4.5 Article

The neural coorelates of risk propensity in males and females using resting-state fMRI

Journal

FRONTIERS IN BEHAVIORAL NEUROSCIENCE
Volume 8, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fnbeh.2014.00002

Keywords

functional connectivity; functional magnetic resonance imaging; resting state; risk propensity; sex difference

Funding

  1. National Basic Research Program of China (973 Program) [2011CB707800, 2011CB711000]
  2. National Natural Science Foundation of China [30900487, 31170976, 91132301]
  3. Chinese Academy of Sciences Visiting Professorship for Senior International Scientists
  4. Project for Young Scientists Fund of the Institute of Psychology, Chinese Academy of Sciences [Y0CX163S01]

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Men are more risk prone than women, but the underlying basis remains unclear. To investigate this question, we developed a trait-like measure of risk propensity which we correlated with resting-state functional connectivity to identify sex differences. Specifically, we used short- and long-range functional connectivity densities to identify associated brain regions and examined their functional connectivities in resting-state functional magnetic resonance imaging (fMRI) data collected from a large sample of healthy young volunteers. We found that men had a higher level of general risk propensity (GRP) than women. At the neural level, although they shared a common neural correlate of GRP in a network centered at the right inferior frontal gyrus, men and women differed in a network centered at the right secondary somatosensory cortex, which included the bilateral dorsal anterior/middle insular cortices and the dorsal anterior cingulate cortex. In addition, men and women differed in a local network centered at the left inferior orbitofrontal cortex. Most of the regions identified by this resting-state fMRI study have been previously implicated in risk processing when people make risky decisions. This study provides a new perspective on the brain-behavioral relationships in risky decision making and contributes to our understanding of sex differences in risk propensity.

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