Mitul Mehta

+44 (0) 2032283053


I am a Reader in Imaging & Psychopharmacology and head of the neuropharmacology section in the Department of Neuroimaging at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN).

My research focuses on understanding drug effects on brain function, and I received the British Association for Psychopharmacology young investigator award in 2005 for my investigations on the dopamine system and its relevance for human cognitive function. Since then, I have applied my research to the assessment of novel drugs for improving cognitive function, and the role of imaging acquisition and analysis technologies in understanding drug mechanisms.


2003 Reader in Imaging & Psychopharmacology, Institute of Psychiatry, Kings College London, UK
1996 Assistant psychologist, University of Cambridge, UK

PhD, University of Cambridge, UK
MRC Research Fellow, Imperial College London / MRC Clinical Sciences Centre, UK

My recent research has shown the brain networks affected by ketamine and developed assays for testing drugs that block the effects of other drugs. Ketamine is interesting to psychiatry and neuroscience for a number of reasons: it allows us to study the human glutamate system; it produces symptoms that overlap with some symptoms in patients with schizophrenia and it has rapid antidepressant effects.

The combination of imaging with drugs is powerful because it gives insights into drug mechanisms and shows the direct brain effects, including those not open to behavioural assessment (such as what happens while we are waiting). Novel drugs can also be tested with imaging assays to give rapid insights into their functional effects in comparison to existing drugs.

The neuropharmacology group are engaged in testing the brain mechanisms of a number of novel compounds which we expect to benefit psychiatry through improved understanding and validation of new treatments.



Developing brain imaging (using MRI, PET and EEG scans) for better diagnosis, improved understanding of disease biology, enhanced prediction of response to treatments, and clearer patient stratification for trials.

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