The control of tonic pain by active relief learning

ELife
Suyi ZhangBen Seymour

Abstract

Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief.

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Citations

Jan 6, 2021·Nature Medicine·Jae-Joong LeeChoong-Wan Woo
Aug 17, 2020·Current Biology : CB·Suyi ZhangBen Seymour

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Software Mentioned

SPM12
WSLS
Axiom
MATLAB7
Variational Bayesian Analysis ( VBA )
BrainVision
FSL
VBA
fmriprep

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