Principal investigators

Ben Seymour

Pain Neuroscience and Technology

Main Lab Location:

CiNet (Main bldg.)

Other Affiliations:

Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, UK. Behavioural and Clinical Neuroscience Institute, Department of Experimental Psychology, University of Cambridge, UK.



Mailing Address:

1-4 Yamadaoka, Suita City Osaka, 565-0871


seymour at


My research aims to understand how pain is processed in the human brain by using a combination of theoretical and experimental methods. Our goal is to use this knowledge to design new types of (technology-based) treatment for patients who suffer from pain – the commonest cause of disability worldwide and a particular problem in aging societies.

At the heart of my research is the development of computational models of how pain is processed in the neural circuits of the brain. These are ‘systems-level’ models, that aim to directly relate neural information processing to subjective perception and observable behaviour. Critically, these models yield precise predictions that can be tested in behavioural, physiological and neuroimaging experiments – my lab typically does all three. We’ve now managed to produce basic working simulations of the human pain system – whilst these don’t fully incorporate all of the complexity of real pain, they do capture what we think is the core ‘structure’ of how pain works as a negative motivation and teaching signal. A much greater challenge is to understand the nature of clinical chronic pain, and we’ve recently started our first translational projects, for example in pain patients with deep brain stimulation, and patients with chronic low back pain

Outside of a clinical context, I am working on the design of new technology-based applications. This includes the development of ‘synthetic’ pain systems that can be used in control systems design, and brain-based communication systems for pain.

Selected Publications:

Zhang S, Mano H, Gowrishanker G, Robbins T, Seymour B Dissociable learning processes underlie human pain conditioning. Current Biology, 26, (1) 52–58 (2016)

Mano H, Yoshida W, Shibata K, Zhang S, Koltzenburg M, Kawato M, Seymour B. Thermosensory perceptual learning is associated with structural brain changes in parietal-opercular (SII) cortex Journal of Neuroscience. 37(39) 9380-8 (2017)

Zhang S, Mano H, Lee M, Yoshida W, Robbins T, Kawato M, Seymour B. The Control of Tonic Pain by Active Relief Learning. eLife 2018;7:e31949 (2018).

Mano H, Kotecha G, Leibnitz K, Matsubara T, Nakae A, Shenker N, Shibata M, Voon, Yoshida W, Lee M, Yanagida T, Kawato M, Rosa M, Seymour B. Classification and characterisation of brain network changes in chronic back pain: A multicenter study. Wellcome Open Research, 3:19 (2018).

Norbury A, Robbins T, Seymour B. Value generalization in human avoidance learning eLife eLife, 7, e34779. (2018)

Short Biography:

I am neuroscientist and neurologist, having trained in computational and imaging neuroscience at UCL, and clinical neurology in London and Cambridge. I currently have a joint appointment between CiNet and the Computational and Biological Learning Lab at the University of Cambridge, funded by the Wellcome Trust. I am an honorary Consultant Neurologist at Addenbrookes Hospital in Cambridge.

Announcements / News:

If you are interested to work in my lab, please contact me by email to discuss.

Lab Members:

Hiroaki Mano