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.

Tasks:

001 Generalization of Instrumental Avoidance Task

Investigators:

• Ben Seymour
• Agnes Norbury

Contact Information:

Acknowledgements and Funding:

This study was funded by the Wellcome Trust. The authors declare no relevant conflicts of interest.

External Publication Links:

Sample Size:

26

Scanner Type:

Siemens Magnetom Skyra Fit (3T)

License:

PDDL

Accession Number:

ds000249

How to cite this dataset:

In addition to any citation requirements in the dataset summary please use the following to cite this dataset:

This data was obtained from the OpenfMRI database. Its accession number is ds000249

Curated:

Yes

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Direct Links to data:

Revision: 1.0.0 Date Set: Dec. 11, 2017, 11:47 p.m.