Resting-state functional connectivity predicts impulsivity in economic decision-making.

Published

Journal Article

Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDT-related brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior.

Full Text

Cited Authors

  • Li, N; Ma, N; Liu, Y; He, X-S; Sun, D-L; Fu, X-M; Zhang, X; Han, S; Zhang, D-R

Published Date

  • March 2013

Published In

Volume / Issue

  • 33 / 11

Start / End Page

  • 4886 - 4895

PubMed ID

  • 23486959

Pubmed Central ID

  • 23486959

Electronic International Standard Serial Number (EISSN)

  • 1529-2401

International Standard Serial Number (ISSN)

  • 0270-6474

Digital Object Identifier (DOI)

  • 10.1523/JNEUROSCI.1342-12.2013

Language

  • eng