Neurocomputational mechanisms underlying fear-biased adaptation learning in changing environments

PLoS Biol. 2023 May 1;21(5):e3001724. doi: 10.1371/journal.pbio.3001724. eCollection 2023 May.

Abstract

Humans are able to adapt to the fast-changing world by estimating statistical regularities of the environment. Although fear can profoundly impact adaptive behaviors, the computational and neural mechanisms underlying this phenomenon remain elusive. Here, we conducted a behavioral experiment (n = 21) and a functional magnetic resonance imaging experiment (n = 37) with a novel cue-biased adaptation learning task, during which we simultaneously manipulated emotional valence (fearful/neutral expressions of the cue) and environmental volatility (frequent/infrequent reversals of reward probabilities). Across 2 experiments, computational modeling consistently revealed a higher learning rate for the environment with frequent versus infrequent reversals following neutral cues. In contrast, this flexible adjustment was absent in the environment with fearful cues, suggesting a suppressive role of fear in adaptation to environmental volatility. This suppressive effect was underpinned by activity of the ventral striatum, hippocampus, and dorsal anterior cingulate cortex (dACC) as well as increased functional connectivity between the dACC and temporal-parietal junction (TPJ) for fear with environmental volatility. Dynamic causal modeling identified that the driving effect was located in the TPJ and was associated with dACC activation, suggesting that the suppression of fear on adaptive behaviors occurs at the early stage of bottom-up processing. These findings provide a neuro-computational account of how fear interferes with adaptation to volatility during dynamic environments.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain Mapping* / methods
  • Cues
  • Emotions
  • Fear* / physiology
  • Humans
  • Learning
  • Magnetic Resonance Imaging

Grants and funding

This study was supported by the National Natural Science Foundation of China (31920103009 to YL, 31871137 to PX), the Major Project of National Social Science Foundation (20&ZD153 to YL), Young Elite Scientists Sponsorship Program by China Association for Science and Technology (YESS20180158 to PX), Shenzhen-Hong Kong Institute of Brain Science – Shenzhen Fundamental Research Institutions (2022SHIBS0003 to YL), and Shenzhen Science and Technology Research Funding Program (JCYJ20180507183500566 to PX). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.