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https://hdl.handle.net/2440/137641
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Type: | Journal article |
Title: | Finding Synaptic Couplings from a Biophysical Model of Motor Evoked Potentials after Theta-Burst Transcranial Magnetic Stimulation |
Author: | Wilson, M.T. Goldsworthy, M. Vallence, A.-M. Fornito, A. Rogasch, N. |
Citation: | Brain Research, 2023; 1801:148205-1-148205-14 |
Publisher: | Elsevier |
Issue Date: | 2023 |
ISSN: | 0006-8993 1872-6240 |
Statement of Responsibility: | Marcus T. Wilson, Mitchell R. Goldsworthy, Ann-Maree Vallence, Alex Fornito, Nigel C. Rogasch |
Abstract: | Objective: We aimed to use measured input-output (IO) data to identify the best fitting model for motor evoked potentials. Methods: We analyzed existing IO data before and after intermittent and continuous theta-burst stimulation (iTBS & cTBS) from a small group of subjects (18 for each). We fitted individual synaptic couplings and sensitivity parameters using variations of a biophysical model. A best performing model was selected and analyzed. Results: cTBS gives a broad reduction in MEPs for amplitudes larger than resting motor threshold (RMT). Close to threshold, iTBS gives strong potentiation. The model captures individual IO curves. There is no change to the population average synaptic weights post TBS but the change in excitatory-to-excitatory synaptic coupling is strongly correlated with the experimental post-TBS response relative to baseline. Conclusions: The model describes population-averaged and individual IO curves, and their post-TBS change. Variation among individuals is accounted for with variation in synaptic couplings, and variation in sensitivity of neural response to stimulation. Significance: The best fitting model could be applied more broadly and validation studies could elucidate underlying biophysical meaning of parameters. |
Keywords: | Motor Evoked Potential transcranial magnetic stimulation cortical plasticity modeling neural field theory theta burst stimulation |
Rights: | © 2022 Elsevier B.V. All rights reserved. |
DOI: | 10.1016/j.brainres.2022.148205 |
Grant ID: | http://purl.org/au-research/grants/arc/DE180100741 http://purl.org/au-research/grants/arc/DE200100575 http://purl.org/au-research/grants/arc/DE190100694 http://purl.org/au-research/grants/nhmrc/1197431 http://purl.org/au-research/grants/nhmrc/1146292 http://purl.org/au-research/grants/arc/DP200103509 |
Published version: | http://dx.doi.org/10.1016/j.brainres.2022.148205 |
Appears in Collections: | Molecular and Biomedical Science publications |
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