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Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males
Authors:Yacila I Deza Araujo  Stephan Nebe  Philipp T Neukam  Shakoor Pooseh  Miriam Sebold  Maria Garbusow  Andreas Heinz  Michael N Smolka
Institution:1.Department of Psychiatry and Neuroimaging Center,Technische Universit?t Dresden,Dresden,Germany;2.Department of Psychiatry and Psychotherapy,Charité–Universit?tsmedizin Berlin, Campus Charité Mitte,Berlin,Germany
Abstract:Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.
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