RT Journal Article
SR Electronic
T1 The control of tonic pain by active relief learning
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 222653
DO 10.1101/222653
A1 Suyi Zhang
A1 Hiroaki Mano
A1 Michael Lee
A1 Wako Yoshida
A1 Mitsuo Kawato
A1 Trevor W Robbins
A1 Ben Seymour
YR 2017
UL http://biorxiv.org/content/early/2017/11/21/222653.abstract
AB 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 so that the cause of the pain can be reduced if possible. 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 also 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 allows reduction of ongoing pain when learning about potential relief.