The control of tonic pain by active relief learning
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.
Article and author information
Author details
Funding
Wellcome
- Trevor W Robbins
- Ben Seymour
National Institute of Information and Communications Technology
- Suyi Zhang
- Hiroaki Mano
- Ben Seymour
Japan Society for the Promotion of Science
- Hiroaki Mano
- Wako Yoshida
- Ben Seymour
Japan Agency for Medical Research and Development
- Wako Yoshida
- Mitsuo Kawato
- Ben Seymour
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The two experiments were performed in different institutes, and approved by their relevant ethics and Safety committees: for the National Institute of Information and Communications Technology, Japan (Expt 1), and the Advanced Telecommunications Research Institute, Japan (Expt 2). All subjects gave informed consent prior to participation
Copyright
© 2018, Zhang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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