TMS-evoked potential propagation reflects effective brain connectivity

<i>Objective.</i>Cognition is achieved through communication between brain regions. Consequently, there is considerable interest in measuring effective connectivity. A promising effective connectivity metric is transcranial magnetic stimulation (TMS) evoked potentials (TEPs), an inflection in amplitude of the electroencephalogram recorded from one brain region as a result of TMS applied to another region. However, the TEP is confounded by multiple factors and there is a need for further investigation of the TEP as a measure of effective connectivity and to compare it to existing statistical measures of effective connectivity.<i>Approach.</i>To this end, we used a pre-existing experimental dataset to compare TEPs between a motor control task with and without visual feedback. We then used the results to compare our TEP-based measures of effective connectivity to established statistical measures of effective connectivity provided by multivariate auto-regressive modelling.<i>Main results.</i>Our results reveal significantly more negative TEPs when feedback is not presented from 40 ms to 100 ms post-TMS over frontal and central channels. We also see significantly more positive later TEPs from 280-400 ms on the contra-lateral hemisphere motor and parietal channels when no feedback is presented. These results suggest differences in effective connectivity are induced by visual feedback of movement. We further find that the variation in one of these early TEPs (the N40) is reliably related to directed coherence.<i>Significance.</i>Taken together, these results indicate components of the TEPs serve as a measure of effective connectivity. Furthermore, our results also support the idea that effective connectivity is a dynamic process and, importantly, support the further use of TEPs in delineating region-to-region maps of changes in effective connectivity as a result of motor control feedback.

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Publication Details

Journal
Journal of Neural Engineering
Published
2024-12-01
DOI
https://doi.org/10.1088/1741-2552/ad9ee0
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

TMS-evoked potential propagation reflects effective brain connectivity

Ian Daly, Nitin Williams, Slawomir J. Nasuto
Journal of Neural Engineering
EEG and Brain-Computer Interfaces
article

TMS-evoked potential propagation reflects effective brain connectivity

Ian Daly, Nitin Williams, Slawomir J. Nasuto
article en

Abstract

<i>Objective.</i>Cognition is achieved through communication between brain regions. Consequently, there is considerable interest in measuring effective connectivity. A promising effective connectivity metric is transcranial magnetic stimulation (TMS) evoked potentials (TEPs), an inflection in amplitude of the electroencephalogram recorded from one brain region as a result of TMS applied to another region. However, the TEP is confounded by multiple factors and there is a need for further investigation of the TEP as a measure of effective connectivity and to compare it to existing statistical measures of effective connectivity.<i>Approach.</i>To this end, we used a pre-existing experimental dataset to compare TEPs between a motor control task with and without visual feedback. We then used the results to compare our TEP-based measures of effective connectivity to established statistical measures of effective connectivity provided by multivariate auto-regressive modelling.<i>Main results.</i>Our results reveal significantly more negative TEPs when feedback is not presented from 40 ms to 100 ms post-TMS over frontal and central channels. We also see significantly more positive later TEPs from 280-400 ms on the contra-lateral hemisphere motor and parietal channels when no feedback is presented. These results suggest differences in effective connectivity are induced by visual feedback of movement. We further find that the variation in one of these early TEPs (the N40) is reliably related to directed coherence.<i>Significance.</i>Taken together, these results indicate components of the TEPs serve as a measure of effective connectivity. Furthermore, our results also support the idea that effective connectivity is a dynamic process and, importantly, support the further use of TEPs in delineating region-to-region maps of changes in effective connectivity as a result of motor control feedback.

Journal of Neural EngineeringVol. 21(6)
University of Essex (GB), University of Helsinki (FI), University of Reading (GB), Aalto University (FI)
Openalex Percentile: Top 76%
EEG and Brain-Computer Interfaces
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