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Computational and neural mechanisms of statistical pain learning

Author

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  • Flavia Mancini

    (University of Cambridge)

  • Suyi Zhang

    (Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital)

  • Ben Seymour

    (Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital
    Center for Information and Neural Networks (CiNet))

Abstract

Pain invariably changes over time. These fluctuations contain statistical regularities which, in theory, could be learned by the brain to generate expectations and control responses. We demonstrate that humans learn to extract these regularities and explicitly predict the likelihood of forthcoming pain intensities in a manner consistent with optimal Bayesian inference with dynamic update of beliefs. Healthy participants received probabilistic, volatile sequences of low and high-intensity electrical stimuli to the hand during brain fMRI. The inferred frequency of pain correlated with activity in sensorimotor cortical regions and dorsal striatum, whereas the uncertainty of these inferences was encoded in the right superior parietal cortex. Unexpected changes in stimulus frequencies drove the update of internal models by engaging premotor, prefrontal and posterior parietal regions. This study extends our understanding of sensory processing of pain to include the generation of Bayesian internal models of the temporal statistics of pain.

Suggested Citation

  • Flavia Mancini & Suyi Zhang & Ben Seymour, 2022. "Computational and neural mechanisms of statistical pain learning," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34283-9
    DOI: 10.1038/s41467-022-34283-9
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    References listed on IDEAS

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    Cited by:

    1. Rotem Botvinik-Nezer & Bogdan Petre & Marta Ceko & Martin A. Lindquist & Naomi P. Friedman & Tor D. Wager, 2024. "Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

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