Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/38080
Title: Dual-site TMS as a tool to probe effective interactions within the motor network: a review
Authors: VAN MALDEREN, Shanti 
HEHL, Melina 
VERSTRAELEN, Stefanie 
Swinnen, Stephan P.
CUYPERS, Koen 
Issue Date: 2022
Publisher: 
Source: Reviews in the neurosciences, 0 (0)
Status: Early view
Abstract: Dual-site transcranial magnetic stimulation (ds-TMS) is well suited to investigate the causal effect of distant brain regions on the primary motor cortex, both at rest and during motor performance and learning. However, given the broad set of stimulation parameters, clarity about which parameters are most effective for identifying particular interactions is lacking. Here, evidence describing inter-and intra-hemispheric interactions during rest and in the context of motor tasks is reviewed. Our aims are threefold: (1) provide a detailed overview of ds-TMS literature regarding inter-and intra-hemispheric connectivity; (2) describe the applicability and contributions of these interactions to motor control, and; (3) discuss the practical implications and future directions. Of the 3659 studies screened, 109 were included and discussed. Overall, there is remarkable variability in the experimental context for assessing ds-TMS interactions, as well as in the use and reporting of stimulation parameters, hindering a quantitative comparison of results across studies. Further studies examining ds-TMS interactions in a systematic manner, and in which all critical parameters are carefully reported, are needed.
Keywords: connectivity;interhemispheric interactions;intrahemispheric interactions;motor network;trans- cranial magnetic stimulation
Document URI: http://hdl.handle.net/1942/38080
ISSN: 0334-1763
e-ISSN: 2191-0200
DOI: 10.1515/revneuro-2022-0020
ISI #: 000850037200001
Rights: Open Access. 2022 the author(s), published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 International License.
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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