The control of tonic pain by active relief learning
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 rel...
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Published in | eLife Vol. 7 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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England
eLife Sciences Publications Ltd
27.02.2018
eLife Sciences Publications, Ltd |
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Online Access | Get full text |
ISSN | 2050-084X 2050-084X |
DOI | 10.7554/eLife.31949 |
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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.
Chronic pain lasting longer than three months is a common problem that affects about 1 in 5 people at some point in their lives. The lack of effective treatments has led to widespread use of a group of drugs called opioids – the best-known example is morphine. Opioids work by activating the brain’s natural painkilling system and are useful to relieve short-term pain, for example in trauma or surgery, or in end-of-life care. Unfortunately, long-term use of opioids can cause many undesirable effects, including drug dependency. Misuse of opioids combined with the widespread availability of prescription drugs have contributed to the current crisis of opioid addiction and overdose.
A better understanding of how the brain’s natural painkilling system works could help scientists develop painkillers that offer relief without the harmful side effects of opioids. While unpleasant, pain is important for survival. After an injury, for example, pain saps motivation and forces people to rest and preserve their energy as they are healing. In a way, this sort of pain is healthy because it promotes recovery. There may be times when the brain might want to turn off pain, such as when an individual is seeking new ways to relieve or manage pain. For example, by finding a way to cool a burn.
Now, Zhang et al. show that the brain reduces pain while individuals are trying to find relief. In the experiments, a metal probe was attached to the arm of healthy volunteers and heated until it became painful but not hot enough to burn the skin. Then, the volunteers were asked to play a game in which they had to find out which button on a small keypad cooled down the probe. Sometimes it was easy to turn off the heat, sometimes it was difficult. During the game, volunteers reported how much pain they felt and Zhang et al. used brain imaging to see what happened in their brains.
When the subjects were actively trying to work out which button they should press, pain was reduced. But when the subjects knew which button to press, it was not. Next, Zhang et al. found that a part of the brain called the pregenual cingulate cortex was responsible for making decisions about when to turn off pain and may so trigger the brain’s natural pain killing system. A next step will be to see how this part of the brain decides to turn off pain and if it also controls opioid-like or other chemicals. This could improve the use of opioids, or even help to discover alternative treatments for chronic pain. |
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AbstractList | 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. 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. Chronic pain lasting longer than three months is a common problem that affects about 1 in 5 people at some point in their lives. The lack of effective treatments has led to widespread use of a group of drugs called opioids – the best-known example is morphine. Opioids work by activating the brain’s natural painkilling system and are useful to relieve short-term pain, for example in trauma or surgery, or in end-of-life care. Unfortunately, long-term use of opioids can cause many undesirable effects, including drug dependency. Misuse of opioids combined with the widespread availability of prescription drugs have contributed to the current crisis of opioid addiction and overdose. A better understanding of how the brain’s natural painkilling system works could help scientists develop painkillers that offer relief without the harmful side effects of opioids. While unpleasant, pain is important for survival. After an injury, for example, pain saps motivation and forces people to rest and preserve their energy as they are healing. In a way, this sort of pain is healthy because it promotes recovery. There may be times when the brain might want to turn off pain, such as when an individual is seeking new ways to relieve or manage pain. For example, by finding a way to cool a burn. Now, Zhang et al. show that the brain reduces pain while individuals are trying to find relief. In the experiments, a metal probe was attached to the arm of healthy volunteers and heated until it became painful but not hot enough to burn the skin. Then, the volunteers were asked to play a game in which they had to find out which button on a small keypad cooled down the probe. Sometimes it was easy to turn off the heat, sometimes it was difficult. During the game, volunteers reported how much pain they felt and Zhang et al. used brain imaging to see what happened in their brains. When the subjects were actively trying to work out which button they should press, pain was reduced. But when the subjects knew which button to press, it was not. Next, Zhang et al. found that a part of the brain called the pregenual cingulate cortex was responsible for making decisions about when to turn off pain and may so trigger the brain’s natural pain killing system. A next step will be to see how this part of the brain decides to turn off pain and if it also controls opioid-like or other chemicals. This could improve the use of opioids, or even help to discover alternative treatments for chronic pain. 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.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. |
Author | Yoshida, Wako Kawato, Mitsuo Lee, Michael Seymour, Ben Mano, Hiroaki Robbins, Trevor W Zhang, Suyi |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29482716$$D View this record in MEDLINE/PubMed |
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Keywords | pain basal ganglia neuroscience cingulate cortex endogenous analgesia relief human reinforcement learning |
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SubjectTerms | Adult basal ganglia Behavior Brain research cingulate cortex Cognition Computational neuroscience Computer Simulation Cortex (cingulate) endogenous analgesia Escape learning Experiments Female Healthy Volunteers Humans Laboratories Learning Male Neural networks Neuroimaging Neuroscience Pain Pain Management - methods Physiology Probability Putamen reinforcement learning relief Young Adult |
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Title | The control of tonic pain by active relief learning |
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