Research groups
Ben Seymour
BSc MB ChB PhD MRCP FRSA
Professor of Clinical Neuroscience
- Wellcome Senior Fellow
- Consultant Neurologist
- Turing Fellow
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 ATR labs (Kyoto). I am a Fellow at the Alan Turing Institute with an interest in safe AI control systems. I am also an honorary consultant neurologist at Oxford University Hospitals NHS Trust with an interest in behavioural homeostasis and sleep, pain and fatigue neurology.
Key publications
Computational and neural mechanisms of statistical pain learning.
Journal article
Mancini F. et al, (2022), Nat Commun, 13
Pain Control by Co-adaptive Learning in a Brain-Machine Interface
Journal article
Zhang S. et al, (2020), Current Biology, 30, 3935 - 3944.e7
Pain: A Precision Signal for Reinforcement Learning and Control.
Journal article
Seymour B., (2019), Neuron, 101, 1029 - 1041
Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure
Journal article
Koizumi A. et al, (2016), Nature Human Behaviour, 1
Recent publications
Homeostasis after injury: How intertwined inference and control underpin post-injury pain and behaviour
Journal article
Mahajan P. et al, (2026), PLOS Computational Biology, 22, e1013538 - e1013538
Neural Associative Skill Memories for Safer Robotics and Modeling Human Sensorimotor Repertoires
Journal article
Mahajan P. et al, (2025), Neural Computation, 38, 1 - 27
Wirelessly transmitted subthalamic nucleus signals decode endogenous pain levels in Parkinson's disease patients.
Journal article
Reza A. et al, (2025), Neurobiol Dis, 219
Forward and reverse engineering the pain system: from computational neuroscience to neuro-engineering
Journal article
Mahajan P. and Seymour B., (2025), Pain, 166, S75 - S78
Composing the value signal for dopamine-mediated learning
Preprint
Mahajan P. and Seymour B., (2025)