Mood Disorder and Addictions, Anxiety/Panic Disorders, Schizophrenia, Dementia, Neurological Disorders (e.g. Dystonia, Chronic Pain Syndromes)

Translational Systems Level Neuroscience

• mechanistic understanding of psychiatric and neurological disorders
• identification of objective biomarkers for psychiatric and neurological disorders

Psychiatry remains entirely clinical and therefore subjective with no objective biomarkers to guide clinical practice and research.  For most of the rest of medicine, biomarkers are of crucial importance.  Consequently, development of psychiatric biomarkers is a priority which my work aims to address.  The work is fundamentally translational.

I am interested in a range of common psychiatric disorders, aiming to improve understanding of illness and therapeutic mechanisms, with a focus on treatment resistant illness.  Two themes particularly interest me: a) the 'biology-phenomenology gap', whereby current clinical and psychological understanding is profoundly separated from biological understanding of medication effects, due to a fundamental lack of understanding of the brain at a 'systems' level, and b) the identification of objective biomarkers for psychiatric disorders, for individual patient management.

Regarding the first theme, my approach to achieving a better understanding of syndrome and therapeutic mechanisms uses neuroimaging based studies of psychiatric disorders, focusing largely on the use of reinforcement learning (also neuroeconomic) paradigms, sometimes involving computational models of brain function.   A recent focus is testing Deakin and Graeff’s predictions about depressive illness using loss-avoidance and reward-gain instrumental learning.

With regard to the second theme, my focus is on the development of machine learning-based methods, to identify biomarkers for accurately predicting clinically relevant variables for individual patients.  Initial publications were ‘proof of concept’ studies for situations where the ‘gold standard’ was well established clinically.  A recent focus is making accurate individual patient predictions where none are otherwise currently possible (e.g. ADHD medication response prior to exposure to methylphenidate, determining an accurate risk score for dementia for elderly patients presenting with Mild Cognitive Impairment).

Up to date list

Johnston, B.A.., Tolomeo, S, Gradin, V., Christmas, D., Matthews, K., Steele J.D. (2015) “Failure of Hippocampal Deactivation during Loss Events in Treatment-Resistant Depression” Brain (in press)

Mwangi, B., Ebmeier K.P., Matthews, K.M., Steele, J.D. (2012) "Multicentre Diagnostic Classification of Individual Structural Neuroimaging Scans from Patients with Major Depressive Disorder", Brain135(1) 1508-21

Perrin, J., Merz, S., Bennett, D.., Currie, J., Steele J.D., Reid I., Schwarzbauer C. (2012) "Electroconvulsive Therapy Reduces Frontal Connectivity in Severe Depression", Proc Natl Acad Sci USA 109(14) 5464-8

Gradin, V., Kumar, P., Waiter, G., Ahearn, T., Stickle, C., Milders, M., Reid, I., Hall, J., Steele, J.D. (2011) "Expected Value and Prediction Error Abnormalities in Depression and Schizophrenia", Brain134(6) 1751-1764

Kumar P, Waiter G, Ahearn T, Milders M, Reid I, Steele J.D. (2008) “Abnormal temporal difference reward-learning signals in major depression” Brain, 131(8) 2084-2093

Rück C, Karlsson A, Steele J.D., Edman G, Meyerson B.A., Ericson K, Nyman H, Åsberg M, Svanborg P (2008) "Capsulotomy for Obsessive-Compulsive Disorder – long-term follow-up of 25 patients"JAMA Psychiatry, 65(8), 914-921

Steele J.D., Christmas D., Eljamel M.S., Matthews K. (2008) “Anterior cingulotomy for major depression: Clinical outcome and relationship to lesion characteristics” Biological Psychiatry, 63(7), 670-677

Steele J.D., Kumar P., Ebmeier, K.P. (2007) “Blunted response to feedback information in depressive illness”, Brain, 130 (9), 2367-74

Ebmeier K., Donaghey C., Steele J.D. (2006) “Recent Developments and Current Controversies in Depression”, Lancet, 367, 153-167

Universities of Edinburgh, Glasgow, St Andrews, Aberdeen, Oxford and UCL

NHS

Matlab programming

Computational modelling of behaviour and brain function

Machine learning

SPM analyses