MRCP PhD MBPsS
Associate Professor and Honorary Consultant
Computational Neurology Group
I use computational modelling to understand how neurons produce cognitive processes like memory, attention and motivation by reward. I study how they are influenced by neurotransmitters such as dopamine and acetylcholine. My research group models eye movements, EEG, fMRI and single-neuron data to track these processes in health and disease. In particular, we ask how memory and motivation are affected by drugs, Parkinson's disease, and focal damage to the frontal lobe of the brain.
- 2020: Thomas Willis Intermediate Career Researcher Prize
- 2019: Leverhulme Trust Research Grant
- 2017: MRC Clinician Scientist Fellowship
- 2017: Fellow of the RCUK-funded Software Sustainability Institute
- 2015: Junior Research Fellowship at Lady Margaret Hall
- 2016: University Staff Innovation Seed Fund award
- 2013: Oxford Learning Institute Teaching Award
- 2013: Oxford University OxTALENT Prize for innovation
- 2009: Wellcome Trust Clinical Research Training Fellowship (UCL)
- 2007: NIHR Academic Clinical Fellowship (Imperial College)
- 2000: Sir Rudolph Peters Prize, Gonville and Caius College Cambridge
Our lab has broad interests, applying neuropsychological methods to open questions in cognitive neuroscience. We are especially interested in working memory, attention and motivation. Cognitive models of these functions generate testable neural predictions about what we should observe when neurotransmitters are modulated, and when specific brain areas are damaged. These predictions can then be tested by comparing behavioural performance of healthy volunteers and patients with neurological disease. We collaborate with several other groups including with Prof Masud Husain, Prof Mark Stokes, and Prof Rafal Bogacz.
Major questions we wish to answer include:
- Is dopamine responsible for learning along multiple dimensions of outcomes?
- Does motivation depend on frontostriatal dopamine? (Manohar et al Current Biology 2015)
- Do acetylcholine and dopamine influence reward-based decision-making?
- Can we modulate attention through cholinergic drugs?
- How do neurons support attention in working memory? (Manohar et al. 2017)
To manipulate neurotransmitters, we administer dopaminergic and cholinergic drugs to healthy volunteers, and study patients with Parkinson’s disease on and off their medication. To study the effect of brain lesions, we test patients who have focal damage in the frontal lobes. We also have access to neurological patients with a number of other diseases.
The main methods that we use for testing include eye tracking, pupillometry and decision-making tasks, combined with computational modelling, but we also have at our disposal functional MRI, EEG and MEG.
Principal Investigator: Prof Sanjay Manohar
As part of this Master’s / DPhil project, you will gain experience in designing experiments, using an eye tracker, and pupillometry. You will also have the opportunity to work with patients, or to study the effects of dopaminergic medication. If interested, you will also have the opportunity to learn how to apply computational modelling and machine learning to data.
You will work in a team comprising a postdoctoral researcher, a research assistant, other DPhil students and undergraduates. There will be plenty of guidance on day-to-day issues, plus a weekly meeting with the supervisor. We hold weekly lab meetings, and you will have an opportunity to present your design and data to the group.
Neural signature of flexible coding in prefrontal cortex
Bocincova A. et al, (2022), Proceedings of the National Academy of Sciences of USA
Printzlau FAB. et al, (2022), J Cogn Neurosci, 1 - 21
Moeller M. et al, (2022), PLoS Comput Biol, 18
Grima LL. et al, (2022), Neuropsychopharmacology
Attaallah B. et al, (2022), Elife, 11
Grogan JP. et al, (2022), Cogn Psychol, 135
Atilgan H. et al, (2022), Brain
Nucleus accumbens D1-receptors regulate and focus transitions to reward-seeking action
GRIMA L. et al, (2022), Neuropsychopharmacology
Manohar SG., (2022), BRAIN
Tai XY. et al, (2022), Commun Biol, 5