Psychiatry, neurology, brain imaging: http://dslink333.dyndns.org/

My main clinical and academic interests are psychiatry, neurology and its overlap neuropsychiatry, linked to neuroimaging and machine learning. Two main areas:

i) Machine learning for individual patient predictions – diagnostic and prognostic.  Initial work focused on proof of concept studies using research data, now focused on application to routinely acquired NHS data, with a particular emphasis on fully integrating the techniques into routine clinical practice.  Recent success in obtaining MRC Programme Grant funding.

ii) Mechanisms research, which include computational modelling of behaviour and brain function (model-based fMRI, forward translation), neurosurgical studies on therapeutic interventions for brain disorders and back translation from functional brain imaging studies on patients to animals for drug discovery.

Techniques: structured psychiatric clinical assessment, neuropsychological testing, reinforcement learning and neuroeconomics paradigms, Matlab programming, fMRI, GABA spectroscopy, computational modelling of brain and behaviour, diffusion tensor imaging, machine learning, PET and EEG source reconstruction.

Up to date list

Selected Publications:

Tolomeo, S., Christmas, D., Jentzsch, I., Johnston, B., Sprenglemeyer, R., Matthews, K., Steele, J.D. (2016) “A Causal Role for the Anterior Mid-Cingulate Cortex in Negative Affect and Cognitive Control”  Brain (in press)

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” Brain138(9) 2766-76

Gradin V., Baldacchino A., Balfour D., Matthews K, Steele J.D. (2014) “Abnormal Brain Activity during a Reward and Loss Task in Opiate Dependent Patients receiving Methadone Maintenance Therapy” Neuropsychopharmacology 39(4):885-94

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", Brain 135(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", Brain 134(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

Steele J.D., Meyer M., Ebmeier K.P. (2004) “Neural Predictive Error Signal Correlates with Depressive Illness Severity in a Game Paradigm” NeuroImage, 23, 269-280

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

Machine learning, Matlab programming, SPM analyses, Computational modelling of behaviour and brain function