Linking Individual Movements to a Skilled Repertoire: Fast Modulation of Motor Synergies by Repetition of Stereotyped Movements

Contribution of the stereoscopic representation of motion-in-depth during visually guided feedback control

Considerable studies have focused on the neural basis of visually guided tracking movement in the frontoparallel plane, whereas the neural process in real-world circumstances regarding the influence of binocular disparity and motion-in-depth (MID) perception is less understood. Although the role of stereoscopic versus monoscopic MID information has been extensively described for visual processing, its influence on top-down regulation for motor execution has not received much attention. Here, we orthogonally varied the visual representation (stereoscopic versus monoscopic) and motion direction (depth motion versus bias depth motion versus frontoparallel motion) during visually guided tracking movements, with simultaneous functional near-infrared spectroscopy recordings. Results show that the stereoscopic representation of MID could lead to more accurate movements, which was supported by specific neural activity pattern. More importantly, we extend prior evidence about the role of frontoparietal network in brain-behavior relationship, showing that occipital area, more specifically, visual area V2/V3 was also robustly involved in the association. Furthermore, by using the stereoscopic representation of MID, it is plausible to detect robust brain-behavior relationship even with small sample size at low executive task demand. Taken together, these findings highlight the importance of the stereoscopic representation of MID for investigating neural correlates of visually guided feedback control.

Similarity of hand muscle synergies elicited by transcranial magnetic stimulation and those found during voluntary movement

Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. Electromyography (EMG) was recorded from eight hand-forearm muscles in eight healthy individuals. Modularity was defined using non-negative matrix factorization to identify low-rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high-density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both data sets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest that corticospinal connectivity to individual intrinsic hand muscles may be combined with modular multimuscle activation via synergies in the formation of hand postures.NEW & NOTEWORTHY This is the first work to examine the similarity of modularity in hand muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex and that derived from voluntary hand movement. We show that TMS-elicited muscle synergies of the hand, measured at rest, reflect those found in voluntary behavior involving finger fractionation. This work provides a basis for future work using TMS to investigate muscle activation modularity in the human motor system.

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.

Adaptation of the Corticomuscular and Biomechanical Systems of Pianists

Independent control of movements between the fingers plays a role in hand dexterity characterizing skilled individuals. However, it remains unknown whether and in what manner neuromuscular and biomechanical constraints on the movement independence of the fingers depend on motor expertise. Here, we compared motor dexterity, corticospinal excitability of multiple muscles, muscular activation, and anatomical features of the fingers between the pianists and nonpianists. When the ring finger was passively moved by a robot, passive motions produced at the adjacent fingers were smaller for the pianists than the nonpianists, indicating reduced biomechanical constraint of fingers in the pianists. In contrast, when the ring finger moved actively, we found no group difference in passive motions produced at the adjacent fingers; however, reduced inhibition of corticospinal excitability of the adjacent fingers in the pianists compared with the nonpianists. This suggests strengthened neuromuscular coupling between the fingers of the pianists, enhancing the production of coordinated finger movements. These group differences were not evident during the index and little finger movements. Together, pianists show expertise-dependent biomechanical and neurophysiological adaptations, specifically at the finger with innately low movement independence. Such contrasting adaptations of pianists may subserve dexterous control of both the individuated and coordinated finger movements.

Synergistic Organization of Neural Inputs from Spinal Motor Neurons to Extrinsic and Intrinsic Hand Muscles

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies.SIGNIFICANCE STATEMENT We addressed whether the output of spinal motor neurons innervating multiple hand muscles could be accounted for by a modular organization, i.e., synergies, previously described to account for the coordination of multiple muscles. We found that motor neuron synergies presented similar dimensionality (implying a >10-fold reduction in dimensionality) and structure as muscle synergies. Nonetheless, the synergistic behavior of subsets of motor neurons within a muscle was also observed. These results advance our understanding of how neuromuscular control arises from mapping descending inputs to muscle activation signals. We provide, for the first time, insights into the organization of neural inputs to spinal motor neurons which, to date, has been inferred through analysis of muscle synergies.

Gaze direction influences grasping actions towards unseen, haptically explored, objects

Haptic exploration produces mental object representations that can be memorized for subsequent object-directed behaviour. Storage of haptically-acquired object images (HOIs), engages, besides canonical somatosensory areas, the early visual cortex (EVC). Clear evidence for a causal contribution of EVC to HOI representation is still lacking. The use of visual information by the grasping system undergoes necessarily a frame of reference shift by integrating eye-position. We hypothesize that if the motor system uses HOIs stored in a retinotopic coding in the visual cortex, then its use is likely to depend at least in part on eye position. We measured the kinematics of 4 fingers in the right hand of 15 healthy participants during the task of grasping different unseen objects behind an opaque panel, that had been previously explored haptically. The participants never saw the object and operated exclusively based on haptic information. The position of the object was fixed, in front of the participant, but the subject’s gaze varied from trial to trial between 3 possible positions, towards the unseen object or away from it, on either side. Results showed that the middle and little fingers’ kinematics during reaching for the unseen object changed significantly according to gaze position. In a control experiment we showed that intransitive hand movements were not modulated by gaze direction. Manipulating eye-position produces small but significant configuration errors, (behavioural errors due to shifts in frame of reference) possibly related to an eye-centered frame of reference, despite the absence of visual information, indicating sharing of resources between the haptic and the visual/oculomotor system to delayed haptic grasping.

The Topography of Visually Guided Grasping in the Premotor Cortex: A Dense-Transcranial Magnetic Stimulation (TMS) Mapping Study

Visuomotor transformations at the cortical level occur along a network where posterior parietal regions are connected to homologous premotor regions. Grasping-related activity is represented in a diffuse, ventral and dorsal system in the posterior parietal regions, but no systematic causal description of a premotor counterpart of a similar diffuse grasping representation is available. To fill this gap, we measured the kinematics of right finger movements in 17 male and female human participants during grasping of three objects of different sizes. Single-pulse transcranial magnetic stimulation was applied 100 ms after visual presentation of the object over a regular grid of 8 spots covering the left premotor cortex (PMC) and 2 Sham stimulations. Maximum finger aperture during reach was used as the feature to classify object size in different types of classifiers. Classification accuracy was taken as a measure of the efficiency of visuomotor transformations for grasping. Results showed that transcranial magnetic stimulation reduced classification accuracy compared with Sham stimulation when it was applied to 2 spots in the ventral PMC and 1 spot in the medial PMC, corresponding approximately to the ventral PMC and the dorsal portion of the supplementary motor area. Our results indicate a multifocal representation of object geometry for grasping in the PMC that matches the known multifocal parietal maps of grasping representations. Additionally, we confirm that, by applying a uniform spatial sampling procedure, transcranial magnetic stimulation can produce cortical functional maps independent of a priori spatial assumptions.SIGNIFICANCE STATEMENT Visually guided actions activate a large frontoparietal network. Here, we used a dense grid of transcranial magnetic stimulation spots covering the whole premotor cortex (PMC), to identify with accurate spatial mapping the functional specialization of the human PMC during grasping movement. Results corroborate previous findings about the role of the ventral PMC in preshaping the fingers according to the size of the target. Crucially, we found that the medial part of PMC, putatively covering the supplementary motor area, plays a direct role in object grasping. In concert with findings in nonhuman primates, these results indicate a multifocal representation of object geometry for grasping in the PMC and expand our understanding of how our brain integrates visual and motor information to perform visually guided actions.