Statistical learning of pain signals in the brain

Pain often fluctuates over time. We don’t know why, but we know that pain fluctuations strongly affect how well pain can be managed in everyday life.

Recent work in our group suggests that the human brain can learn and control the temporal dynamics of pain. Our approach combines computational models of sequence learning with behavioural and neuroimaging methods.

Specifically, we showed that somatosensory regions in the brain encode probabilistic predictions of the frequency of noxious inputs (Mancini et al., Nature Commun 2022). As predicted by Bayesian theory, cortical sensory responses to noxious inputs are inversely related to the confidence of probabilistic predictions of pain. The smaller the response, the higher the confidence of the posterior, and vice versa (Mulders et al. PNAS 2023). These probabilistic learning processes modulate pain perception (Onysk et al. eLife 2023). Now we are investigating whether statistical learning is affected in chronic pain. Watch this space.

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