Summary
Bio
I work as a post-doctoral research associate and have been based at C3NL at Imperial College London since July 2013. My main research interests are in the use of structural and functional magnetic resonance imaging (MRI) to investigate the neuroanatomy of neurological and psychiatric disorders, with a view to improving diagnosis, predicting disease progression and quantifying treatment response. My background has included research in a variety of different disorders, particularly Major Depressive Disorder, Huntington's Disease as well as schizophrenia, pre-term birth and obesity.
Currently I'm working on the EU-funded COmorbidity in Relation to AIDS (COBRA) project. This international collaboration aims to characterise the effects of living with HIV during the anti-retroviral era, in relation to many aspects of biology, including brain structure and function. Further details can be found on the research page of my profile.
My other research activities include using machine learning techniques to build a predictive model of brain age, based on MRI data. This can be used to quantify the normal distribution of brain ageing and understanding how neurological or psychiatric conditions, prinicipally traumatic brain injury (TBI), may add to or accelerate the ageing process and consequent susceptibility to dementia. I'm also interested in the interplay of genes and environment on neuroimaging phenotypes and the integration of multi-modal datasets, along with running a study on the test-retest reliability of neuroimaging here at C3NL.
Links
Twitter @JamesCole_Neuro
Publications
Journals
Anaturk M, Kaufmann T, Cole JH, et al., 2020, Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging, Human Brain Mapping, Vol:42, ISSN:1065-9471, Pages:1626-1640
Graham NSN, Jolly A, Zimmerman K, et al., 2020, Diffuse axonal injury predicts neurodegeneration after moderate-severe traumatic brain injury, Brain: a Journal of Neurology, Vol:143, ISSN:0006-8950, Pages:3685-3698
de Lange A-MG, Anatürk M, Suri S, et al., 2020, Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study., Neuroimage, Vol:222
Ramírez J, Górriz JM, Ortiz A, et al., 2020, Editorial: Deep Learning in Aging Neuroscience, Frontiers in Neuroinformatics, Vol:14
Cole JH, 2020, Multimodality neuroimaging brain -age in UK biobank: relationship to biomedical, lifestyle, and cognitive factors, Neurobiology of Aging, Vol:92, ISSN:0197-4580, Pages:34-42