Effect of muscle length in a handgrip task on corticomotor excitability of extrinsic and intrinsic hand muscles under resting and submaximal contraction conditions.

The neurophysiological mechanisms underlying muscle force control for different wrist postures still need to be better understood. To further elucidate these mechanisms, the present study aimed to investigate the effects of wrist posture on the corticospinal excitability by transcranial magnetic stimulation (TMS) of extrinsic (flexor [FCR] and extensor carpi radialis [ECR]) and intrinsic (flexor pollicis brevis (FPB)) muscles at rest and during a submaximal handgrip strength task. Fourteen subjects (24.06 ± 2.28 years) without neurological or motor disorders were included. We assessed how the wrist posture (neutral: 0°; flexed: +45°; extended: -45°) affects maximal handgrip strength (HGSmax ) and the motor evoked potentials (MEP) amplitudes during rest and active muscle contractions. HGSmax was higher at 0° (133%) than at -45° (93.6%; p < 0.001) and +45° (73.9%; p < 0.001). MEP amplitudes were higher for the FCR at +45° (83.6%) than at -45° (45.2%; p = 0.019) and at +45° (156%; p < 0.001) and 0° (146%; p = 0.014) than at -45° (106%) at rest and active condition, respectively. Regarding the ECR, the MEP amplitudes were higher at -45° (113%) than at +45° (60.8%; p < 0.001) and 0° (72.6%; p = 0.008), and at -45° (138%) than +45° (96.7%; p = 0.007) also at rest and active conditions, respectively. In contrast, the FPB did not reveal any difference among wrist postures and conditions. Although extrinsic and intrinsic hand muscles exhibit overlapping cortical representations and partially share the same innervation, they can be modulated differently depending on the biomechanical constraints.

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 centroid 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.

MarLe: Markerless estimation of head pose for navigated transcranial magnetic stimulation.

Navigated transcranial magnetic stimulation (nTMS) is a valuable tool for non-invasive brain stimulation. Currently, nTMS requires fixing of markers on the patient's head. Head marker displacements lead to changes in coil placement and brain stimulation inaccuracy. A markerless neuronavigation method is needed to increase the reliability of nTMS and simplify the nTMS protocol. In this study, we introduce and release MarLe, a Python markerless head tracker neuronavigation software for TMS. This novel software uses computer-vision techniques combined with low-cost cameras to estimate the head pose for neuronavigation. A coregistration algorithm, based on a closed-form solution, was designed to track the patient's head and the TMS coil referenced to the individual's brain image. We show that MarLe can estimate head pose based on real-time video processing. An intuitive pipeline was developed to connect the MarLe and nTMS neuronavigation software. MarLe achieved acceptable accuracy and stability in a mockup nTMS experiment. MarLe allows real-time tracking of the patient's head without any markers. The combination of face detection and a coregistration algorithm can overcome nTMS head marker displacement concerns. MarLe can improve reliability, simplify, and reduce the protocol time of brain intervention techniques such as nTMS.

Development and characterization of the InVesalius Navigator software for navigated transcranial magnetic stimulation.

BACKGROUND: Neuronavigation provides visual guidance of an instrument during procedures of neurological interventions, and has been shown to be a valuable tool for accurately positioning transcranial magnetic stimulation (TMS) coils relative to an individual's anatomy. Despite the importance of neuronavigation, its high cost, low portability, and low availability of magnetic resonance imaging facilities limit its insertion in research and clinical environments. NEW METHOD: We have developed and validated the InVesalius Navigator as the first free, open-source software for image-guided navigated TMS, compatible with multiple tracking devices. A point-based, co-registration algorithm and a guiding interface were designed for tracking any instrument (e.g. TMS coils) relative to an individual's anatomy. RESULTS: Localization, precision errors, and repeatability were measured for two tracking devices during navigation in a phantom and in a simulated TMS study. Errors were measured in two commercial navigated TMS systems for comparison. Localization error was about 1.5 mm, and repeatability was about 1 mm for translation and 1° for rotation angles, both within limits established in the literature. COMPARISON WITH EXISTING METHODS: Existing TMS neuronavigation software programs are not compatible with multiple tracking devices, and do not provide an easy to implement platform for custom tools. Moreover, commercial alternatives are expensive with limited portability. CONCLUSIONS: InVesalius Navigator might contribute to improving spatial accuracy and the reliability of techniques for brain interventions by means of an intuitive graphical interface. Furthermore, the software can be easily integrated into existing neuroimaging tools, and customized for novel applications such as multi-locus and/or controllable-pulse TMS.