Mapping cortical hand motor representation using TMS: A method to assess brain plasticity and a surrogate marker for recovery of function after stroke?

Lüdemann-Podubecká, Jitka; Nowak, Dennis A.

doi:10.1016/j.neubiorev.2016.07.006

Cited by 31 publications

(34 citation statements)

References 48 publications

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“…TMS is frequently used in combination with MRI-guided neuronavigation, which allows mapping of the stimulated neuroanatomical targets that evoke responses in specific muscles. [3]. Using a standardized grid of stimulation targets, the functional motor areas of different muscles can be delineated systematically, based on the amplitudes of the MEPs as a function of stimulation location.…”

Section: Introductionmentioning

confidence: 99%

Outcome of TMS-based motor mapping depends on TMS current direction

Mandija

et al. 2018

Preprint

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Navigated transcranial magnetic stimulation (TMS) in combination with electromyography (EMG) recordings can be used to map the brain regions in which TMS evokes motor-evoked potentials (MEPs) in certain muscles. Navigated TMS (nTMS) is used increasingly to identify the functional motor area of different muscles for clinical applications, including neurosurgical planning. However, the accuracy of TMS-based mapping of functional motor areas may depend on the TMS-induced current direction due to anisotropic cortical morphology, complicating association of the functional motor maps with neuroanatomical structures. Furthermore, it is not clear how well nTMS can distinguish nearby muscle representations on the cortical surface. We therefore investigated the functional motor maps obtained with posterior-to-anterior (PA) and lateral-to-medial (LM) TMS-induced currents within a spatially defined area by stimulating targets in a grid of locations over the left primary motor cortex in 8 healthy participants. Results were compared to functional MRI (fMRI) activation maps obtained using a voluntary opposing thumb movement task. We found that TMS applied with PA-induced currents identifies a motor area that is located significantly more anterior (8.7 -10.4 mm depending on the muscle) with respect to an MEP motor area identified using LM-induced currents for the same muscle. Motor maps obtained with LM-induced currents show more overlap with the motor map identified using fMRI compared to PA-induced currents. In conclusion, the spatial representation of the MEP motor map identified by TMS is dependent on the direction of the induced current. These findings suggest that the application of nTMS using an LM-induced current direction corresponds best with the hand motor area as measured with fMRI.

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Section: Introductionmentioning

confidence: 99%

Outcome of TMS-based motor mapping depends on TMS current direction

Mandija

et al. 2018

Preprint

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“…The existence of a robust within-limb somatotopy in the primary motor cortex (M1), obtained with TMS, is still debated, although -homunculus-like‖ TMS motor cortical maps were described from the earliest years of TMS mapping (Gentner & Classen, 2006;Metman, Bellevich, Jones, Barber, & Streletz, 1993). A commonly reported output for different muscles` TMS MCRs interaction is the distances/shifts between the COGs (Dubbioso, Raffin, Karabanov, Thielscher, & Siebner, 2017;Schabrun, Stinear, Byblow, & Ridding, 2009; Tyč, Boyadjian, Allam, & Brasil-Neto, 2012) or hotspots (Bashir et al, 2013;Lüdemann-Podubecká & Nowak, 2016) of these different muscles` MCRs. To the best of our knowledge, the clearest recent demonstration of the somatotopy gradient of the hand TMS MCRs has been made using -along-sulcus‖ TMS mapping, when one investigates MEPs produced by stimulation only along the central sulcus, taking into account its shape (Dubbioso et al, 2017;Raffin et al, 2015;Raffin & Siebner, 2019).…”

Section: Somatotopy Gradientmentioning

confidence: 99%

“…When MEPs from the stimulation of many cortical points are acquired, the resulting output is referred to as cortical muscle representation (MCR) (Bashir, Perez, Horvath, & Pascual-Leone, 2013;de Carvalho, Miranda, Luis, & Ducla-Soares, 1999), also known as TMS cortical motor map (Kraus & Gharabaghi, 2015;Novikov, Nazarova, & Nikulin, 2018). There are numerous studies showing that the MCR parameters such as excitability, size and topography reflect functionally relevant features of the motor cortex organization in healthy people (Beaulieu, Flamand, Massé-Alarie, & Schneider, 2017;Gentner & Classen, 2006;Nazarova, Novikov, Nikulin, & Ivanova, 2020;Tyč & Boyadjian, 2011) and in patients with motor pathology such as stroke (Lüdemann-Podubecká & Nowak, 2016;Yarossi et al, 2019), amyotrophic lateral sclerosis (Chervyakov et al, 2015;de Carvalho et al, 1999), dystonia (Schabrun, Stinear, Byblow, & Ridding, 2009) etc. Considering the nTMS mapping of multiple muscles, the existence of the somatotopy gradient for MCRs, along with their extensive overlap, has been discussed from the earliest TMS studies (Gentner & Classen, 2006;Metman, Bellevich, Jones, Barber, & Streletz, 1993).…”

Section: Introductionmentioning

confidence: 99%

TMS cortical mapping of multiple muscles: absolute and relative test-retest reliability

Nazarova

Pavel

Олеговна

et al. 2020

Preprint

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The spatial accuracy of TMS may be as small as a few millimeters. Despite such great potential, navigated TMS (nTMS) mapping is still underused for the assessment of motor plasticity, particularly in clinical settings. Here we investigate the within-limb somatotopy gradient as well as absolute and relative reliability of three hand muscle cortical representations (MCRs) using a comprehensive grid-based sulcus-informed nTMS motor mapping. We enrolled 22 young healthy male volunteers. Two nTMS mapping sessions were separated by 5-10 days. Motor evoked potentials were obtained from abductor pollicis brevis (APB), abductor digiti minimi, and extensor digitorum communis. In addition to individual MRI-based analysis, we studied MNI normalized MCRs. For the reliability assessment, we calculated intra-class correlation and the smallest detectable change. Our results revealed a somatotopy gradient reflected by APB MCR having the most lateral location. Reliability analysis showed that the commonly used metrics of MCRs, such as areas, volumes, centers of gravity (COGs), and hotspots had a high relative and low absolute reliability for all three muscles. For within-limb TMS somatotopy, the most common metrics such as the shifts between MCR COGs and hotspots had poor relative reliability. However, overlaps between different muscle MCRs were highly reliable. We thus provide novel evidence that inter-muscle MCR interaction can be reliably traced using MCR overlaps while shifts between the COGs and hotspots of different MCRs are not suitable for this purpose. Our results have implications for the interpretation of nTMS motor mapping results in healthy subjects and patients with neurological conditions.

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“…Its ability to localize motor eloquent cortical areas has found successful applications in preoperative planning [4,5]. Additionally, a growing body of literature is concerned with the use of nTMS mapping for assessing the state of the motor system and its plastic changes during learning of new skills [6–9], in neurological diseases, such as stroke [10], dystonia [11], spinal cord injury [12,13], amyotrophic lateral sclerosis [14], as well as in the course of treatment [15]. For identifying the possibly subtle differences in motor maps, it is essential to make the method precise and reliable.…”

Section: Introductionmentioning

confidence: 99%

“…One of the most frequently used approaches is based on a predefined grid of cortical points with application of a fixed number of stimuli at each point [20,21]. The studies using this method are heterogeneous in terms of the number of grid cells, their size and the number of stimuli per cell [10,21–25]. Given the high variability of MEPs, the number of stimuli per cell is an important factor influencing the accuracy of the representation parameters [20,26].…”

Section: Introductionmentioning

confidence: 99%

Optimization of the navigated TMS mapping algorithm for accurate detection of plasticity and abnormalities in cortical muscle representations

Синицын

Chernyavskiy

Poydasheva

et al. 2019

Preprint

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Navigated TMS mapping of cortical muscle representations allows noninvasive assessment of the 11 state of a healthy or diseased motor system and monitoring its change with time. These applications are 12 hampered by the heterogeneity of existing mapping algorithms and the lack of detailed information about their 13 accuracy. We aimed to find an optimal motor evoked potential (MEP) sampling scheme in the grid-based 14 mapping algorithm in terms of the accuracy of muscle representation parameters. The APB muscles of eight 15 healthy subjects were mapped three times on consecutive days using a seven-by-seven grid with ten stimuli 16 per cell. The effect of the MEP variability on the parameter accuracy was assessed using bootstrapping. The 17 accuracy of representation parameters increased with the number of stimuli without saturation up to at least 18 ten stimuli per cell. The detailed sampling showed that the between-session representation area changes in the 19 absence of interventions were significantly larger than the within-session fluctuations and thus could not be 20 explained solely by the trial-to-trial variability of MEPs. The results demonstrate that the number of stimuli 21 has no universally optimal value and must be chosen by balancing the accuracy requirements with the mapping 22 time constraints in a given problem. 23

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Mapping cortical hand motor representation using TMS: A method to assess brain plasticity and a surrogate marker for recovery of function after stroke?

Cited by 31 publications

References 48 publications

Outcome of TMS-based motor mapping depends on TMS current direction

Outcome of TMS-based motor mapping depends on TMS current direction

TMS cortical mapping of multiple muscles: absolute and relative test-retest reliability

Optimization of the navigated TMS mapping algorithm for accurate detection of plasticity and abnormalities in cortical muscle representations

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