Anatomical and functional correlates of cortical motor threshold of the dominant hand

Rosso, Charlotte; Perlbarg, Vincent; Valabrègue, Romain; Obadia, Mickaël Alexandre; Kemlin-Méchin, Claire; Moulton, Eric; Leder, Sara; Meunier, Sabine; Lamy, Jean‐Charles

doi:10.1016/j.brs.2017.05.005

Cited by 26 publications

(76 citation statements)

References 49 publications

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“…Using Dynamical Causal Modeling, an MRI technique that allows making inference between regions during a task, Sarfeld et al ( 51 ) demonstrated that the higher the excitability of left M1 the stronger the coupling between left supplementary motor area and M1. In line with these results, we demonstrated in a previous study ( 52 ) that rMT was in part explained by the functional connectivity of the premotor cortex and M1. These results underlined the major role of the premotor areas and the cortico-cortical connections toward M1 in the excitation of the CST fibers (through trans-synaptic pathways).…”

Section: Rmt As a Biomarker Of Stroke Hand Functionsupporting

confidence: 90%

Does Resting Motor Threshold Predict Motor Hand Recovery After Stroke?

Rosso

Lamy

2018

Front. Neurol.

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Background: Resting Motor threshold (rMT) is one of the measurement obtained by Transcranial Magnetic Stimulation (TMS) that reflects corticospinal excitability. As a functional marker of the corticospinal pathway, the question arises whether rMT is a suitable biomarker for predicting post-stroke upper limb function. To that aim, we conducted a systematic review of relevant studies that investigated the clinical significance of rMT in stroke survivors by using correlations between upper limb motor scores and rMT.Methods: Studies that reported correlations between upper limb motor function and rMT as a measure of corticospinal excitability in distal arm muscle were identified via a literature search in stroke patients. Two authors extracted the data using a home-made specific form. Subgroup analyses were carried out with patients classified with respect to time post-stroke onset (early vs. chronic stage) and stroke location (cortical, subcortical, or cortico-subcortical). Methodological quality of the study was also evaluated by a published checklist.Results: Eighteen studies with 22 groups (n = 508 stroke patients) were included in this systematic review. Mean methodological quality score was 14.75/24. rMT was often correlated with motor function or hand dexterity (n = 15/22, 68%), explaining on average 31% of the variance of the motor score. Moreover, the results did not seem impacted if patients were examined at the early or chronic stages of stroke. Two findings could not be properly interpreted: (i) the fact that the rMT is an independent predictor of motor function as several confounding factors are well-established, and, (ii) whether the stroke location impacts this prediction.Conclusion: Most of the studies found a correlation between rMT and upper limb motor function after stroke. However, it is still unclear if rMT is an independent predictor of upper limb motor function when taking into account for age, time post stroke onset and level of corticospinal tract damage as confounding factors. Clear-cut conclusions could not be drawn at that time but our results suggest that rMT could be a suitable candidate although future investigations are needed.Systematic Review Registration Number: (https://www.crd.york.ac.uk/prospero/): ID 114317.

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Section: Rmt As a Biomarker Of Stroke Hand Functionsupporting

confidence: 90%

Does Resting Motor Threshold Predict Motor Hand Recovery After Stroke?

Rosso

Lamy

2018

Front. Neurol.

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“…Still, because of the large number of anatomical factors that are related to stimulation and the degree of variance left unexplained by gross non-brain factors, finite element simulations are well suited to quantify differences in the induced E-Field from TMS. Moving beyond biophysics, factors such as state-dependent features (Luber et al, 2017; Siebner et al, 2009) and functional organization (Drysdale et al, 2017; Rosso et al, 2017; Wang et al, 2015) will also affect stimulation outcomes. Although these biological variables unrelated to current modeling efforts will affect stimulation effects, understanding how the site of stimulation differs between individuals is an important step to understand biological contributors to inter-subject variability.…”

Section: Resultsmentioning

confidence: 99%

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline

Lee

Rastogi

Hadimani

et al. 2018

Clinical Neurophysiology

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“…To assess the relationship between the RMT and all included predictors alone, we replicated the correlation analyses of Rosso et al (2017) for the data of the dominant hemisphere. Correlation coefficients, 95%-confidence intervals (CIs) and p-values are stated in Table 1.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies (Bhandari et al 2016;Latorre et al 2019;Wassermann 2002) have shown a substantial variability in the RMT between and within healthy subjects. While the impact of methodological factors such as the TMS device, use of neuronavigation software and algorithm used to assess the RMT is established, the impact of structural and functional factors is still poorly understood (Herbsman et al 2009;Hübers et al 2012;Rosso et al 2017). Recent studies have shown a positive correlation of the RMT with the age of participants after maturation of the white mater, a relationship potentially mediated by a decreasing cortical volume and increasing coil-cortex distance (CCD; Bhandari et al 2016;Rosso et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…We deviated from their paradigm only by using an atlas for delineation of the seed regions and focusing on the FC analysis, thus not investigating the impact of FA. Rosso et al (2017) were contacted to inquire about details of the fMRI preprocessing and experimental setting, but were not included in any other way in this study. After this initial contact, we further included an exploratory analysis of the impact of the timing between the MRI and TMS procedure on our results.…”

Section: Introductionmentioning

confidence: 99%

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No impact of functional connectivity of the motor system on the resting motor threshold: A replication study

Engelhardt

Komnenić

Roth

et al. 2020

Preprint

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The physiological mechanisms of corticospinal excitability and factors influencing its measurement with transcranial magnetic stimulation are still poorly understood. A recent study reported an impact of functional connectivity between the primary motor cortex and dorsal premotor cortex on the resting motor threshold of the dominant hemisphere. We aimed to replicate these findings in a larger sample of 38 healthy right-handed subjects with data from both hemispheres. Resting-state functional connectivity was assessed between the primary motor cortex and five a-priori defined motor-relevant regions on each hemisphere as well as interhemispherically between both primary motor cortices. Following the procedure by the original authors, we included age, the cortical grey matter volume and coil to cortex distance as further predictors in the analysis. We report replication models for the dominant hemisphere as well as an extension to data from both hemispheres and support the results with Bayes factors. Functional connectivity between the primary motor cortex and dorsal premotor cortex did not explain variability in the resting motor threshold and we obtained moderate evidence for the absence of this effect. In contrast, coil to cortex distance could be confirmed as an important predictor with strong evidence. These findings contradict the previously proposed effect, thus questioning the notion of the dorsal premotor cortex playing a major role in modifying corticospinal excitability.

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Anatomical and functional correlates of cortical motor threshold of the dominant hand

Cited by 26 publications

References 49 publications

Does Resting Motor Threshold Predict Motor Hand Recovery After Stroke?

Does Resting Motor Threshold Predict Motor Hand Recovery After Stroke?

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline

No impact of functional connectivity of the motor system on the resting motor threshold: A replication study

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