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The control of tonic pain by active relief learning.

Published version
Peer-reviewed

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Authors

Mano, Hiroaki 
Lee, Michael 
Kawato, Mitsuo 

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.

Description

Keywords

basal ganglia, cingulate cortex, endogenous analgesia, human, neuroscience, pain, reinforcement learning, relief, Adult, Behavior, Computer Simulation, Female, Healthy Volunteers, Humans, Learning, Male, Neuroimaging, Pain Management, Young Adult

Journal Title

Elife

Conference Name

Journal ISSN

2050-084X
2050-084X

Volume Title

7

Publisher

eLife Sciences Publications, Ltd
Sponsorship
Wellcome Trust (097490/Z/11/Z)
Arthritis Research UK (21537)
Arthritis Research UK (21192)
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