At Risk of Being Risky: The Relationship Between "brain Age" Under Emotional States and Risk Preference

Overview

Journal Dev Cogn Neurosci

Publisher Elsevier

Specialties Neurology
Psychiatry

Date 2017 Mar 11

PMID 28279917

Citations 30

Authors

Marc D Rudolph

Oscar Miranda-Dominguez

Alexandra O Cohen

Kaitlyn Breiner

Laurence Steinberg

Richard J Bonnie

Elizabeth S Scott

Kim Taylor-Thompson

Jason Chein

Karla C Fettich

Jennifer A Richeson

Danielle V Dellarco

Adriana Galvan

B J Casey

Damien A Fair

Affiliations

Soon will be listed here.

Abstract

Developmental differences regarding decision making are often reported in the absence of emotional stimuli and without context, failing to explain why some individuals are more likely to have a greater inclination toward risk. The current study (N=212; 10-25y) examined the influence of emotional context on underlying functional brain connectivity over development and its impact on risk preference. Using functional imaging data in a neutral brain-state we first identify the "brain age" of a given individual then validate it with an independent measure of cortical thickness. We then show, on average, that "brain age" across the group during the teen years has the propensity to look younger in emotional contexts. Further, we show this phenotype (i.e. a younger brain age in emotional contexts) relates to a group mean difference in risk perception - a pattern exemplified greatest in young-adults (ages 18-21). The results are suggestive of a specified functional brain phenotype that relates to being at "risk to be risky."

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References

Laumann T, Gordon E, Adeyemo B, Snyder A, Joo S, Chen M . Functional System and Areal Organization of a Highly Sampled Individual Human Brain. Neuron. 2015; 87(3):657-70. PMC: 4642864. DOI: 10.1016/j.neuron.2015.06.037. View

Gabrieli J, Ghosh S, Whitfield-Gabrieli S . Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience. Neuron. 2015; 85(1):11-26. PMC: 4287988. DOI: 10.1016/j.neuron.2014.10.047. View

Fair D, Schlaggar B, Cohen A, Miezin F, Dosenbach N, Wenger K . A method for using blocked and event-related fMRI data to study "resting state" functional connectivity. Neuroimage. 2007; 35(1):396-405. PMC: 2563954. DOI: 10.1016/j.neuroimage.2006.11.051. View

Power J, Schlaggar B, Petersen S . Recent progress and outstanding issues in motion correction in resting state fMRI. Neuroimage. 2014; 105:536-51. PMC: 4262543. DOI: 10.1016/j.neuroimage.2014.10.044. View

Fox M, Raichle M . Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007; 8(9):700-11. DOI: 10.1038/nrn2201. View

Cao M, Wang J, Dai Z, Cao X, Jiang L, Fan F . Topological organization of the human brain functional connectome across the lifespan. Dev Cogn Neurosci. 2013; 7:76-93. PMC: 6987957. DOI: 10.1016/j.dcn.2013.11.004. View

Satterthwaite T, Wolf D, Ruparel K, Erus G, Elliott M, Eickhoff S . Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth. Neuroimage. 2013; 83:45-57. PMC: 3874413. DOI: 10.1016/j.neuroimage.2013.06.045. View

Wager T, Nichols T . Optimization of experimental design in fMRI: a general framework using a genetic algorithm. Neuroimage. 2003; 18(2):293-309. DOI: 10.1016/s1053-8119(02)00046-0. View

Mueller S . The influence of emotion on cognitive control: relevance for development and adolescent psychopathology. Front Psychol. 2012; 2:327. PMC: 3223617. DOI: 10.3389/fpsyg.2011.00327. View

10.

Brown M, Lebel R, Dolcos F, Wilman A, Silverstone P, Pazderka H . Effects of emotional context on impulse control. Neuroimage. 2012; 63(1):434-46. DOI: 10.1016/j.neuroimage.2012.06.056. View

11.

Fox M, Snyder A, Zacks J, Raichle M . Coherent spontaneous activity accounts for trial-to-trial variability in human evoked brain responses. Nat Neurosci. 2005; 9(1):23-5. DOI: 10.1038/nn1616. View

12.

Mennes M, Kelly C, Zuo X, Di Martino A, Biswal B, Castellanos F . Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity. Neuroimage. 2010; 50(4):1690-701. PMC: 2839004. DOI: 10.1016/j.neuroimage.2010.01.002. View

13.

Petersen S, Dubis J . The mixed block/event-related design. Neuroimage. 2011; 62(2):1177-84. PMC: 3288695. DOI: 10.1016/j.neuroimage.2011.09.084. View

14.

Fox M, Snyder A, Vincent J, Raichle M . Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron. 2007; 56(1):171-84. DOI: 10.1016/j.neuron.2007.08.023. View

15.

Betzel R, Byrge L, He Y, Goni J, Zuo X, Sporns O . Changes in structural and functional connectivity among resting-state networks across the human lifespan. Neuroimage. 2014; 102 Pt 2:345-57. DOI: 10.1016/j.neuroimage.2014.07.067. View

16.

Huettel S . Event-related fMRI in cognition. Neuroimage. 2011; 62(2):1152-6. PMC: 3277683. DOI: 10.1016/j.neuroimage.2011.08.113. View

17.

Fair D, Nigg J, Iyer S, Bathula D, Mills K, Dosenbach N . Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data. Front Syst Neurosci. 2013; 6:80. PMC: 3563110. DOI: 10.3389/fnsys.2012.00080. View

18.

Jones O, Wagner A, Faigman D, Raichle M . Neuroscientists in court. Nat Rev Neurosci. 2013; 14(10):730-6. DOI: 10.1038/nrn3585. View

19.

Steinberg L . A Social Neuroscience Perspective on Adolescent Risk-Taking. Dev Rev. 2008; 28(1):78-106. PMC: 2396566. DOI: 10.1016/j.dr.2007.08.002. View

20.

Fair D, Bathula D, Nikolas M, Nigg J . Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD. Proc Natl Acad Sci U S A. 2012; 109(17):6769-74. PMC: 3340031. DOI: 10.1073/pnas.1115365109. View