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Numerical modelling of plasticity induced by transcranial magnetic stimulation

Abstract
We use neural field theory and spike-timing dependent plasticity to make a simple but biophysically reasonable model of long-term plasticity changes in the cortex due to transcranial magnetic stimulation (TMS). We show how common TMS protocols can be captured and studied within existing neural field theory. Specifically, we look at repetitive TMS protocols such as theta burst stimulation and paired-pulse protocols. Continuous repetitive protocols result mostly in depression, but intermittent repetitive protocols in potentiation. A paired pulse protocol results in depression at short (<∼10 ms) and long (>∼ 100 ms) interstimulus intervals, but potentiation for mid-range intervals. The model is sensitive to the choice of neural populations that are driven by the TMS pulses, and to the parameters that describe plasticity, which may aid interpretation of the high variability in existing experimental results. Driving excitatory populations results in greater plasticity changes than driving inhibitory populations. Modelling also shows the merit in optimizing a TMS protocol based on an individual’s electroencephalogram. Moreover, the model can be used to make predictions about protocols that may lead to improvements in repetitive TMS outcomes.
Type
Journal Article
Type of thesis
Series
Citation
Wilson, M.T., Goodwin, D.P., Brownjohn, P.W., Shemmell, J. & Reynolds, J.N.J. (2013). Numerical modelling of plasticity induced by transcranial magnetic stimulation. Article accepted for publication in the Journal of Computational Neuroscience.
Date
2013
Publisher
Springer
Degree
Supervisors
Rights
This is an author’s accepted version of an article accepted for publication in the Journal of Computational Neuroscience. Full text embargoed until October 2014.