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

Value generalization in human avoidance learning.

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


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.


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

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