Research groups
Ben Seymour
BSc MB ChB PhD MRCP FRSA
Professor of Clinical Neuroscience
- Wellcome Senior Fellow
- Consultant Neurologist
Pain and aversive learning, with a focus on computational neuroscience and neurotechnology
Pain and aversive learning
My lab addresses the computational and systems neuroscience of pain. This research is part theoretical: building realistic models of neuronal information processes to understand processes of pain perception and behaviour, and part experimental: testing these theories using a range of experimental methodologies, especially fMRI. My research aims to develop new technology-based therapies for treating pain in clinical populations.
I am a Wellcome Senior Clinical Fellow at Oxford University, working jointly at the Wellcome Centre for Integrative Neuroimaging and the Oxford Institute for Biomedical Engineering; and a visiting researcher at the National institute of Information and Communications Technology in Osaka, and ATR labs (Kyoto). I am also an honorary consultant neurologist at Oxford University Hospitals NHS Trust with an interest in behavioural homeostasis and sleep neurology.
Key publications
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Pain Control by Co-adaptive Learning in a Brain-Machine Interface.
Journal article
Zhang S. et al, (2020), Curr Biol
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Pain: A Precision Signal for Reinforcement Learning and Control
Journal article
Seymour B., (2019), Neuron, 101, 1029 - 1041
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The control of tonic pain by active relief learning
Journal article
Zhang S. et al, (2017)
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Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure
Journal article
Koizumi A. et al, (2017), Nature Human Behaviour, 1
Recent publications
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Computational and neural mechanisms of statistical pain learning.
Journal article
Mancini F. et al, (2022), Nat Commun, 13
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Confidence of probabilistic predictions modulates the cortical response to pain
Preprint
Mulders D. et al, (2022)
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Neurofeedback training without explicit phantom hand movements and hand-like visual feedback to modulate pain: A randomized crossover feasibility trial.
Journal article
Yanagisawa T. et al, (2022), J Pain
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Endogenous modulation of pain relief: evidence for dopaminergic but not opioidergic involvement
Preprint
Desch S. et al, (2022)
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Learning the statistics of pain: computational and neural mechanisms
Preprint
Mancini F. et al, (2021)