Biology subjects

Souza, V. H.

Publications and source records attributed to Souza, V. H..

18 recordsLinked to original sources

bioRxiv2026

Adaptive Bayesian localization of motor representation areas

Transcranial magnetic stimulation (TMS) enables non-invasive localization of cortical motor representations, with important clinical applications in presurgical planning. Existing methods either disregard spatial information about the TMS-induced electric field (E-field) or use acquisition schemes that do not leverage previously elicited motor responses to guide subsequent stimulation. We present an adaptive Bayesian localization method that combines real-time E-field optimization with per-trial probabilistic inference. The cortical origin of the motor responses is represented as a spatial probability distribution that is updated after each stimulus. Subsequent stimuli are then optimized to maximize the expected localization improvement given previous responses. We validated the method experimentally, using multi-locus TMS for adaptive localization and single-coil TMS as a non-adaptive reference with randomized coil placements. Across eight subjects, the adaptive protocol at least halved the number of stimuli required for stable localization compared to the randomized protocol, converging in 60 stimuli on average, with 95% highest-density regions often below 10 mm2 by 150 stimuli.

neuroscience↗

bioRxiv2026

Automated robotic control system for EEG-BCI-guided closed-loop TMS

Brain-state-guided and closed-loop transcranial magnetic stimulation (TMS) protocols have emerged as methods for decreasing the variability and increasing the therapeutic effectiveness of stimulation protocols. However, most existing brain-state-dependent TMS systems only control the timing of stimulation, while the location is fixed and manually adjusted between blocks or sessions. This limits flexible targeting of distributed networks. We developed a system that jointly manages TMS pulse timing and location automatically controlled by an electroencephalography (EEG)-based brain- computer interface (BCI). A machine-learning algorithm infers the brain state in real time to guide the robotic coil placement and target. We present a proof-of-concept study in which a BCI controlled both the target site and the timing of TMS. A pre-trained convolutional neural network discriminated between resting state and movements performed with the right or left hand; the classifier output determined the hemisphere in which primary-motor-cortex hand area was stimulated and when. Preprocessing and decoding of 2-s EEG segments required 150 ms, and the robot took 7.5 s to move from the vertex home position to the predefined motor targets. The EEG-BCI-guided robotic TMS system expands the toolkit for brain-state-dependent and closed-loop neurostimulation by enabling control of stimulus location based on volitional brain activity. Thus, the system can benefit both neuroscience research and clinical neuromodulation applications. A prominent application of the system is automatically controlling spinal cord injury or motor disorder TMS rehabilitation with motor imagery, optimizing stimulation timing to the brain state producing optimal rehabilitation results.

neuroscience↗

bioRxiv2026

TMS-EEG Indices to Define Local Cortical Excitability Thresholds

IntroductionTranscranial magnetic stimulation (TMS) is widely employed to treat various psychiatric and neurological disorders. However, TMS protocols typically rely on generalizations, particularly in selecting stimulation intensities, leading to suboptimal and variable outcomes. Combining TMS with electroencephalography (EEG) offers a potential solution by allowing direct monitoring of stimulation effects. In this study, we investigate how features of the TMS-EEG signal change with intensity to identify thresholds implying qualitative shifts in the brain response. MethodsWe stimulated eight subjects at both the primary motor cortex (M1) and the pre-supplementary motor area (pre-SMA) with navigated TMS at 15 closely spaced intensities and measured TMS-evoked EEG responses (TMS-evoked potential, TEP) with 60 trials per intensity. TEP thresholds were identified with three methods: by selecting the intensity where the TEP peak-to-peak exceeds 6 V, or by fitting either piecewise-linear or sigmoid curves into the power spectral density (PSD) frequency components to identify nonlinear intensity behavior. ResultsThe identified TEP thresholds varied depending on subject, target, and identification method. In M1, the thresholds attained with the fixed-amplitude and piecewise PSD fit methods averaged around the motor threshold, and in pre-SMA around 120% of the motor threshold. The TEP thresholds yielded by the sigmoid fit method were higher in intensity, and least consistent between subjects. ConclusionsOur findings support the hypothesis that detectable changes in EEG patterns occur at specific TMS intensities. These results provide a basis for individualized stimulation dosing, potentially enhancing therapeutic efficacy and reliability. Future research should focus on refining these methods and validating their clinical applicability across diverse conditions and patient populations.

neuroscience↗

bioRxiv2025

Fast and standardized motor-hotspot determination with automated TMS mapping

Determining the optimal stimulation target for motor responses (motor hotspot) and the required intensity for reliably eliciting said responses (motor threshold) are common procedures in transcranial magnetic stimulation (TMS) research and treatments. However, the procedures for determining them are user-dependent, slow, and lack standardization, leading to long stimulation sessions with potentially inadequate outcomes. Partially automated algorithms for determining the motor threshold have been developed, but the motor hotspot is still largely mapped by hand. Automating the hotspot mapping will accelerate the process and improve standardization and accuracy. We developed a fully automated algorithm for finding the motor hotspot with multi-locus TMS and Bayesian optimization. Tested online in five healthy participants, the algorithm located motor hotspots with (mean {+/-} 95% CI) 2.1 {+/-} 0.7 mm and 6 {+/-} 2{degrees} difference from the global best target with only (mean) 47 stimuli. This is a significant improvement from previous motor-mapping algorithms, which do not optimize for stimulation location and orientation simultaneously. This accurate, fast, and user-independent procedure paves the way for faster experimental processes and more streamlined clinical applications.

neuroscience↗

bioRxiv2025

The dependency of TMS-evoked potentials on electric-field orientation in the cortex

Transcranial magnetic stimulation (TMS) stimulates the brain by electromagnetic induction. The outcome depends on multiple stimulation parameters such as the induced electric-field pattern (in particular, the location of the peak field and its orientation), intensity and timing. However, it is not clear how the TMS-evoked responses are affected by all the stimulation parameters. This study elucidates the dependency of the TMS-evoked electroencephalography (EEG) responses on the orientation of the stimulating electric field. To achieve this, we analysed a dataset from six subjects who were given pulses with 36 stimulus orientations to the pre-supplementary motor area (pre-SMA). The TMS-evoked potentials (TEPs) and induced oscillations were analysed with cluster-based statistics. Source estimation was performed to assess the effects of stimulus orientation on the TMS-evoked signal propagation. The amplitudes of the early peaks (20 and 40 ms after the TMS pulse) strongly depended on the electric field orientation. Our analysis suggested orientation dependency up to 100 ms post-stimulus in most subjects, indicating changes in stimulation efficacy and potential changes in signal propagation from the stimulated site. These results suggest that different orientations may perturb different networks. Thus, the orientation is a crucial parameter for the stimulation outcome and should be adjusted according to the cortical network under investigation.

neuroscience↗

bioRxiv2024

Optimization of TMS target engagement: novel evidence based on combined TMS-EEG and dMRI tractography of brain circuitry

Neuromodulation is based on the principle that brain stimulation produces plastic changes in cerebral circuitry. Given the intersubject structural and functional variability, neuromodulation has a personalized effect in the brain. Moreover, because of cerebral dominance and interhemispheric functional and structural differences in the same individual, the characterization of specific brain circuitries involved is currently not feasible. This notion is extremely important for neuromodulation treatments applied in neuropsychiatry. Specifically, the efficacy of the neuromodulation treatments is critically dependent on the anatomical precision of the brain target and the circuitry which has been affected. However, a complete understanding of how the brain behaves under stimulation needs a combined characterization of its neurophysiological response. This can be achieved by TMS-EEG guided by current multimodal neuroimaging techniques in real time. Herein, we present novel data based on dMRI tractography-guided TMS-EEG on one healthy young adult volunteer.

neuroscience↗

bioRxiv2024

Characterizing an electronic-robotic targeting platform for precise and fast brain stimulation with multi-locus transcranial magnetic stimulation

1.BackgroundMulti-locus TMS (mTMS) enables precise electronic control of brain stimulation targeting, eliminating the need for physical coil movement. However, with a small number of coils, the stimulation area is constrained, and manually handling the coil array is cumbersome. Combining electronic mTMS targeting with robotics will enable automated, user-independent, and precise brain stimulation protocols. ObjectiveCharacterizing an open-source electronic-robotic mTMS platform for rapid and accurate brain stimulation targeting. MethodsWe developed an automated robotic mTMS positioning platform. The accuracy of the system was quantified with a TMS characterizer that measures the TMS-induced electric field on a spherical cortex model. We used a 5-coil mTMS device equipped with a set of five coils coupled to a collaborative robot. The induced electric-field distortion generated by robot coupling was evaluated for each coil. We compared the accuracy of robotic-electronic targeting by repositioning the mTMS coil set with the robotic and the conventional manual positioning. ResultsOur collaborative robot-based system offers submillimeter precision and autonomy in positioning mTMS coil sets. The electronic-robotic mTMS platform was approximately 1.8 mm and 1.0{degrees} more accurate than the conventional manual positioning. Integrating robotics and mTMS automates brain stimulation procedures, resulting in minimal reliance on user expertise and subjective analysis. ConclusionOur open-source platform combining rapid mTMS targeting with robotic precision enhances the safety and reproducibility of brain stimulation techniques, enabling more efficient and reliable outcomes than previous techniques.

neuroscience↗

bioRxiv2023

A multi-channel TMS system enabling accurate stimulus orientation control during concurrent ultra-high-field MRI for preclinical applications

Monitoring cortical responses to neuromodulation protocols on preclinical models can elucidate fundamental mechanisms of brain function. Concurrent brain stimulation and imaging is challenging, usually compromising spatiotemporal resolution, accuracy, and versatility. Here we report a non-invasive brain stimulation system with electronic control of neuromodulation parameters in a 9.4-T magnetic resonance imaging (MRI) environment. In the imaging scanner, transcranial magnetic stimulation is delivered with a set of two coils and the MRI signals are recorded with a radiofrequency coil. The coil set provides millisecond-scale electronic control of the stimulus orientation with 1{degrees} resolution. Without physically rotating the coils, we evoked orientation-specific muscle responses after cortical stimulation on an anesthetized rat. We show that the stimulation pulses do not affect the anatomical imaging quality, and imaging signals are disrupted only if recorded before 10 ms after pulse delivery. Concurrent electronically targeted brain stimulation and neuroimaging sets the stage for the causal investigation of whole-brain network functions, endorsing more efficient treatment protocols.

neuroscience↗

bioRxiv2023

Directional Sensitivity of Cortical Neurons Towards TMS Induced Electric Fields

We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 245 small, nested, and large basket cells from layer 4, and 30 PC from layer 5 with different morphologies for deriving average models. With these models, it is possible to efficiently estimate the stimulation thresholds depending on the underlying electric field distribution in the brain, without having to implement and compute complex neuron compartment models. The stimulation thresholds were determined by exposing the neurons to TMS-induced electric fields with different angles, intensities, pulse waveforms, and field decays along the somato-dendritic axis. The derived average response models were verified by reference simulations using a high-resolution realistic head model containing several million neurons. Differences of only 1-2% between the average model and the average response of the reference cells were observed, while the computation time was only a fraction of a second compared to several weeks using the cells. Finally, we compared the model behavior to TMS experiments and observed high correspondence to the orientation sensitivity of motor evoked potentials. The derived models were compared to the classical cortical column cosine model and to simplified ball-and-stick neurons. It was shown that both models oversimplify the complex interplay between the electric field and the neurons and do not adequately represent the directional sensitivity of the different cell types. The derived models are simple to apply and only require the TMS induced electric field in the brain as input variable. The models and code are available to the general public in open-source repositories for integration into TMS studies to estimate the expected stimulation thresholds for an improved dosing and treatment planning in the future.

neuroscience↗

bioRxiv2023

Real-time tractography-assisted neuronavigation for TMS

BackgroundState-of-the-art navigated transcranial magnetic stimulation (nTMS) systems can display the TMS coil position relative to the structural magnetic resonance image (MRI) of the subjects brain and calculate the induced electric field. However, the local effect of TMS propagates via the white-matter network to different areas of the brain, and currently there is no commercial or research neuronavigation system that can highlight in real time the brains structural connections during TMS. ObjectiveTo develop a real-time tractography-assisted TMS neuronavigation system and investigate its feasibility. MethodWe propose a modular framework that seamlessly integrates offline (preparatory) analysis of diffusion MRI data with online (real-time) tractography. For tractography and neuronavigation we combine our custom software Trekker and InVesalius, respectively. We evaluate the feasibility of our system by comparing online and offline tractography results in terms of streamline count and their overlap. ResultsA real-time tractography-assisted TMS neuronavigation system is developed. Key features include the application of state-of-the-art tractography practices, the ability to tune tractography parameters on the fly, and the display of thousands of new streamlines every few seconds using a novel uncertainty visualization technique. We demonstrate in a video the feasibility and quantitatively show the agreement with offline filtered streamlines. ConclusionReal-time tractography-assisted TMS neuronavigation is feasible. With our system, it is possible to target specific brain regions based on their structural connectivity, and to aim for the fiber tracts that make up the brains networks.

neuroscience↗

bioRxiv2021

Local brain-state dependency of effective connectivity: evidence from TMS-EEG

BackgroundSpontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). If not controlled for, they might increase variability in responses and mask meaningful changes in the signals of interest when studying the brain with TMS combined with electroencephalography (TMS-EEG). To address this challenge in future closed-loop stimulation paradigms, we need to understand how spontaneous oscillations affect TMS-evoked responses. ObjectiveTo describe the effect of the pre-stimulus phase of cortical mu (8-13 Hz) and beta (13-30 Hz) oscillations on TMS-induced effective connectivity patterns. MethodsWe applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes. ResultsPhase had significant effects on the GMFA in 11 out of 12 datasets (3 subjects x 2 stimulation sites x 2 frequency bands). Seven of the datasets showed significant differences in the time range 15-50 ms, nine in 50-150 ms, and eight after 150 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity. ConclusionsTMS-evoked effective connectivity appears to depend on the phase of local cortical oscillations at the stimulated site. This may be crucial for efficient design of future brain-state-dependent and closed-loop stimulation paradigms.

neuroscience↗

bioRxiv2021

Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation

BackgroundTranscranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer. ObjectiveTo develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region. MethodsWe designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand. ResultsThe transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum. ConclusionThe developed mTMS system enables electronically targeted brain stimulation within a cortical region.

neuroscience↗

bioRxiv2021

Synergic Renoprotective Effects Of Combined ASC Therapy With RAAS Blockade In Experimental Advanced CKD

Global prevalence of chronic kidney disease (CKD) has increased considerably in the recent decades. Overactivity of the renin-angiotensin-aldosterone system (RAAS), associated to renal inflammation and fibrosis contribute to its evolution. The treatments currently employed to control CKD progression are limited and mainly based on the pharmacological inhibition of RAAS, associated with diuretics and immunosuppressive drugs. However, this conservative management promotes only partial deceleration of CKD evolution, and does not completely avoid the progression of the disease and the loss of renal function, which motivates the medical and scientific community to investigate new therapeutic approaches to detain renal inflammation / fibrosis and CKD progression. Recent studies have shown the application of mesenchymal stem cells (mSC) to exert beneficial effects on the renal tissue of animals submitted to experimental models of CKD. In this context, the aim of the present study was to evaluate the effects of subcapsular application of adipose tissue-derived mSC (ASC) in rats submitted to the 5/6 renal ablation model, 15 days after the establishment of CKD, when the nephropathy was already severe. We also verify whether ASC associated to Losartan, would promote greater renoprotection when compared to the respective monotherapies. Animals were followed until 30 days of CKD, when body weight, systolic blood pressure, biochemical, histological, immunohistochemical and gene expression analysis were performed. The combination of ASC and Losartan was more effective than Losartan monotherapy in reducing systolic blood pressure and glomerulosclerosis, and also promoted the complete normalization of proteinuria and albuminuria, a significant reduction in renal interstitial macrophage infiltration and downregulation of renal IL-6 gene expression. The beneficial effects of ACS are possibly due to the immunomodulatory and anti-inflammatory role of factors secreted by these cells, modulating the local immune response. Although studies are still required, our results demonstrated that a subcapsular inoculation of ASC, associated with the administration of Losartan, exerted additional renoprotective effect in rats submitted to a severe model of established CKD, when compared to Losartan monotherapy, thus suggesting ASC may be a potential adjuvant to RAAS-blockade therapy currently employed in the conservative management of CKD.

physiology↗

bioRxiv2021

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

BackgroundTranscranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. ObjectiveTo develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). MethodsWe developed an automated closed-loop TMS-EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS- EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. ResultsThe validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. ConclusionOptimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity.

bioengineering↗

bioRxiv2021

Trade-off between stimulation focality and the number of coils in multi-locus transcranial magnetic stimulation

ObjectiveCoils designed for transcranial magnetic stimulation (TMS) must incorporate trade-offs between the required electrical power or energy, focality and depth penetration of the induced electric field (E-field), coil size, and mechanical properties of the coil, as all of them cannot be optimally met at the same time. In multi-locus TMS (mTMS), a transducer consisting of several coils allows electronically targeted stimulation of the cortex without physically moving a coil. In this study, we aimed to investigate the relationship between the number of coils in an mTMS transducer, the focality of the induced E-field, and the extent of the cortical region within which the location and orientation of the maximum of the induced E-field can be controlled. ApproachWe applied convex optimization to design planar and spherically curved mTMS transducers of different E-field focalities and analyzed their properties. We characterized the trade-off between the focality of the induced E-field and the extent of the cortical region that can be stimulated with an mTMS transducer with a given number of coils. Main resultsAt the expense of the E-field focality, one can, with the same number of coils, design an mTMS transducer that can control the location and orientation of the peak of the induced E-field within a wider cortical region. SignificanceWith E-fields of moderate focality, the problem of electronically targeted TMS becomes considerably easier compared with highly focal E-fields; this may speed up the development of mTMS and the emergence of new clinical and research applications.

neuroscience↗

bioRxiv2021

Probing the orientation specificity of excitatory and inhibitory circuitries in the primary motor cortex with multi-channel TMS

BackgroundThe electric field orientation is a crucial parameter for optimizing the excitation of neuronal tissue in transcranial magnetic stimulation (TMS). Yet, the effects of stimulus orientation on the short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) paradigms are poorly known, mainly due to significant technical challenges in manipulating the TMS-induced stimulus orientation within milliseconds. ObjectiveOur aim is to assess the effect of the TMS-induced stimulus orientation on the SICI and ICF paradigms and search for the optimal orientations to maximize the facilitation and suppression of the motor evoked potentials (MEP). MethodsWe applied paired-pulse multi-channel TMS in healthy subjects to generate SICI and ICF with conditioning and test pulses in the same, opposite, and perpendicular orientations to each other. The conditioning- and test-stimulus intensities were 80% and 110% of the resting motor threshold, respectively. ResultsBoth SICI and ICF were significantly affected by the conditioning- and test-stimulus orientation. MEP suppression and facilitation were strongest with both pulses delivered in the same direction. SICI with a 2.5-ms and ICF with a 6.0-ms interstimulus interval (ISI) were more sensitive to changes in stimulus orientation compared with SICI at 0.5- and ICF at 8.0-ms ISIs, respectively. ConclusionOur findings provide evidence that SICI and ICF at specific ISIs are mediated by distinct mechanisms. Such mechanisms exhibit a preferential orientation depending on the anatomical and morphological arrangement of inhibitory and excitatory neuronal populations. We also demonstrate that the SICI and ICF can be maximized by adjusting the TMS-induced electric field orientation.

neuroscience↗

bioRxiv2021

Fine multi-coil electronic control of transcranial magnetic stimulation: effects of stimulus orientation and intensity

BackgroundTranscranial magnetic stimulation (TMS) coils allow only a slow, mechanical adjustment of the stimulating electric field (E-field) orientation in the cerebral tissue. Fast E-field control is needed to synchronize the stimulation with the ongoing brain activity. Also, empirical models that fully describe the relationship between evoked responses and the stimulus orientation and intensity are still missing. ObjectiveWe aimed to (1) develop a TMS transducer for manipulating the E-field orientation electronically with high accuracy at the neuronally meaningful millisecond-level time scale and (2) devise and validate a physiologically based model describing the orientation selectivity of neuronal excitability. MethodsWe designed and manufactured a two-coil TMS transducer. The coil windings were computed with a minimum-energy optimization procedure, and the transducer was controlled with our custom-made electronics. The electronic E-field control was verified with a TMS characterizer. The motor evoked potential amplitude and latency of a hand muscle were mapped in 3{degrees} steps of the stimulus orientation in 16 healthy subjects for three stimulation intensities. We fitted a logistic model to the motor response amplitude. ResultsThe two-coil TMS transducer allows one to manipulate the pulse orientation accurately without manual coil movement. The motor response amplitude followed a logistic function of the stimulus orientation; this dependency was strongly affected by the stimulus intensity. ConclusionThe developed electronic control of the E-field orientation allows exploring new stimulation paradigms and probing neuronal mechanisms. The presented model helps to disentangle the neuronal mechanisms of brain function and guide future non-invasive stimulation protocols.

neuroscience↗

bioRxiv2021

Forearm and hand muscles exhibit high coactivation and overlapping of cortical motor representations

Most of the motor mapping procedures using navigated transcranial magnetic stimulation (nTMS) follow the conventional somatotopic organization of the primary motor cortex (M1) by assessing the representation of a particular target muscle, disregarding the possible coactivation of synergistic muscles. In turn, multiple reports describe a functional organization of the M1 with an overlapping among motor representations acting together to execute movements. In this context, the overlap degree among cortical representations of synergistic hand and forearm muscles remains an open question. This study aimed to evaluate the muscle coactivation and representation overlapping common to the grasping movement and its dependence on the stimulation parameters. The nTMS motor maps were obtained from one carpal muscle and two intrinsic hand muscles during rest. We quantified the overlapping motor maps in size (area and volume overlap degree) and topography (similarity and centroids Euclidean distance) parameters. We demonstrated that these muscle representations are highly overlapped and similar in shape. The overlap degrees involving the forearm muscle were significantly higher than only among the intrinsic hand muscles. Moreover, the stimulation intensity had a stronger effect on the size compared to the topography parameters. Our study contributes to a more detailed cortical motor representation towards a synergistic, functional arrangement of M1. Understanding the muscle group coactivation may provide more accurate motor maps when delineating the eloquent brain tissue during pre-surgical planning.

neuroscience↗