Reliability of robotic transcranial magnetic stimulation motor mapping

A Narrative Review of Stroke of Cortical Hand Knob Area

The cortical hand knob region of the brain is a knob-like segment of the precentral gyrus, projecting into the middle genu of the central sulcus. This anatomic landmark is responsible for intricate control of hand motor movements and has often been implicated in motor weakness following stroke. In some instances, damage to this area has been mistaken for peripheral causes of hand weakness. Our article aims to consolidate clinically relevant information on the cortical hand knob area in a comprehensive review to guide clinicians regarding diagnosis and treatment strategies. We conducted a systematic search within the Medline/PubMed database for reports of strokes in the cortical hand knob region. All studies were published electronically up until December 2023. The search was conducted using the keyword "hand knob". A total of 24 reports containing 150 patients were found. The mean and median ages were 65 and 67 years, respectively. Sixty-two percent of the individuals were male. According to the TOAST criteria for the classification of the stroke, 59 individuals had a stroke due to large-artery atherosclerosis, 8 had small-vessel occlusion, 20 had cardioembolism, 25 were determined, and 38 were undetermined. The most common etiologies for stroke in the hand knob area can be attributed to large vessel occlusions, small vessel occlusions, or cardioembolism. Presentations following damage to this area can mimic ulnar, median, or radial neuropathy as well. Our comprehensive review serves as a resource for recognizing and managing stroke in the cortical hand knob area.

Semi-automated motor hotspot search (SAMHS): a framework toward an optimised approach for motor hotspot identification

Background

Motor hotspot identification represents the first step in the determination of the motor threshold and is the basis for the specification of stimulation intensity used for various Transcranial Magnetic Stimulation (TMS) applications. The level of experimenters' experience and the methodology of motor hotspot identification differ between laboratories. The need for an optimized and time-efficient technique for motor hotspot identification is therefore substantial.

Objective

With the current work, we present a framework for an optimized and time-efficient semi-automated motor hotspot search (SAMHS) technique utilizing a neuronavigated robot-assisted TMS system (TMS-cobot). Furthermore, we aim to test its practicality and accuracy by a comparison with a manual motor hotspot identification method.

Method

A total of 32 participants took part in this dual-center study. At both study centers, participants underwent manual hotspot search (MHS) with an experienced TMS researcher, and the novel SAMHS procedure with a TMS-cobot (hereafter, called cobot hotspot search, CHS) in a randomized order. Resting motor threshold (RMT), and stimulus intensity to produce 1 mV (SI1mV) peak-to-peak of motor-evoked potential (MEP), as well as MEPs with 120% RMT and SI1mV were recorded as outcome measures for comparison.

Results

Compared to the MHS method, the CHS produced lower RMT, lower SI1mV and a trend-wise higher peak-to-peak MEP amplitude in stimulations with SI1mV. The duration of the CHS procedure was longer than that of the MHS (15.60 vs. 2.43 min on average). However, accuracy of the hotspot was higher for the CHS compared to the MHS.

Conclusions

The SAMHS procedure introduces an optimized motor hotspot determination system that is easy to use, and strikes a fairly good balance between accuracy and speed. This new procedure can thus be deplored by experienced as well as beginner-level TMS researchers.

A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation

When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well as comprehensive biophysical modeling. We formulate, test, and disseminate a direct (i.e., non-iterative) TMS solver that can accurately determine global TMS fields for any coil type everywhere in a high-resolution MRI-based surface model with ~ 200,000 or more arbitrarily selected observation points within approximately 5 s, with the solution time itself of 3 s. The solver is based on the boundary element fast multipole method (BEM-FMM), which incorporates the latest mathematical advancement in the theory of fast multipole methods-an FMM-based LU decomposition. This decomposition is specific to the head model and needs to be computed only once per subject. Moreover, the solver offers unlimited spatial numerical resolution. Despite the fast execution times, the present direct solution is numerically accurate for the default model resolution. In contrast, the widely used brain modeling software SimNIBS employs a first-order finite element method that necessitates additional mesh refinement, resulting in increased computational cost. However, excellent agreement between the two methods is observed for various practical test cases following mesh refinement, including a biophysical modeling task. The method can be readily applied to a wide range of TMS analyses involving multiple coil positions and orientations, including image-guided neuronavigation. It can even accommodate continuous variations in coil geometry, such as flexible H-type TMS coils. The FMM-LU direct solver is freely available to academic users.

A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation

Background

When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well as comprehensive biophysical modeling.

Objective

We formulate, test, and disseminate a direct (i.e., non-iterative) TMS solver that can accurately determine global TMS fields for any coil type everywhere in a high-resolution MRI-based surface model with ~200,000 or more arbitrarily selected observation points within approximately 5 sec, with the solution time itself of 3 sec.

Method

The solver is based on the boundary element fast multipole method (BEM-FMM), which incorporates the latest mathematical advancement in the theory of fast multipole methods - an FMM-based LU decomposition. This decomposition is specific to the head model and needs to be computed only once per subject. Moreover, the solver offers unlimited spatial numerical resolution.

Results

Despite the fast execution times, the present direct solution is numerically accurate for the default model resolution. In contrast, the widely used brain modeling software SimNIBS employs a first-order finite element method that necessitates additional mesh refinement, resulting in increased computational cost. However, excellent agreement between the two methods is observed for various practical test cases following mesh refinement, including a biophysical modeling task.

Conclusion

The method can be readily applied to a wide range of TMS analyses involving multiple coil positions and orientations, including image-guided neuronavigation. It can even accommodate continuous variations in coil geometry, such as flexible H-type TMS coils. The FMM-LU direct solver is freely available to academic users.

Reliability of active robotic neuro-navigated transcranial magnetic stimulation motor maps

Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method used to study corticomotor organization and intervention-induced plasticity. Reliability of resting maps is well established, but understudied for active maps and unestablished for active maps obtained using robotic TMS techniques. The objective of  this study was to determine the reliability of robotic neuro-navigated TMS motor map measures during active muscle contraction. We hypothesized that map area and volume would show excellent short- and medium-term reliability. Twenty healthy adults were tested on 3 days. Active maps of the first dorsal interosseous muscle were created using a 12 × 12 grid (7 mm spacing). Short- (24 h) and medium-term (3-5 weeks) relative (intra-class correlation coefficient) and absolute (minimal detectable change (MDC); standard error of measure) reliabilities were evaluated for map area, volume, center of gravity (CoG), and hotspot magnitude (peak-to-peak MEP amplitude at the hotspot), along with active motor threshold (AMT) and maximum voluntary contraction (MVC). This study found that AMT and MVC had good-to-excellent short- and medium-term reliability. Map CoG (x and y) were the most reliable map measures across sessions with excellent short- and medium-term reliability (p < 0.001). Map area, hotspot magnitude, and map volume followed with better reliability medium-term than short-term, with a change of 28%, 62%, and 78% needed to detect a true medium-term change, respectively. Therefore, robot-guided neuro-navigated TMS active mapping is relatively reliable but varies across measures. This, and MDC, should be considered in interventional study designs.

Differences in neurometabolites and transcranial magnetic stimulation motor maps in children with attention-deficit/hyperactivity disorder

BACKGROUND

Although much is known about cognitive dysfunction in attention-deficit/hyperactivity disorder (ADHD), few studies have examined the pathophysiology of disordered motor circuitry. We explored differences in neurometabolite levels and transcranial magnetic stimulation (TMS)-derived corticomotor representations among children with ADHD and typically developing children.

METHODS

We used magnetic resonance spectroscopy (MRS) protocols to measure excitatory (glutamate + glutamine [Glx]) and inhibitory (γ-aminobutyric acid [GABA]) neurometabolite levels in the dominant primary motor cortex (M1) and the supplementary motor area (SMA) in children with ADHD and typically developing children. We used robotic neuronavigated TMS to measure corticospinal excitability and create corticomotor maps.

RESULTS

We collected data from 26 medication-free children with ADHD (aged 7-16 years) and 25 typically developing children (11-16 years). Children with ADHD had lower M1 Glx (p = 0.044, d = 0.6); their mean resting motor threshold was lower (p = 0.029, d = 0.8); their map area was smaller (p = 0.044, d = 0.7); and their hotspot density was higher (p = 0.008, d = 0.9). M1 GABA levels were associated with motor map area (p = 0.036).Limitations: Some TMS data were lost because the threshold of some children exceeded 100% of the machine output. The relatively large MRS voxel required to obtain sufficient signal-to-noise ratio and reliably measure GABA levels encompassed tissue beyond the M1, making this measure less anatomically specific.

CONCLUSION

The neurochemistry and neurophysiology of key nodes in the motor network may be altered in children with ADHD, and the differences appear to be related to each other. These findings suggest potentially novel neuropharmacological and neuromodulatory targets for ADHD.

Active versus resting neuro-navigated robotic transcranial magnetic stimulation motor mapping

Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method that can be used to study corticomotor organization. Motor maps are typically acquired at rest, and comparisons to maps obtained during muscle activation have been both limited and contradictory. Understanding the relationship between functional activation of the corticomotor system as recorded by motor mapping is crucial for their use clinically and in research. The present study utilized robotic TMS paired with personalized neuro-navigation to examine the relationship between resting and active motor map measures and their relationship with motor performance. Twenty healthy right-handed participants underwent resting and active robotic TMS motor mapping of the first dorsal interosseous to 10% maximum voluntary contraction. Motor map parameters including map area, volume, and measures of map centrality were compared between techniques using paired sample tests of difference and Bland-Altman plots and analysis. Map area, volume, and hotspot magnitude were larger in the active motor maps, while map center of gravity and hotspot locations remained consistent between both maps. No associations were observed between motor maps and motor performance as measured by the Purdue Pegboard Test. Our findings support previous suggestions that maps scale with muscle contraction. Differences in mapping outcomes suggest rest and active motor maps may reflect functionally different corticomotor representations. Advanced analysis methods may better characterize the underlying neurophysiology of both types of motor mapping.

Transcranial Magnetic Stimulation in the Treatment of Neurological Diseases

Transcranial Magnetic Stimulation (TMS) has widespread use in research and clinical application. For psychiatric applications, such as depression or OCD, repetitive TMS protocols (rTMS) are an established and globally applied treatment option. While promising, rTMS is not yet as common in treating neurological diseases, except for neurorehabilitation after (motor) stroke and neuropathic pain treatment. This may soon change. New clinical studies testing the potential of rTMS in various other neurological conditions appear at a rapid pace. This can prove challenging for both practitioners and clinical researchers. Although most of these neurological applications have not yet received the same level of scientific/empirical scrutiny as motor stroke and neuropathic pain, the results are encouraging, opening new doors for TMS in neurology. We here review the latest clinical evidence for rTMS in pioneering neurological applications including movement disorders, Alzheimer's disease/mild cognitive impairment, epilepsy, multiple sclerosis, and disorders of consciousness.

Robotic mapping of motor cortex in children with perinatal stroke and hemiparesis

Brain stimulation combined with intensive therapy may improve hand function in children with perinatal stroke‐induced unilateral cerebral palsy (UCP). However, response to therapy varies and underlying neuroplasticity mechanisms remain unclear. Here, we aimed to characterize robotic motor mapping outcomes in children with UCP. Twenty‐nine children with perinatal stroke and UCP (median age 11 ± 2 years) were compared to 24 typically developing controls (TDC). Robotic, neuronavigated transcranial magnetic stimulation was employed to define bilateral motor maps including area, volume, and peak motor evoked potential (MEP). Map outcomes were compared to the primary clinical outcome of the Jebsen–Taylor Test of Hand Function (JTT). Maps were reliably obtained in the contralesional motor cortex (24/29) but challenging in the lesioned hemisphere (5/29). Within the contralesional M1 of participants with UCP, area and peak MEP amplitude of the unaffected map were larger than the affected map. When comparing bilateral maps within the contralesional M1 in children with UCP to that of TDC, only peak MEP amplitudes were different, being smaller for the affected hand as compared to TDC. We observed correlations between the unaffected map when stimulating the contralesional M1 and function of the unaffected hand. Robotic motor mapping can characterize motor cortex neurophysiology in children with perinatal stroke. Map area and peak MEP amplitude may represent discrete biomarkers of developmental plasticity in the contralesional M1. Correlations between map metrics and hand function suggest clinical relevance and utility in studies of interventional plasticity.

Effects of Transcranial Direct Current Stimulation and High-Definition Transcranial Direct Current Stimulation Enhanced Motor Learning on Robotic Transcranial Magnetic Stimulation Motor Maps in Children

Introduction: Conventional transcranial direct current stimulation (tDCS) and high-definition tDCS (HD-tDCS) may improve motor learning in children. Mechanisms are not understood. Neuronavigated robotic transcranial magnetic stimulation (TMS) can produce individualised maps of primary motor cortex (M1) topography. We aimed to determine the effects of tDCS- and HD-tDCS-enhanced motor learning on motor maps. Methods: Typically developing children aged 12-18 years were randomised to right M1 anodal tDCS, HD-tDCS, or Sham during training of their left-hand on the Purdue Pegboard Task (PPT) over 5 days. Bilateral motor mapping was performed at baseline (pre), day 5 (post), and 6-weeks retention time (RT). Primary muscle was the first dorsal interosseous (FDI) with secondary muscles of abductor pollicis brevis (APB) and adductor digiti minimi (ADM). Primary mapping outcomes were volume (mm²/mV) and area (mm²). Secondary outcomes were centre of gravity (COG, mm) and hotspot magnitude (mV). Linear mixed-effects modelling was employed to investigate effects of time and stimulation type (tDCS, HD-tDCS, Sham) on motor map characteristics. Results: Twenty-four right-handed participants (median age 15.5 years, 52% female) completed the study with no serious adverse events or dropouts. Quality maps could not be obtained in two participants. No effect of time or group were observed on map area or volume. LFDI COG (mm) differed in the medial-lateral plane (x-axis) between tDCS and Sham (p = 0.038) from pre-to-post mapping sessions. Shifts in map COG were also observed for secondary left-hand muscles. Map metrics did not correlate with behavioural changes. Conclusion: Robotic TMS mapping can safely assess motor cortex neurophysiology in children undergoing motor learning and neuromodulation interventions. Large effects on map area and volume were not observed while changes in COG may occur. Larger controlled studies are required to understand the role of motor maps in interventional neuroplasticity in children.

Robotic transcranial magnetic stimulation motor maps and hand function in adolescents

Introduction

Transcranial magnetic stimulation (TMS) motor mapping can characterize the neurophysiology of the motor system. Limitations including human error and the challenges of pediatric populations may be overcome by emerging robotic systems. We aimed to show that neuronavigated robotic motor mapping in adolescents could efficiently produce discrete maps of individual upper extremity muscles, the characteristics of which would correlate with motor behavior.

Methods

Typically developing adolescents (TDA) underwent neuronavigated robotic TMS mapping of bilateral motor cortex. Representative maps of first dorsal interosseous (FDI), abductor pollicis brevis (APB), and abductor digiti minimi (ADM) muscles in each hand were created. Map features including area (primary), volume, and center of gravity were analyzed across different excitability regions (R100%, R75%, R50%, R25%). Correlations between map metrics and validated tests of hand motor function (Purdue Pegboard Test as primary) were explored.

Results

Twenty‐four right‐handed participants (range 12–18 years, median 15.5 years, 52% female) completed bilateral mapping and motor assessments with no serious adverse events or dropouts. Gender and age were associated with hand function and motor map characteristics. Full motor maps (R100%) for FDI did not correlate with motor function in either hand. Smaller excitability subset regions demonstrated reduced variance and dose‐dependent correlations between primary map variables and motor function in the dominant hemisphere.

Conclusions

Hand function in TDA correlates with smaller subset excitability regions of robotic TMS motor map outcomes. Refined motor maps may have less variance and greater potential to quantify interventional neuroplasticity. Robotic TMS mapping is safe and feasible in adolescents.