Taking action in the face of threat: Neural synchronization predicts adaptive coping

Katherine A. Collins, Avi Mendelsohn, Christopher K. Cain, Daniela Schiller

Research output: Contribution to journalArticlepeer-review

Abstract

The ability to take action in the face of threat is highly diverse across individuals. What are the neural processes that determine individual differences in the ability to cope with danger? We hypothesized that the extent of synchronization between amygdala, striatum, and medial prefrontal cortex (mPFC) would predict successful active coping performance. To test this, we developed a novel computer task based on the principals of Sidman avoidance. Healthy human participants learned through trial and error to move a marker between virtual game board compartments once every 3 s to avoid mild shocks. Behaviorally, participants exhibited large individual differences. Strikingly, both amygdala-mPFC and caudate-mPFC coupling during active coping trials covaried with final active coping performance across participants. These findings indicate that synchronization between mPFC subregions, and both amygdala and caudate predicts whether individuals will achieve successful active coping performance by the end of training. Thus, successful performance of adaptive actions in the face of threat requires functional synchronization of a neural circuit consisting of mPFC, striatum, and amygdala. Malfunction in the crosstalk between these components might underlie anxiety symptoms and impair individuals’ ability to actively cope under stress. This opens an array of possibilities for therapeutic targets for fear and anxiety disorders.

Original languageEnglish
Pages (from-to)14733-14738
Number of pages6
JournalJournal of Neuroscience
Volume34
Issue number44
DOIs
StatePublished - 29 Oct 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 the authors.

Keywords

  • Active avoidance
  • Coping
  • Emotion
  • Fear
  • Individual differences
  • Instrumental learning

ASJC Scopus subject areas

  • Neuroscience (all)

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