About
I am interested in understanding human brain network organization from neuroimaging data in health and disease. My recent methodological work has focused on graph theory to measure aspects of brain network topology. I am also interested in better neuroscientific understanding and treatment of psychiatric disorders. I am currently leading a consortium funded by the Wellcome Trust and pharmaceutical companies (GSK, Janssen, Lundbeck) - the Neuroimmunology of Mood Disorders and Alzheimer's Disease (NIMA) consortium - which is exploring immune mechanisms and therapeutics for depression and dementia.
Professor Ed Bullmore came to Cambridge as a Professor of Psychiatry in 1999, after undergraduate and graduate degrees at Oxford and King's College, London, where he played a prominent role at the Institute of Psychiatry. He is one of the most distinguished research psychiatrists in the UK with an international reputation.
His research mainly involves the application of brain imaging to psychiatry. He has introduced an entirely original approach to the analysis of human brain anatomy, involving graph theory and its application to small world networks. This has had an enormous impact on the field, especially in relation to understanding the biological basis of schizophrenia and depression. His work has been key to the understanding of the 'wiring' of the human brain.
He was Head of the Department of Psychiatry from 2014 – 2021 and is currently Deputy Head of the School of Clinical Medicine and Director of the Wolfson Brain Imaging Centre. He has been a Vice-President at GlaxoSmithKline, researching how anti-inflammatory drugs may be used in the treatment of psychiatric disorders. His popular science book "The Inflamed Mind: A Radical New Approach to Depression” was a Sunday Times bestseller.
Skills & Expertise
Medicine
Neuroscience
Neuroimaging
Clinical Trials
Lifesciences
Pharmacology
Molecular Biology
Research Interests
Drug Discovery
Bioinformatics
PHARMACOLOGY
Connectivity
Depression Anxiety
Clinical Medicine
Psychiatry
Psychiatric Disorders
Psychiatrist
Cancer
Cognitive Neuroscience
Human Brain Network Organization
Neuroimaging
Graph Theory in Neuroscience
Brain Network Topology
Dementia
Neuroimmunology
Immune Mechanisms in Mental Health
Alzheimer's Disease Research
Mood Disorders
Biological Basis of Schizophrenia
Small World Networks in Brain Anatomy
Brain Wiring
Inflammatory Mechanisms in Mental Health
Anti-inflammatory Drugs for Psychiatry
Neuroscience
Academic Leadership in Psychiatry
Connect With Me
Experience
Head, Department of Psychiatry
- Leading neuroscience research with focus on neuroimaging and brain network analysis in health and brain disorders
Director, Research & Development
Vice-President, Experimental Medicine and Head, Clinical Unit Cambridge
- Leading clinical research unit for experimental medicine and early drug development
Chair, Cambridge Health Imaging
Advanced Research Training Fellow
- Institute of Psychiatry, King's College London
Wellcome Trust Research Training Fellow
Education
University of London (UL)
University of Oxford
Patents (1)
Methods for assessing psychotic disorders
description
Invited Position (2)
CSAR
A New Approach to Depression
Publications (110)
The spectrum, pathophysiology and recovery trajectory of persistent post-COVID-19 cognitive deficits are unknown, limiting our ability to develop prevention and treatment strategies. We report the 1-y...
Functional connectivity analysis of resting state blood oxygen level–dependent (BOLD) functional MRI is widely used for noninvasively studying brain functional networks. Recent findings have indicated...
The complex organization of connectivity in the human brain is incompletely understood. Recently, topological measures based on graph theory have provided a new approach to quantify large-scale cortic...
Studies of the fat-derived hormone leptin have provided key insights into the molecular and neural components of feeding behavior and body weight regulation. An important challenge lies in understandi...
Background
It would be therapeutically useful to predict clinical response to antidepressant drugs. We evaluated structural magnetic resonance imaging (MRI) and functional MRI (fMRI) data as predicto...
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