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Dissociable neural correlates of uncertainty underlie different exploration strategies

Author

Listed:
  • Momchil S. Tomov

    (Harvard Medical School
    Harvard University)

  • Van Q. Truong

    (Harvard University)

  • Rohan A. Hundia

    (Harvard University)

  • Samuel J. Gershman

    (Harvard University)

Abstract

Most real-world decisions involve a delicate balance between exploring unfamiliar alternatives and committing to the best known option. Previous work has shown that humans rely on different forms of uncertainty to negotiate this "explore-exploit” trade-off, yet the neural basis of the underlying computations remains unclear. Using fMRI (n = 31), we find that relative uncertainty is represented in right rostrolateral prefrontal cortex and drives directed exploration, while total uncertainty is represented in right dorsolateral prefrontal cortex and drives random exploration. The decision value signal combining relative and total uncertainty to compute choice is reflected in motor cortex activity. The variance of this signal scales with total uncertainty, consistent with a sampling mechanism for random exploration. Overall, these results are consistent with a hybrid computational architecture in which different uncertainty computations are performed separately and then combined by downstream decision circuits to compute choice.

Suggested Citation

  • Momchil S. Tomov & Van Q. Truong & Rohan A. Hundia & Samuel J. Gershman, 2020. "Dissociable neural correlates of uncertainty underlie different exploration strategies," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15766-z
    DOI: 10.1038/s41467-020-15766-z
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    Cited by:

    1. Gloria W. Feng & Robb B. Rutledge, 2024. "Surprising sounds influence risky decision making," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Shinji Nakazato & Bojian Yang & Tetsuya Shimokawa, 2024. "Analyzing Human Search Behavior When Subjective Returns are Unobservable," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1921-1947, May.

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