Neuroscience is now well established as an inter-disciplinary area of research, and the contribution of theoretical techniquesis invaluable. I have been particularly interested in biologically accurate computational modelling of neurons and systems of neurons, and it seems clear that an alliance between experimental, theoretical and clinical work will continue to yield positive outcomes.
In my current research I am continuing within the realm of biologically constrained computational models, in combination with electrophysiology and behavioural experiments to address clinical questions about the mechanism of therapeutic neurostimulation, specifically deep brain stimulation (DBS) and sacral nerve stimulation (SNS).
For example, my recent work explains the difference in the electric fields created by commonly used stimulation approaches, and therefore can help clinicians to better target the abnormal neural activity that exists as a result of movement disorders. The challenge will be to use such models within routine clinical practice in order to predict the best settings for each individual patient.
September 2016: My new paper on dopamine and visual perception in the presence of TMS induced noise, is now available as an open access article in the Journal of Neuroscience - link
I am currently funded by a grant from the National Tremor Foundation (2016-2017).
Jörn Diedrichsen, Motor Control Group, University of Western Ontario.
Professor Roman Borisyuk, Centre for Theoretical and Computational Neuroscience, University of Plymouth.
et al., 2016, The effect of pedunculopontine nucleus deep brain stimulation on postural sway and vestibular perception, European Journal of Neurology, Vol:23, ISSN:1351-5101, Pages:668-670
et al., 2016, Dopamine Activation Preserves Visual Motion Perception Despite Noise Interference of Human V5/MT., J Neurosci, Vol:36, Pages:9303-9312
et al., 2015, Proprioception in motor learning: lessons from a deafferented subject, Experimental Brain Research, Vol:233, ISSN:0014-4819, Pages:2449-2459
et al., 2014, Movement speed is biased by prior experience, Journal of Neurophysiology, Vol:111, ISSN:0022-3077, Pages:128-134
et al., 2014, An automated approach towards detecting complex behaviours in deep brain oscillations, Journal of Neuroscience Methods, Vol:224, ISSN:0165-0270, Pages:66-78