Optimization of the Navigated TMS Mapping Algorithm for Accurate Estimation of Cortical Muscle Representation Characteristics

Abstract

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

Mapping of multiple muscles with transcranial magnetic stimulation: absolute and relative test–retest reliability

“…To our knowledge, this is the first work where the absolute reliability of multiple muscle MCRs was probed, using individual brain navigated TMS mapping for the whole motor cortex, in addition to the along-sulcus TMS mapping (Dubbioso et al, 2017;Raffin et al, 2015). Another feature of this study is its robust mapping design: we used up to 350 points per subject, because the literature about the necessary number of points for TMS motor mapping is contradictory: while some parameters of MCR were reported to be reliably traced already with 60 stimuli (van de Ruit et al, 2015), there have also been indications that accuracy of MCR parameters continued to increase without saturation up to a much higher number of stimuli (Nazarova et al, 2019;Sinitsyn et al, 2019).…”

“…Relative reliability reflects the degree of variation in position among participants over repeated measurements and, thus, allowing subjects/patients stratifying, while absolute reliability reflects the degree of variation in measurements for individuals, and, thus, allowing the interpretation of changes at the individual level (Atkinson & Nevill, 1998). Articles dedicated to TMS motor mapping reliability are mostly focused on the relative reliability (Cavaleri, Schabrun, & Chipchase, 2018;Forster, Limbart, Seifert, & Senft, 2014;Jonker et al, 2019;Kraus & Gharabaghi, 2016;Malcolm et al, 2006;McGregor et al, 2012;Ngomo, Leonard, Moffet, & Mercier, 2012;Pitkänen et al, 2017;Plowman-Prine, Triggs, Malcolm, & Rosenbek, 2008;Sankarasubramanian et al, 2015;Sinitsyn et al, 2019;Sollmann et al, 2013;van de Ruit, Perenboom, & Grey, 2015;Weiss et al, 2013;Wolf et al, 2004;Zdunczyk, Fleischmann, Schulz, Vajkoczy, & Picht, 2013), while absolute reliability has been investigated much less frequently (Jonker et al, 2019;Ngomo et al, 2012;Sankarasubramanian et al, 2015;van de Ruit et al, 2015).…”

Diagnostic capabilities of transcranial magnetic stimulation to predict motor recovery after a stroke

“…In this article we will present these 4 directions of the transcranial magnetic stimulation application to study motor system pathophysiology and to predict motor outcome in stroke, including both existing and developing approaches. [64][65][66][67][68][69][70][71][72][73][74].…”

Mapping of Motor Function with Neuronavigated Transcranial Magnetic Stimulation: A Review on Clinical Application in Brain Tumors and Methods for Ensuring Feasible Accuracy

“…From a methodological perspective, the nTMS parameters selected for motor mapping, such as the stimulation intensity (SI), number of applied stimuli, and the density of the applied stimulation grid, affect the outcome and accuracy of the motor mapping ( Figure 3 ) [ 24 , 25 , 26 , 27 ]. Specifically, optimal selection becomes especially important when quantitative parameters are drawn from the motor maps, e.g., to characterize the location of motor function or to define its extent on the cortex.…”

“…Quantitative mapping refers to those quantitative parameters derived from nTMS motor mapping, based on the recorded responses and location information related to the responses. The quantitative parameters in nTMS motor mapping include the locations of the motor hotspot and center of gravity (CoG), and area and volume of the motor map, which are all based on recorded amplitudes of motor-evoked potentials (MEPs) elicited by stimulation ( Figure 3 ) [ 24 , 25 , 26 , 27 ]. The motor hotspot location is often considered as the location of the maximum MEP amplitude response [ 28 , 29 ].…”