Stanford, United States of America Tisdall Loreen;
2020 Interdisciplinary Conference on Humanities, Social Sciences, Medicine, Biology, and Mathematics, Natural & Engineering Sciences Talk given at a conference Predicting individual differences in risk taking: What can affective neuroscience add? 30.06.2020 online; Stanford, United States of America Tisdall Loreen;
Scientific Research Network on Decision Neuroscience and Aging Talk given at a conference Age differences in risk-taking behavior and their neural correlates 09.03.2020 Kapolei, Hawaii, United States of America Tisdall Loreen;


Abstract

Taking risks is an adaptive, developmentally required aspect of human life that can promote happiness and success [1,2]. However, engagement in excessive or maladaptive risk taking can have detrimental effects on individual as well as societal levels of health, wealth and criminality [3-5]. To contain the potential fallout from maladaptive risky behaviors, individual differences in risk taking and related constructs have become attractive targets for intervention [6]. One approach to understanding and, ultimately, predicting individual differences in risk taking has been to illuminate the biological substrates [7], specifically the neural pathways. Neural functional data have indeed been associated with or even found to be predictive of risky behaviors [8-10], yet one fundamental problem of existing studies relates to the challenge of measuring risk taking. As suggested by previous work [11-14], convergence between risk-taking measures is low, both at the level of behavior and neural activation, meaning different risk-taking measures will result in different behavioral and neural profiles for the same person. By extension, whether regional activation differences are mere correlates or actual predictors of risky behaviors is also likely to vary as a function of the measure used. The aim of this project is to comprehensively test the predictive power of neural indices for individual differences in risk taking. Addressing the shortcomings of previous research, the proposed project comprises two main components. Component 1 (MApredict) comprises a systematic literature review and the meta-analytic quantification of the existing evidence for the power of neural functional and structural markers to predict real-world, concrete risk-taking behaviors. Component 2 (STRUCpredict) examines the predictive power of neural structural connectivity for individual differences in risk taking, adopting out-of-task and out-of-sample research methodology. Concretely, STRUCpredict comprises four sequential subcomponents that move from correlation to prediction: 1) the conceptual replication of a promising association between risk preference and the structural coherence of a newly-identified neural white matter fiber tract between the nucleus accumbens and insula [15], 2) examination of the association between trait-like psychometrically derived risk preference factors [13] and coherence in this as well as through theory identified additional tracts, 3) examination of the association between a concrete, real-world risk-taking measure, namely objectively measured substance use, and tract coherence in the young adult sample of the Human Connectome Project, and ultimately 4) prediction of a concrete, real-world risk-taking measure, namely objectively measured substance use, from tract coherence using baseline and follow-up data from the Adolescent Brain Cognitive Development Study. References1.Duell, N., & Steinberg, L. (2018). Positive Risk Taking in Adolescence. Child Development Perspectives, 13(1), 48-52. doi:10.1111/cdep.123102.Fischer, S., & Smith, G. T. (2004). Deliberation affects risk taking beyond sensation seeking. Personality and Individual Differences, 36(3), 527-537. doi:10.1016/S0191-8869(03)00112-03.Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., Houts, R., Poulton, R., Roberts, B.W., Ross, S., Sears, M.R., Thomson, W.M., & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108(7), 2693-2698. doi:10.1073/pnas.10100761084.Steinberg, L. (2013). The influence of neuroscience on US Supreme Court decisions about adolescents’ criminal culpability. Nature Reviews Neuroscience, 14(7), 513-518. doi:10.1038/nrn35095.Williams, M. T. (2010). Uncontrolled Risk: The Lessons of Lehman Brothers and How Systemic Risk Can Still Bring Down the World Financial System. New York: McGraw Hill. 6.Conrod, P. J., O’Leary-Barrett, M., Newton, N., Topper, L., Castellanos-Ryan, N., Mackie, C., & Girard, A. (2013). Effectiveness of a Selective, Personality-Targeted Prevention Program for Adolescent Alcohol Use and Misuse. JAMA Psychiatry, 70(334-342). doi:10.1001/jamapsychiatry.2013.6517.Linnér, R. K., et al. (2019). Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nature Genetics, 51(2), 245-257. doi:10.1038/s41588-018-0309-38.Poldrack, R. A., Monahan, J., Imrey, P. B., Reyna, V., Raichle, M. E., Faigman, D., & Buckholtz, J. W. (2018). Predicting Violent Behavior: What Can Neuroscience Add? Trends in Cognitive Sciences, 22(2), 111-123. doi:10.1016/j.tics.2017.11.0039.Gabrieli, J. D. E., Ghosh, S. S., & Whitfield-Gabrieli, S. (2015). Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience. Neuron, 85(1), 11-26. doi:10.1016/j.neuron.2014.10.04710.Büchel, C., et al. (2017). Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents. Nature Communications, 8, 14140. doi:10.1038/ncomms1414011.Mamerow, L., Frey, R., & Mata, R. (2016). Risk Taking Across the Life Span: A Comparison of Self-Report and Behavioral Measures of Risk Taking. Psychology and Aging, 31(7). Retrieved from http://dx.doi.org/10.1037/pag000012412.Tisdall, L., Frey, R., Horn, A., Ostwald, D., Horvath, L., Blankenburg, F., Hertwig, R., & Mata, R. (2018). Group and individual differences in the neural representation of described and experienced risk. PsyArXiv. Retrieved from https://psyarxiv.com/3sc9j/13.Frey, R., Pedroni, A., Mata, R., Rieskamp, J., & Hertwig, R. (2017). Risk preference shares the psychometric structure of major psychological traits. Science Advances, 3(10), 1-13. doi:10.1126/sciadv.170138114.Pedroni, A., Frey, R., Bruhin, A., Dutilh, G., Hertwig, R., & Rieskamp, J. (2017). The risk elicitation puzzle. Nature Human Behaviour, 1(November). doi:10.1038/s41562-017-0219-x15.Leong, J. K., Pestilli, F., Wu, C. C., Samanez-Larkin, G. R., & Knutson, B. (2016). White-Matter Tract Connecting Anterior Insula to Nucleus Accumbens Correlates with Reduced Preference for Positively Skewed Gambles. Neuron, 89(1), 63-69. doi:10.1016/j.neuron.2015.12.015
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