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      Numerical modelling of plasticity induced by transcranial magnetic stimulation

      Wilson, Marcus T.; Goodwin, D.P.; Brownjohn, P.W.; Shemmell, J.; Reynolds, John N.J.
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      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.
      Permanent Research Commons link: https://hdl.handle.net/10289/8062
      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.
      Date
      2013
      Type
      Journal Article
      Publisher
      Springer
      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.
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      • Science and Engineering Papers [3011]
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