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Elife. 2018 May 8;7. pii: e34779. doi: 10.7554/eLife.34779.

Value generalization in human avoidance learning.

Author information

1
Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
2
Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
3
Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.
4
Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita City, Japan.

Abstract

Generalization during aversive decision-making allows us to avoid a broad range of potential threats following experience with a limited set of exemplars. However, over-generalization, resulting in excessive and inappropriate avoidance, has been implicated in a variety of psychological disorders. Here, we use reinforcement learning modelling to dissect out different contributions to the generalization of instrumental avoidance in two groups of human volunteers (N = 26, N = 482). We found that generalization of avoidance could be parsed into perceptual and value-based processes, and further, that value-based generalization could be subdivided into that relating to aversive and neutral feedback - with corresponding circuits including primary sensory cortex, anterior insula, amygdala and ventromedial prefrontal cortex. Further, generalization from aversive, but not neutral, feedback was associated with self-reported anxiety and intrusive thoughts. These results reveal a set of distinct mechanisms that mediate generalization in avoidance learning, and show how specific individual differences within them can yield anxiety.

KEYWORDS:

anxiety disorders; aversive learning; avoidance; generalization; human; neuroscience; obsessive-compulsive disorder; reinforcement learning

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