Dr Ben Seymour, Computational and Biological Learning Lab, Trumpington Street, Cambridge CB2 1PZ


Center for Information and Neural Networks, National Institute for Information and Communications Technology (NICT), 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan.

bjs49 AT / seymour AT

F1000 reviews (paywall)



Moving to Oxford - new positions available

From 1st April 2020, the lab will be moving to WIN / IBME at Oxford University, where we will work across clinical neuroscience and biomedical engineering. Later this year, we will advertise for postdoctoral researcher positions to commence from 1st April 2020 or later, so if you are interested, feel free to contact me at any point from now. There may also be PhD opportunities through either clinical neuroscience or engineering schools. 


New paper in Neuron - a review of the RL model of pain

Our new paper proposes a computational architecture of the pain system - how pain drives a diversity of responses, actions and learning. At its heart it addresses a fundamental question about what pain represents:either i) a sensory-dominant view, where pain reflects an optimal inference of perceived magnitude of a noxious event, or ii) control-dominant view, where pain reflects an optimal control signal for behavioural change? We argue for the control-dominant view, primarily on the basis of evidence from several core categories of endogenous control: modulation by decision conflict, by predictive value, and by informational value; i.e. even though Bayesian / predictive coding models can explain core instances of pain modulation, they can only be part of the solution, and a broader reinforcement learning model can accommodate pain variability more fully. This helps reframe pain as primarily and precisely tuned for learning and behavioural control. So whilst pain may be private, self-intimating, and incorrigible; it may also be precise and computationally objectifiable. This gives some insight into the broad array of brain regions needed to construct the perception of pain, and suggests a wealth of ways in abnormalities in the underlying computational architecture might predispose to chronic pain


New paper in eLife: Value generalization in human avoidance learning

Our new paper is out - here's the eLife digest:

People apply what they have learned from past experiences to similar situations, a phenomenon known as generalization. For example, if eating a particular food caused illness, a person will likely avoid foods that look or smell similar in the future. Generalization can be helpful because it allows people to decide how to act in new situations. But over-generalizing after a bad experience could lead an individual to fear benign scenarios. This may lead to unnecessary anxiety. It can also create a negative cycle where people avoid certain situations or objects, which prevents them from learning that they are safe.

Now, Norbury et al. show what happens in the brain when making decisions that involve generalization. In the experiments, volunteers were told seeing a particular flower design would lead to a painful electric shock, unless they pushed a button to ‘avoid’ that image. Individuals completed this task in a magnetic resonance imaging machine so Norbury et al. could observe their brain activity while they completed the task. A second group of individuals were asked to complete a similar task online, but instead of being shocked they lost money if they failed to hit a key when they saw the ‘dangerous’ flower. The online participants also filled out a survey about their experience of various psychological symptoms.

Norbury et al. used computer modeling to reconstruct how people decided whether or not to avoid images that looked similar to the harm-associated images but were in fact safe (did not lead to pain or losing money). The experiments showed that different parts of the brain were involved in different parts of the generalization process. Areas of the brain that interpret vision, fear, and safety played distinct roles. People who generalized more from harmful outcomes were more likely to report feeling anxious and having intrusive negative thoughts in their everyday lives. A better understanding of the brain processes that cause these symptoms in different situations might help scientists develop better treatments for conditions like anxiety in the future.

This was picked up by a number of news sites, for example ScienceDaily


New paper in eLife: The control of tonic pain by active relief learning

Our new paper on relief learning, endogenous control and the pgACC. Here's the eLife digest:

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.


The research was covered by several news sources.
Yahoo News


New paper in J. Neurosci suggests SII may act as thermosensory cortex

Here's the abstract and significance statement:

The location of a sensory cortex for temperature perception remains a topic of substantial debate. Both the parietal–opercular (SII) and posterior insula have been consistently implicated in thermosensory processing, but neither region has yet been identified as the locus of fine temperature discrimination. Using a perceptual learning paradigm in male and female humans, we show improvement in discrimination accuracy for subdegree changes in both warmth and cool detection over 5 d of repetitive training. We found that increases in discriminative accuracy were specific to the temperature (cold or warm) being trained. Using structural imaging to look for plastic changes associated with perceptual learning, we identified symmetrical increases in gray matter volume in the SII cortex. Furthermore, we observed distinct, adjacent regions for cold and warm discrimination, with cold discrimination having a more anterior locus than warm. The results suggest that thermosensory discrimination is supported by functionally and anatomically distinct temperature-specific modules in the SII cortex.

SIGNIFICANCE STATEMENT We provide behavioral and neuroanatomical evidence that perceptual learning is possible within the temperature system. We show that structural plasticity localizes to parietal–opercular (SII), and not posterior insula, providing the best evidence to date resolving a longstanding debate about the location of putative “temperature cortex.” Furthermore, we show that cold and warm pathways are behaviorally and anatomically dissociable, suggesting that the temperature system has distinct temperature-dependent processing modules.