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Heemels RE, Ademi S, Hehl M. Test-retest reliability of intrahemispheric dorsal premotor and primary motor cortex dual-site TMS connectivity measures. Clin Neurophysiol 2024; 165:64-75. [PMID: 38959537 DOI: 10.1016/j.clinph.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 05/23/2024] [Accepted: 06/02/2024] [Indexed: 07/05/2024]
Abstract
OBJECTIVE Investigating the optimal interstimulus interval (ISI) and the 24-hour test-retest reliability for intrahemispheric dorsal premotor cortex (PMd) - primary motor cortex (M1) connectivity using dual-site transcranial magnetic stimulation (dsTMS). METHODS In 21 right-handed adults, left intrahemispheric PMd-M1 connectivity has been investigated with a stacked-coil dsTMS setup (conditioning stimulus: 75% of resting motor threshold; test stimulus: eliciting MEPs of 1-1.5 mV) at ISIs of 3, 5-8, and 10 ms. Additionally, M1-M1 short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) were investigated to assess comparability to standard paired-pulse setups. RESULTS Conditioning PMd led to significant inhibition of M1 output at ISIs of 3 and 5 ms, whereas 10 ms resulted in facilitation (all, p < 0.001), with a fair test-retest reliability for 3 (ICC: 0.47) and 6 ms (ICC: 0.44) ISIs. Replication of SICI (p < 0.001) and ICF (p = 0.017) was successful, with excellent test-retest reliability for SICI (ICC: 0.81). CONCLUSION This dsTMS setup can probe the inhibitory and facilitatory PMd-M1 connections, as well as reliably replicate SICI and ICF paradigms. SIGNIFICANCE The stacked-coil dsTMS setup for investigating intrahemispheric PMd-M1 connectivity offers promising possibilities to better understand motor control.
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Affiliation(s)
- Robin E Heemels
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium
| | - Sian Ademi
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium
| | - Melina Hehl
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium.
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Hehl M, Van Malderen S, Geraerts M, Meesen RLJ, Rothwell JC, Swinnen SP, Cuypers K. Probing intrahemispheric interactions with a novel dual-site TMS setup. Clin Neurophysiol 2024; 158:180-195. [PMID: 38232610 DOI: 10.1016/j.clinph.2023.12.128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/02/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024]
Abstract
OBJECTIVE Using dual-site transcranial magnetic stimulation (dsTMS), the effective connectivity between the primary motor cortex (M1) and adjacent brain areas such as the dorsal premotor cortex (PMd) can be investigated. However, stimulating two brain regions in close proximity (e.g., ±2.3 cm for intrahemispheric PMd-M1) is subject to considerable spatial restrictions that potentially can be overcome by combining two standard figure-of-eight coils in a novel dsTMS setup. METHODS After a technical evaluation of its induced electric fields, the dsTMS setup was tested in vivo (n = 23) by applying a short-interval intracortical inhibition (SICI) protocol. Additionally, the intrahemispheric PMd-M1 interaction was probed. E-field modelling was performed using SimNIBS. RESULTS The technical evaluation yielded no major alterations of the induced electric fields due to coil overlap. In vivo, the setup reliably elicited SICI. Investigating intrahemispheric PMd-M1 interactions was feasible (inter-stimulus interval 6 ms), resulting in modulation of M1 output. CONCLUSIONS The presented dsTMS setup provides a novel way to stimulate two adjacent brain regions with fewer technical and spatial limitations than previous attempts. SIGNIFICANCE This dsTMS setup enables more accurate and repeatable targeting of brain regions in close proximity and can facilitate innovation in the field of effective connectivity.
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Affiliation(s)
- Melina Hehl
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Shanti Van Malderen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Marc Geraerts
- Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Raf L J Meesen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom
| | - Stephan P Swinnen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium
| | - Koen Cuypers
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium.
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Van Hoornweder S, Nuyts M, Frieske J, Verstraelen S, Meesen RLJ, Caulfield KA. Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study. Neuroimage 2023; 281:120379. [PMID: 37716590 PMCID: PMC11008458 DOI: 10.1016/j.neuroimage.2023.120379] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/18/2023] [Accepted: 09/13/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing. OBJECTIVES This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures. METHODS Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals. RESULTS In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model. CONCLUSIONS Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.
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Affiliation(s)
- Sybren Van Hoornweder
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium.
| | - Marten Nuyts
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium
| | - Joana Frieske
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Stefanie Verstraelen
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium
| | - Raf L J Meesen
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Kevin A Caulfield
- Brain Stimulation Laboratory, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States.
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Van Malderen S, Hehl M, Verstraelen S, Swinnen SP, Cuypers K. Dual-site TMS as a tool to probe effective interactions within the motor network: a review. Rev Neurosci 2023; 34:129-221. [PMID: 36065080 DOI: 10.1515/revneuro-2022-0020] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 07/02/2022] [Indexed: 02/07/2023]
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.
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Affiliation(s)
- Shanti Van Malderen
- Department of Movement Sciences, Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Heverlee 3001, Belgium.,Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek 3590, Belgium
| | - Melina Hehl
- Department of Movement Sciences, Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Heverlee 3001, Belgium.,Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek 3590, Belgium
| | - Stefanie Verstraelen
- Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek 3590, Belgium
| | - Stephan P Swinnen
- Department of Movement Sciences, Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Heverlee 3001, Belgium.,KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium
| | - Koen Cuypers
- Department of Movement Sciences, Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Heverlee 3001, Belgium.,Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek 3590, Belgium
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Van Hoornweder S, Nuyts M, Frieske J, Verstraelen S, Meesen RLJ, Caulfield KA. A Systematic Review and Large-Scale tES and TMS Electric Field Modeling Study Reveals How Outcome Measure Selection Alters Results in a Person- and Montage-Specific Manner. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.22.529540. [PMID: 36865243 PMCID: PMC9980068 DOI: 10.1101/2023.02.22.529540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Background Electric field (E-field) modeling is a potent tool to examine the cortical effects of transcranial magnetic and electrical stimulation (TMS and tES, respectively) and to address the high variability in efficacy observed in the literature. However, outcome measures used to report E-field magnitude vary considerably and have not yet been compared in detail. Objectives The goal of this two-part study, encompassing a systematic review and modeling experiment, was to provide an overview of the different outcome measures used to report the magnitude of tES and TMS E-fields, and to conduct a direct comparison of these measures across different stimulation montages. Methods Three electronic databases were searched for tES and/or TMS studies reporting E-field magnitude. We extracted and discussed outcome measures in studies meeting the inclusion criteria. Additionally, outcome measures were compared via models of four common tES and two TMS modalities in 100 healthy younger adults. Results In the systematic review, we included 118 studies using 151 outcome measures related to E-field magnitude. Structural and spherical regions of interest (ROI) analyses and percentile-based whole-brain analyses were used most often. In the modeling analyses, we found that there was an average of only 6% overlap between ROI and percentile-based whole-brain analyses in the investigated volumes within the same person. The overlap between ROI and whole-brain percentiles was montage- and person-specific, with more focal montages such as 4Ã-1 and APPS-tES, and figure-of-eight TMS showing up to 73%, 60%, and 52% overlap between ROI and percentile approaches respectively. However, even in these cases, 27% or more of the analyzed volume still differed between outcome measures in every analyses. Conclusions The choice of outcome measures meaningfully alters the interpretation of tES and TMS E-field models. Well-considered outcome measure selection is imperative for accurate interpretation of results, valid between-study comparisons, and depends on stimulation focality and study goals. We formulated four recommendations to increase the quality and rigor of E-field modeling outcome measures. With these data and recommendations, we hope to guide future studies towards informed outcome measure selection, and improve the comparability of studies.
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