Value generalization in human avoidance learning
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, and ventromedial prefrontal cortex, respectively. 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.
- Ben Seymour
- Agnes Norbury
Contact Information:Name: Agnes Norbury
Acknowledgements and Funding:
This study was funded by the Wellcome Trust. The authors declare no relevant conflicts of interest.
External Publication Links:Value generalization in human avoidance learning
Siemens Magnetom Skyra Fit (3T)
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This data was obtained from the OpenfMRI database. Its accession number is ds000249
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Revision: 1.0.0 Date Set: Dec. 11, 2017, 11:47 p.m.
- Initial release