The computational and neural basis of voluntary motor control and planning

A session of transcutaneous electrical nerve stimulation changes the input-output function of motoneurons and alters the sense of force

Transcutaneous electrical nerve stimulation (TENS) is commonly used in research and clinical settings for pain management and augmenting somatosensory inputs for motor recovery. Besides its functional effect, TENS acutely alters kinesthesia and force steadiness. However, the short-term impact following a session of TENS on proprioception and motor unit behavior is unknown. We evaluated the effect of a session of TENS on the senses of force, joint position, touch, and discharge activity of motor units. Fifteen healthy participants underwent two experiments, each with two visits randomly administering TENS or sham-TENS. The sense of force (experiment 1) and position (experiment 2) were evaluated through matching trials by pinching a dial and rotating their wrist (ulnar deviation). Isometric pinch contractions were performed before and after the session of TENS or sham-TENS, in which electromyographic (EMG) signals were recorded from the first dorsal interosseus (FDI) and abductor pollicis brevis (APB). Results showed that TENS acutely altered the senses of force, position, and touch, but only the sense of force remained altered following TENS. Motor unit discharge rates increased in both FDI and APB muscles for the same force output following TENS. A positive correlation was also observed between changes in motor unit discharge rates and changes in errors in force perception. These findings suggest that a session of TENS may have short-term effects on the input/output function of motoneurons (5-10 min in this study), which in turn may alter the sense of force. However, the precise timeline for these short-term aftereffects is unknown.NEW & NOTEWORTHY It is often assumed that transcutaneous electrical nerve stimulation (TENS) has a transient effect on proprioception and motor control. We found that position, force, and touch perception were altered during TENS. However, the sense of force remained altered following TENS. As the discharge rate of motor units also increased in first dorsal interosseus (FDI) and abductor pollicis brevis (APB) muscles for the same force output following TENS, we suggest that their input-output function was altered, potentially causing a sustained decrease in performance in force-matching tasks.

Lack of pre-movement facilitation as neurophysiological hallmark of fatigue in patients with Parkinson's disease: A single pulse TMS study

BACKGROUND

Fatigue is a debilitating symptom in Parkinson's disease (PD), significantly affecting quality of life. Despite its prevalence, the underlying neurophysiological mechanisms remain poorly understood. Recent evidence suggests that deficits in cortical motor preparation processes may contribute to PD-related fatigue.

METHODS

This study investigated premovement facilitation (PMF), a marker of corticospinal excitability during motor preparation, in 20 healthy subjects (HS) and 28 PD patients, subdivided into those with fatigue (PDwF, n = 14) and without fatigue (PDwoF, n = 14). Participants performed a reaction time (RT) task involving thumb abduction following a visual go signal, while transcranial magnetic stimulation (TMS) was applied over the primary motor cortex (M1) at intervals of 50, 100, and 150 ms before movement onset. Motor-evoked potentials (MEPs) were recorded from the abductor pollicis brevis (APB) and the task-irrelevant abductor digiti minimi (ADM).

RESULTS

In HS and PDwoF, MEP APB amplitude increased progressively when TMS was applied at 150, 100, and 50 ms before movement onset, reflecting intact PMF, with the greater MEP APB amplitude at the shorter interval (50 ms). However, in PDwF patients, PMF was absent on the most affected side, while it remained preserved on the less affected side. Furthermore, the absence of PMF correlated with fatigue severity (FSS scores) and rigidity subscores, highlighting a link between impaired motor preparation and clinical symptoms.

CONCLUSION

These findings suggest that cortical dysfunction in motor preparation contributes to PD-related fatigue, particularly in the most affected hemisphere. The observed PMF deficits provide a potential neurophysiological marker for fatigue in PD, supporting future investigations into targeted therapeutic interventions to restore motor excitability and alleviate fatigue symptoms.

Cortical neural activity during responses to mechanical perturbation: Effects of hand preference and hand used

Handedness is an important feature of human behavioral lateralization that has often been associated with hemispheric specialization. Existing neuroimaging research on the effect of handedness during motor control has focused on well-practiced or predictable tasks, but not tasks that involve unpredictable perturbations. We examined the extent to which handedness (measured by self-reported hand preference) and whether the dominant hand is used or not influence the motor and neural response during unimanual voluntary corrective actions. The experimental task involved controlling a robotic manipulandum to move a cursor from a center start point to a target presented above or below the start. In some trials, a mechanical perturbation of the hand was randomly applied by the robot either consistent or against the target direction, while electroencephalography (EEG) was recorded. Fourteen left-handers and fourteen right-handers completed the experiment. Left-handed individuals had a greater negative peak in the frontal event-related potential (ERP) during the initial voluntary response stage (N140) than right-handed individuals. Furthermore, left-handed individuals showed more symmetrical ERP distributions between two hemispheres than right-handed individuals in the frontal and parietal regions during the late voluntary response stage (P380). To the best of our knowledge, this is the first evidence to demonstrate the differences in the cortical control of voluntary corrective actions between left-handers and right-handers.

String-pulling by the common marmoset

Coordinated hand movements used to grasp and manipulate objects are crucial for many daily activities, such as tying shoelaces or opening jars. Recently, the string-pulling task, which involves cyclically reaching, grasping, and pulling a string, has been used to study coordinated hand movements in rodents and humans. Here, we characterize how adult common marmosets perform the string-pulling task and describe changes in performance across the lifespan. Marmosets (n = 15, 7 females) performed a string-pulling task for a food reward using an instrumented apparatus attached to their home-cage. Movement kinematics were acquired using markerless video tracking and we assessed individual hand movements and bimanual coordination using standard metrics. Marmosets oriented their gaze toward the string above their hands and readily performed the task regardless of sex or age. The task required little training and animals routinely engaged in multiple pulling trials per session, despite not being under water or food control. All marmosets showed consistent pulling speed and similar hand movements regardless of age. Adult marmosets exhibited a clear hand effect, performing straighter and faster movements with their right hand despite showing idiosyncratic hand preference according to a traditional food retrieval assay. Hand effects were also evident for younger animals but seemed attenuated in the older animals. In terms of bimanual coordination, all adult marmosets demonstrated alternating movement pattern for vertical hand positions. Two younger and two older marmosets exhibited idiosyncratic coordination patterns even after substantial experience. In general, younger and older animals exhibited higher variability in bimanual coordination than adults.NEW & NOTEWORTHY Bimanual coordination is crucial for daily activities. In this study, we characterized how common marmosets performed the string-pulling task without extensive training, regardless of sex or age, and naturally exhibited a cyclical alternating pattern of hand movements. Although the overall behavior was similar across ages, younger and older marmosets demonstrated higher variability in bimanual coordination. These results establish the string-pulling task as a reliable tool for studying bimanual coordination and its underlying neural substrates.

Effects of posterior parietal cortex anodal transcranial direct current stimulation on ankle tracking visuomotor control in healthy young adults

Ankle motor control is crucial for balance maintenance and fall prevention. Neurocomputational models of motor control suggest that the posterior parietal cortex (PPC) plays a critical role in estimating body and environmental states, a process fundamental to motor control. Anodal transcranial direct current stimulation (atDCS) has been shown to modulate cortical excitability and alter behaviors accordingly. This study explored the impact of atDCS over the PPC on ankle tracking visuomotor control using a motor adaptation research paradigm in healthy young adults. Thirty-eight participants were randomly assigned to either an atDCS or sham control group. All participants completed an ankle tracking experiment divided into three phases: pre-adaptation, adaptation, and re-adaptation, with each phase comprising eight blocks of five trials. During the experiment, each participant wore a sensor on the non-dominant foot and performed continuous dorsiflexion and plantarflexion movements to track a target cursor on a screen. Visual feedback of the foot position was provided, with a 1:1 feedback ratio in the pre- and re-adaptation phases and a 2.5:1 ratio in the adaptation phase to promote visual-motor remapping. The atDCS group received 20 min of 2 mA atDCS over the PPC during the adaptation phase. Tracking performance on each trial was measured as the root mean squared error (RMSE) between the target and actual movement trajectories. Both groups showed similar RMSEs in the pre-adaptation phase (p > 0.05). However, in the adaptation phase, the atDCS group demonstrated a significant reduction from block 1 to block 2 (p = 0.001, Cohen's d = 0.86) and maintained this improved performance in the following blocks, while the sham group showed no significant changes throughout this phase (p > 0.05). In the re-adaptation phase, both groups quickly returned to their pre-adaptation performance levels. These findings indicate that neither the atDCS nor the sham group adapted to the high visual feedback ratio. However, the early reduction in RMSE observed in the atDCS group suggests that atDCS over the PPC may transiently enhance ankle tracking visuomotor control under the heightened visual feedback ratio condition, resulting in short-term improvements. Future research is warranted to explore whether multiple atDCS sessions over the PPC could provide long-term benefits for lower extremity visuomotor control.

A neural implementation model of feedback-based motor learning

Animals use feedback to rapidly correct ongoing movements in the presence of a perturbation. Repeated exposure to a predictable perturbation leads to behavioural adaptation that compensates for its effects. Here, we tested the hypothesis that all the processes necessary for motor adaptation may emerge as properties of a controller that adaptively updates its policy. We trained a recurrent neural network to control its own output through an error-based feedback signal, which allowed it to rapidly counteract external perturbations. Implementing a biologically plausible plasticity rule based on this same feedback signal enabled the network to learn to compensate for persistent perturbations through a trial-by-trial process. The network activity changes during learning matched those from populations of neurons from monkey primary motor cortex - known to mediate both movement correction and motor adaptation - during the same task. Furthermore, our model natively reproduced several key aspects of behavioural studies in humans and monkeys. Thus, key features of trial-by-trial motor adaptation can arise from the internal properties of a recurrent neural circuit that adaptively controls its output based on ongoing feedback.

Hypergravity is more challenging than microgravity for the human sensorimotor system

The importance of gravity for human motor control is well established, but it remains unclear how the central nervous system accounts for gravitational changes to perform complex motor skills. We tested the hypothesis that microgravity and hypergravity have distinct effects on the neuromuscular control of reaching movements compared to normogravity. To test the influence of gravity levels on sensorimotor planning and control, participants (n = 9) had to reach toward visual targets during parabolic flights. Whole-body kinematics and muscular activity were adjusted in microgravity, allowing arm reaching to be as accurate as in normogravity. However, we observed in hypergravity a systematic undershooting, which likely resulted from a lack of reorganization of muscle activations. While new studies are necessary to clarify whether hypergravity impairs the internal model of limb dynamics, our findings provide new evidence that hypergravity creates a challenge that the human sensorimotor system is unable to solve in the short term.

Effect of a Perturbation-Based Balance Training Session on Adaptive Locomotor Response in Older Adults With a History of Falls

AIM

To assess the adaptive response of older adults with a history of falls in a single Perturbation-Based Balance Training (PBT) session by examining the margin of stability (MoS) and the number of falls.

METHODS

Thirty-two older adults with a history of falls underwent a treadmill walking session lasting 20-25 min. During the PBT protocol, participants experienced 24 unexpected perturbations delivered in two ways: acceleration or deceleration of the treadmill belt, with 12 perturbations in each direction. The MoS in the anteroposterior direction was assessed for the first and last perturbations of the session, during the perturbation step (N) and the recovery step (REC), along with the number of falls during the training session.

RESULTS

There was no statistically significant difference in MoS between the first and last perturbations (acceleration and deceleration) for steps N and REC. Regarding the number of falls, a significant reduction was found when comparing the first half with the second half of the training session (p = .033). There were 13 falls in the first half and only three in the second half of the PBT session.

CONCLUSION

Older adults with a history of falls exhibited an adaptive response with a reduction in the number of falls during a single session of PBT despite not showing changes in the MoS.

Estimating descending activation patterns from EMG in fast and slow movements using a model of the stretch reflex

Due to spinal reflex loops, descending activation from the brain is not the only source of muscle activation that ultimately generates movement. This study directly estimates descending activation patterns from measured patterns of muscle activation (electromyographic; EMG) during human arm movements. A simple model of the spinal stretch reflex is calibrated in a postural unloading task and then used to estimate descending activation patterns from muscle EMG patterns and kinematics during voluntary arm motion performed at different speeds. We observed three key features of the estimated descending activation patterns: 1) Within about the first 15% of movement duration, descending and muscle activations are temporally aligned. Thereafter, they diverge and develop qualitatively different temporal profiles. 2) The time course of descending activation is monotonic for slow movements, nonmonotonic for fast movements. 3) Varying model parameters such as the spinal reflex gain or the level of cocontraction do not qualitatively change the temporal pattern of estimated descending activation. Our findings highlight the substantial contribution of spinal reflex loops to movement generation, while at the same time providing evidence that the brain must generate qualitatively different descending activation patterns for movements that vary in their mechanical dynamics.NEW & NOTEWORTHY We propose a new method that directly estimates descending activation from measured electromyographic (EMG) signals and arm kinematics by inverting a model of the spinal stretch reflex, without the need for muscle models or an arm dynamics model. This approach identifies key features of the time structure of descending activation as movement speed is varied, while also revealing the significant contribution of the spinal stretch reflex to movement generation.

Distinct patterns of connectivity with the motor cortex reflect different components of sensorimotor learning

Sensorimotor learning is supported by multiple competing processes that operate concurrently, making it a challenge to elucidate their neural underpinnings. Here, using human functional MRI, we identify 3 distinct axes of connectivity between the motor cortex and other brain regions during sensorimotor adaptation. These 3 axes uniquely correspond to subjects' degree of implicit learning, performance errors and explicit strategy use, and involve different brain networks situated at increasing levels of the cortical hierarchy. We test the generalizability of these neural axes to a separate form of motor learning known to rely mainly on explicit processes and show that it is only the Explicit neural axis, composed of higher-order areas in transmodal cortex, that predicts learning in this task. Together, our study uncovers multiple distinct patterns of functional connectivity with motor cortex during sensorimotor adaptation, the component processes that these patterns support, and how they generalize to other forms of motor learning.

Cortical neural activity during responses to mechanical perturbation: Effects of hand preference and hand used

Handedness, as measured by self-reported hand preference, is an important feature of human behavioral lateralization that has often been associated with hemispheric specialization. We examined the extent to which hand preference and whether the dominant hand is used or not influence the motor and neural response during voluntary unimanual corrective actions. The experimental task involved controlling a robotic manipulandum to move a cursor from a center start point to a target presented above or below the start. In some trials, a mechanical perturbation of the hand was randomly applied by the robot either consistent or against the target direction, while electroencephalography (EEG) was recorded. Twelve left-handers and ten right-handers completed the experiment. Left-handed individuals had a greater negative peak in the frontal event-related potential (ERP) than right-handed participants during the initial response phase (N150) than right-handed individuals. Furthermore, left-handed individuals showed more symmetrical ERP distributions between two hemispheres than right-handed individuals in the frontal and parietal regions during the late voluntary response phase (P390). To the best of our knowledge, this is the first evidence that demonstrates the differences in the cortical control of voluntary corrective actions between left-handers and right-handers.

Kernels of Motor Memory Formation: Temporal Generalization in Bimanual Adaptation

In daily life, we coordinate both simultaneous and sequential bimanual movements to manipulate objects. Our ability to rapidly account for different object dynamics suggests there are neural mechanisms to quickly deal with them. Here we investigate how actions of one arm can serve as a contextual cue for the other arm and facilitate adaptation. Specifically, we examine the temporal characteristics that underlie motor memory formation and recall, by testing the contextual effects of prior, simultaneous, and post contralateral arm movements in both male and female human participants. To do so, we measure their temporal generalization in three bimanual interference tasks. Importantly, the timing context of the learned action plays a pivotal role in the temporal generalization. While motor memories trained with post adaptation contextual movements generalize broadly, motor memories trained with prior contextual movements exhibit limited generalization, and motor memories trained with simultaneous contextual movements do not generalize to prior or post contextual timings. This highlights temporal tuning in sensorimotor plasticity: different training conditions yield substantially different temporal generalization characteristics. Since these generalizations extend far beyond any variability in training times, we suggest that the observed differences may stem from inherent differences in the use of prior, current, and post adaptation contextual information in the generation of natural behavior. This would imply differences in the underlying neural circuitry involved in learning and executing the corresponding coordinated bimanual movements.

Increased muscle coactivation is linked with fast feedback control when reaching in unpredictable visual environments

Humans encounter unpredictable disturbances in daily activities and sports. When encountering unpredictable physical disturbances, healthy participants increase the peak velocity of their reaching movements, muscle coactivation, and responses to sensory feedback. Emerging evidence suggests that muscle coactivation may facilitate responses to sensory feedback and may not solely increase stiffness to resist displacements. We tested this idea by examining how healthy participants alter the control of reaching movements and responses to sensory feedback when encountering variable visuomotor rotations. The rotations changed amplitude and direction between movements, creating unpredictable errors that required fast online corrections. Participants increased the peak velocity of their movements, muscle coactivation, and responses to visual and proprioceptive feedback with the variability of the visuomotor rotations. The findings highlight an increase in neural responsiveness to sensory feedback and suggest that muscle coactivation may prime the nervous system for fast responses to sensory feedback that accommodate properties of unpredictable visual environments.

Co-contraction embodies uncertainty: An optimal feedforward strategy for robust motor control

Despite our environment often being uncertain, we generally manage to generate stable motor behaviors. While reactive control plays a major role in this achievement, proactive control is critical to cope with the substantial noise and delays that affect neuromusculoskeletal systems. In particular, muscle co-contraction is exploited to robustify feedforward motor commands against internal sensorimotor noise as was revealed by stochastic optimal open-loop control modeling. Here, we extend this framework to neuromusculoskeletal systems subjected to random disturbances originating from the environment. The analytical derivation and numerical simulations predict a characteristic relationship between the degree of uncertainty in the task at hand and the optimal level of anticipatory co-contraction. This prediction is confirmed through a single-joint pointing task experiment where an external torque is applied to the wrist near the end of the reaching movement with varying probabilities across blocks of trials. We conclude that uncertainty calls for impedance control via proactive muscle co-contraction to stabilize behaviors when reactive control is insufficient for task success.

Corticocortical and corticomuscular connectivity dynamics in standing posture: electroencephalography study

Cortical mechanism is necessary for human standing control. Previous research has demonstrated that cortical oscillations and corticospinal excitability respond flexibly to postural demands. However, it is unclear how corticocortical and corticomuscular connectivity changes dynamically during standing with spontaneous postural sway and over time. This study investigated the dynamics of sway- and time-varying connectivity using electroencephalography and electromyography. Electroencephalography and electromyography were recorded in sitting position and 3 standing postures with varying base-of-support: normal standing, one-leg standing, and standing on a piece of wood. For sway-varying connectivity, corticomuscular connectivity was calculated based on the timing of peak velocity in anteroposterior sway. For time-varying connectivity, corticocortical connectivity was measured using the sliding-window approach. This study found that corticomuscular connectivity was strengthened at the peak velocity of postural sway in the γ- and β-frequency bands. For time-varying corticocortical connectivity, the θ-connectivity in all time-epoch was classified into 7 clusters including posture-relevant component. In one of the 7 clusters, strong connectivity pairs were concentrated in the mid-central region, and the proportion of epochs under narrow-base standing conditions was significantly higher, indicating a functional role for posture balance. These findings shed light on the connectivity dynamics and cortical oscillation that govern standing balance.

Learning and Control in Motor Cortex across Cell Types and Scales

The motor cortex is essential for controlling the flexible movements underlying complex behaviors. Behavioral flexibility involves the ability to integrate and refine new movements, thereby expanding an animal's repertoire. This review discusses recent strides in motor learning mechanisms across spatial and temporal scales, describing how neural networks are remodeled at the level of synapses, cell types, and circuits and across time as animals' learn new skills. It highlights how changes at each scale contribute to the evolving structure and function of neural circuits that accompanies the expansion and refinement of motor skills. We review new findings highlighted by advanced imaging techniques that have opened new vistas in optical physiology and neuroanatomy, revealing the complexity and adaptability of motor cortical circuits, crucial for learning and control. At the structural level, we explore the dynamic regulation of dendritic spines mediating corticocortical and thalamocortical inputs to the motor cortex. We delve into the role of perisynaptic astrocyte processes in maintaining synaptic stability during learning. We also examine the functional diversity among pyramidal neuron subtypes, their dendritic computations and unique contributions to single cell and network function. Further, we highlight how cortical activation is characterized by increased consistency and reduced strength as new movements are learned and how external inputs contribute to these changes. Finally, we consider the motor cortex's necessity as movements unfold over long time scales. These insights will continue to drive new research directions, enhancing our understanding of motor cortical circuit transformations that underpin behavioral changes expressed throughout an animal's life.

Visuomotor prediction during action planning in the human frontoparietal cortex and cerebellum

The concept of forward models in the brain, classically applied to describing on-line motor control, can in principle be extended to action planning, i.e. assuming forward sensory predictions are issued during the mere preparation of movements. To test this idea, we combined a delayed movement task with a virtual reality based manipulation of visuomotor congruence during functional magnetic resonance imaging. Participants executed simple hand movements after a delay. During the delay, two aspects of the upcoming movement could be cued: the movement type and the visuomotor mapping (i.e. congruence of executed hand movements and visual movement feedback by a glove-controlled virtual hand). Frontoparietal areas showed increased delay period activity when preparing pre-specified movements (cued > uncued). The cerebellum showed increased activity during the preparation for incongruent > congruent visuomotor mappings. The left anterior intraparietal sulcus showed an interaction effect, responding most strongly when a pre-specified (cued) movement was prepared under expected visuomotor incongruence. These results suggest that motor planning entails a forward prediction of visual body movement feedback, which can be adjusted in anticipation of nonstandard visuomotor mappings, and which is likely computed by the cerebellum and integrated with state estimates for (planned) control in the anterior intraparietal sulcus.

Adaptation of the gain of the corrective lifting response in object manipulation transfers across the hand

Our ability to skillfully manipulate objects is supported by rapid corrective responses that are initiated when we experience perturbations that interfere with movement goals. For example, the corrective lifting response is triggered when an object is heavier than expected and fails to lift off the surface. In this situation, the absence of expected sensory feedback signalling lift off initiates, within ~ 90 ms, an increase in lifting force. Importantly, when people repeatedly lift an object that, on occasional catch trials, is heavier than expected, the gain of the corrective response, defined as the rate of force increase, adapts to the 'catch' weight. In the present study, we investigated whether this response adaption transfers intermanually. In the training phase, participants used either their left or right hand (counterbalanced) to repeatedly lift a 3 N object that unexpectedly increased to 9 N on catch trials, leading to an increase in the gain of the lifting response across catch trials. Participants then lifted the object with their other hand. On the first catch trial, the gain remained elevated and thus transferred across the hands. This finding suggests that the history of lifts performed by one hand updates the corrective responses for both hands.

Neural dynamics of delayed feedback in robot teleoperation: insights from fNIRS analysis

Introduction

As robot teleoperation increasingly becomes integral in executing tasks in distant, hazardous, or inaccessible environments, operational delays remain a significant obstacle. These delays, inherent in signal transmission and processing, adversely affect operator performance, particularly in tasks requiring precision and timeliness. While current research has made strides in mitigating these delays through advanced control strategies and training methods, a crucial gap persists in understanding the neurofunctional impacts of these delays and the efficacy of countermeasures from a cognitive perspective.

Methods

This study addresses the gap by leveraging functional Near-Infrared Spectroscopy (fNIRS) to examine the neurofunctional implications of simulated haptic feedback on cognitive activity and motor coordination under delayed conditions. In a human-subject experiment (N = 41), sensory feedback was manipulated to observe its influences on various brain regions of interest (ROIs) during teleoperation tasks. The fNIRS data provided a detailed assessment of cerebral activity, particularly in ROIs implicated in time perception and the execution of precise movements.

Results

Our results reveal that the anchoring condition, which provided immediate simulated haptic feedback with a delayed visual cue, significantly optimized neural functions related to time perception and motor coordination. This condition also improved motor performance compared to the asynchronous condition, where visual and haptic feedback were misaligned.

Discussion

These findings provide empirical evidence about the neurofunctional basis of the enhanced motor performance with simulated synthetic force feedback in the presence of teleoperation delays. The study highlights the potential for immediate haptic feedback to mitigate the adverse effects of operational delays, thereby improving the efficacy of teleoperation in critical applications.

Toward a neuroscience of natural behavior

One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.

No support for a causal role of primary motor cortex in construing meaning from language: An rTMS study

Embodied cognition theories predict a functional involvement of sensorimotor processes in language understanding. In a preregistered experiment, we tested this idea by investigating whether interfering with primary motor cortex (M1) activation can change how people construe meaning from action language. Participants were presented with sentences describing actions (e.g., "turning off the light") and asked to choose between two interpretations of their meaning, one more concrete (e.g., "flipping a switch") and another more abstract (e.g., "going to sleep"). Prior to this task, participants' M1 was disrupted using repetitive transcranial magnetic stimulation (rTMS). The results yielded strong evidence against the idea that M1-rTMS affects meaning construction (BF01 > 30). Additional analyses and control experiments suggest that the absence of effect cannot be accounted for by failure to inhibit M1, lack of construct validity of the task, or lack of power to detect a small effect. In sum, these results do not support a causal role for primary motor cortex in building meaning from action language.

Relationship between pain and proprioception among individuals with rotator cuff-related shoulder pain

BACKGROUND

Individuals with rotator cuff-related shoulder pain (RCRSP) have altered proprioception. The relationship between shoulder pain and proprioception is not well understood.

PURPOSE

This study aimed to investigate the relationship between shoulder pain and proprioception.

STUDY DESIGN

This was a cross-sectional comparative study.

METHODS

Twenty-two participants with RCRSP (mean age 27.6 ± 4.8 years) and 22 matched pain-free participants (23.4 ± 2.5 years) performed two upper limb active joint position sense tests: (1) the Upper Limb Proprioception Reaching Test (PRO-Reach; reaching toward seven targets) in centimeters and (2) Biodex System at 90% of maximum internal rotation in degrees. Participants performed three memorization and three reproduction trials blindfolded. The proprioception error (PE) is the difference between the memorized and estimation trials. Pain levels were captured pre- and post-evaluation (11-point Likert Numerical Pain Rating Scale). Relationships between PE and pain were investigated using independent t-tests and Spearman rank correlations.

RESULTS

Overall, 22.7% RCRSP participants indicated an increase in pain following the PRO-Reach (X̅ increase of 1.4 ± 1.5 points), while 59% did so with the Biodex (X̅ increase of 2.3 ± 1.8 points), reflecting a clinically important increase in pain. Weak-to-moderate correlations between pain and PEs were found with the Biodex (r = 0.39-0.53) and weak correlations with the PRO-Reach (r = -0.26 to 0.38). Concerning PEs, no significant differences were found between groups with the Biodex (p = 0.32, effect size d = -0.31 [-0.90 to 0.29]). The RCRSP participants demonstrated lower PEs with the PRO-Reach in elevation compared to pain-free participants (global X̅ = 4.6 ± 1.2 cm vs 5.5 ± 1.5 cm; superior 3.8 ± 2.1 cm vs 5.7 ± 2.9 cm; superior-lateral nondominant targets 4.3 ± 2.2 cm vs 6.1 ± 2.8 cm; p = 0.02-0.05, effect size d = 0.72-0.74 [0.12-1.3]).

CONCLUSIONS

Individuals with RCRSP demonstrated better upper limb proprioception in elevation, suggesting a change to interoception (sensory reweighting) in the presence of pain.

Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling

Spatiotemporal properties of neuronal population activity in cortical motor areas have been subjects of experimental and theoretical investigations, generating numerous interpretations regarding mechanisms for preparing and executing limb movements. Two competing models, representational and dynamical, strive to explain the relationship between movement parameters and neuronal activity. A dynamical model uses the jPCA method that holistically characterizes oscillatory activity in neuron populations by maximizing the data rotational dynamics. Different rotational dynamics interpretations revealed by the jPCA approach have been proposed. Yet, the nature of such dynamics remains poorly understood. We comprehensively analyzed several neuronal-population datasets and found rotational dynamics consistently accounted for by a traveling wave pattern. For quantifying rotation strength, we developed a complex-valued measure, the gyration number. Additionally, we identified parameters influencing rotation extent in the data. Our findings suggest that rotational dynamics and traveling waves are typically the same phenomena, so reevaluation of the previous interpretations where they were considered separate entities is needed.

Rapid Online Corrections for Proprioceptive and Visual Perturbations Recruit Similar Circuits in Primary Motor Cortex

An important aspect of motor function is our ability to rapidly generate goal-directed corrections for disturbances to the limb or behavioral goal. The primary motor cortex (M1) is a key region involved in processing feedback for rapid motor corrections, yet we know little about how M1 circuits are recruited by different sources of sensory feedback to make rapid corrections. We trained two male monkeys (Macaca mulatta) to make goal-directed reaches and on random trials introduced different sensory errors by either jumping the visual location of the goal (goal jump), jumping the visual location of the hand (cursor jump), or applying a mechanical load to displace the hand (proprioceptive feedback). Sensory perturbations evoked a broad response in M1 with ∼73% of neurons (n = 257) responding to at least one of the sensory perturbations. Feedback responses were also similar as response ranges between the goal and cursor jumps were highly correlated (range of r = [0.91, 0.97]) as were the response ranges between the mechanical loads and the visual perturbations (range of r = [0.68, 0.86]). Lastly, we identified the neural subspace each perturbation response resided in and found a strong overlap between the two visual perturbations (range of overlap index, 0.73-0.89) and between the mechanical loads and visual perturbations (range of overlap index, 0.36-0.47) indicating each perturbation evoked similar structure of activity at the population level. Collectively, our results indicate rapid responses to errors from different sensory sources target similar overlapping circuits in M1.

Dynamic causal model application on hierarchical human motor control estimation in visuomotor tasks

Introduction

In brain function research, each brain region has been investigated independently, and how different parts of the brain work together has been examined using the correlations among them. However, the dynamics of how different brain regions interact with each other during time-varying tasks, such as voluntary motion tasks, are still not well-understood.

Methods

To address this knowledge gap, we conducted functional magnetic resonance imaging (fMRI) using target tracking tasks with and without feedback. We identified the motor cortex, cerebellum, and visual cortex by using a general linear model during the tracking tasks. We then employed a dynamic causal model (DCM) and parametric empirical Bayes to quantitatively elucidate the interactions among the left motor cortex (ML), right cerebellum (CBR) and left visual cortex (VL), and their roles as higher and lower controllers in the hierarchical model.

Results

We found that the tracking task with visual feedback strongly affected the modulation of connection strength in ML → CBR and ML↔VL. Moreover, we found that the modulation of VL → ML, ML → ML, and ML → CBR by the tracking task with visual feedback could explain individual differences in tracking performance and muscle activity, and we validated these findings by leave-one-out cross-validation.

Discussion

We demonstrated the effectiveness of our approach for understanding the mechanisms underlying human motor control. Our proposed method may have important implications for the development of new technologies in personalized interventions and technologies, as it sheds light on how different brain regions interact and work together during a motor task.

A Cortical Mechanism Linking Saliency Detection and Motor Reactivity in Rhesus Monkeys

Sudden and surprising sensory events trigger neural processes that swiftly adjust behavior. To study the phylogenesis and the mechanism of this phenomenon, we trained two male rhesus monkeys to keep a cursor inside a visual target by exerting force on an isometric joystick. We examined the effect of surprising auditory stimuli on exerted force, scalp electroencephalographic (EEG) activity, and local field potentials (LFPs) recorded from the dorsolateral prefrontal cortex. Auditory stimuli elicited (1) a biphasic modulation of isometric force, a transient decrease followed by a corrective tonic increase, and (2) EEG and LFP deflections dominated by two large negative-positive waves (N70 and P130). The EEG potential was symmetrical and maximal at the scalp vertex, highly reminiscent of the human "vertex potential." Electrocortical potentials and force were tightly coupled: the P130 amplitude predicted the magnitude of the corrective force increase, particularly in the LFPs recorded from deep rather than superficial cortical layers. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to salient sensory events.Significance Statement Survival in the natural world depends on an animal's capacity to adapt ongoing behavior to abrupt unexpected events. To study the neural mechanisms underlying this capacity, we trained monkeys to apply constant force on a joystick while we recorded their brain activity from the scalp and the prefrontal cortex contralateral to the hand holding the joystick. Unexpected auditory stimuli elicited a biphasic force modulation: a transient reduction followed by a corrective adjustment. The same stimuli also elicited EEG and LFP responses, dominated by a biphasic wave that predicted the magnitude of the behavioral adjustment. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to unexpected events.

Pose analysis in free-swimming adult zebrafish, Danio rerio : "fishy" origins of movement design

Movement requires maneuvers that generate thrust to either make turns or move the body forward in physical space. The computational space for perpetually controlling the relative position of every point on the body surface can be vast. We hypothesize the evolution of efficient design for movement that minimizes active (neural) control by leveraging the passive (reactive) forces between the body and the surrounding medium at play. To test our hypothesis, we investigate the presence of stereotypical postures during free-swimming in adult zebrafish, Danio rerio . We perform markerless tracking using DeepLabCut, a deep learning pose estimation toolkit, to track geometric relationships between body parts. To identify putative clusters of postural configurations obtained from twelve freely behaving zebrafish, we use unsupervised multivariate time-series analysis (B-SOiD machine learning software). When applied to single individuals, this method reveals a best-fit for 36 to 50 clusters in contrast 86 clusters for data pooled from all 12 animals. The centroids of each cluster obtained over 14,000 sequential frames recorded for a single fish represent an apriori classification into relatively stable "target body postures" and inter-pose "transitional postures" that lead to and away from a target pose. We use multidimensional scaling of mean parameter values for each cluster to map cluster-centroids within two dimensions of postural space. From a post-priori visual analysis, we condense neighboring postural variants into 15 superclusters or core body configurations. We develop a nomenclature specifying the anteroposterior level/s (upper, mid and lower) and degree of bending. Our results suggest that constraining bends to mainly three levels in adult zebrafish preempts the neck, fore- and hindlimb design for maneuverability in land vertebrates.

Learning context shapes bimanual control strategy and generalization of novel dynamics

Bimanual movements are fundamental components of everyday actions, yet the underlying mechanisms coordinating adaptation of the two hands remain unclear. Although previous studies highlighted the contextual effect of kinematics of both arms on internal model formation, we do not know how the sensorimotor control system associates the learned memory with the experienced states in bimanual movements. More specifically, can, and if so, how, does the sensorimotor control system combine multiple states from different effectors to create and adapt a motor memory? Here, we tested motor memory formation in two groups with a novel paradigm requiring the encoding of the kinematics of the right hand to produce the appropriate predictive force on the left hand. While one group was provided with training movements in which this association was evident, the other group was trained on conditions in which this association was ambiguous. After adaptation, we tested the encoding of the learned motor memory by measuring the generalization to new movement combinations. While both groups adapted to the novel dynamics, the evident group showed a weighted encoding of the learned motor memory based on movements of the other (right) hand, whereas the ambiguous group exhibited mainly same (left) hand encoding in bimanual trials. Despite these differences, both groups demonstrated partial generalization to unimanual movements of the left hand. Our results show that motor memories can be encoded depending on the motion of other limbs, but that the training conditions strongly shape the encoding of the motor memory formation and determine the generalization to novel contexts.

Muscular reflex gains reflect changes of mind in reaching

Decisions for action are accompanied by a continual processing of sensory information, sometimes resulting in a revision of the initial choice, called a change of mind (CoM). Although the motor system is tuned during the formation of a reach decision, it is unclear whether its preparatory state differs between CoM and non-CoM decisions. To test this, participants (n = 14) viewed a random-dot motion (RDM) stimulus of various coherence levels for a random viewing duration. At the onset of a mechanical perturbation that rapidly stretched the pectoralis muscle, they indicated the perceived motion direction by making a reaching movement to one of two targets. Using electromyography (EMG), we quantified the reflex gains of the pectoralis and posterior deltoid muscles. Results show that reflex gains scaled with both the coherence level and the viewing duration of the stimulus. We fit a drift diffusion model (DDM) to the behavioral choices. The decision variable (DV), derived from the DDM, correlated well with the measured reflex gain at the single-trial level. However, when matched on DV magnitude, reflex gains were significantly lower in CoM than non-CoM trials. We conclude that the internal state of the motor system, as measured by the spinal reflexes, reflects the continual deliberation on sensory evidence for action selection, including the postdecisional evidence that can lead to a change of mind.NEW & NOTEWORTHY Using behavioral findings, EMG, and computational modeling, we show that not only the perceptual decision outcome but also the accumulating evidence for that outcome is continuously sent to the relevant muscles. Moreover, we show that an upcoming change of mind can be detected in the motor periphery, suggesting that a correlate of the internal decision making process is being sent along.

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.

Measuring upper limb active joint position sense: Introducing a new clinical tool - The Upper Limb Proprioception Reaching Test

BACKGROUND

Proprioception is our sense of body awareness, including the sub-category of active joint position sense (AJPS). AJPS is fundamental to joint stability and movement coordination. Despite its importance, there remain few confident ways to measure upper limb AJPS in a clinic.

OBJECTIVE

To assess a new AJPS clinical tool, the Upper Limb Proprioception Reaching Test (PRO-Reach; seven targets), for discriminant validity, intra-rater and absolute reliability.

DESIGN

Cross-sectional measurement study.

METHODS

Seventy-five healthy participants took part in a single session with 2 consecutive evaluations (E1 and E2) (within-day reliability). Twenty participants were randomly selected to perform a dominant shoulder fatigue protocol (discriminant validity), whereafter a third evaluation was repeated (E3). The PRO-Reach was analyzed with paired t tests (discriminant validity), intra-class correlation coefficients (ICCs) and minimal detectable change [MDC]) (intra-rater: within-day and between-trial relative and absolute reliability).

RESULTS

The PRO-Reach supports moderate (mostly superior targets) to excellent (mostly inferior targets) reliability. Between-trial ICCs (T1/T2/T3) varied between 0.72 and 0.90, and within-day (E1/E2) ICCs between 0.45 and 0.72, with associated MDC95 values (3.9-5.0 cm). The overall scores (seven targets) supported the strongest within-day reliability (ICC = 0.77). The inferior targets demonstrated the highest between-trial and within-day reliability (ICCs = 0.90 and 0.72). A fatigue effect was found with the superior and superior-lateral targets (P < .05).

CONCLUSIONS

The inferior targets and overall scores demonstrate the strongest reliability. The use of the PRO-Reach tool may be suitable for clinical use upon further psychometric testing amongst pathological populations.

LEVEL OF EVIDENCE

Level III cross-sectional study.

Representational drift as a window into neural and behavioural plasticity

Large-scale recordings of neural activity over days and weeks have revealed that neural representations of familiar tasks, precepts and actions continually evolve without obvious changes in behaviour. We hypothesise that this steady drift in neural activity and accompanying physiological changes is due in part to the continuous application of a learning rule at the cellular and population level. Explicit predictions of this drift can be found in neural network models that use iterative learning to optimise weights. Drift therefore provides a measurable signal that can reveal systems-level properties of biological plasticity mechanisms, such as their precision and effective learning rates.

Kinematic markers of skill in first-person shooter video games

Video games present a unique opportunity to study motor skill. First-person shooter (FPS) games have particular utility because they require visually guided hand movements that are similar to widely studied planar reaching tasks. However, there is a need to ensure the tasks are equivalent if FPS games are to yield their potential as a powerful scientific tool for investigating sensorimotor control. Specifically, research is needed to ensure that differences in visual feedback of a movement do not affect motor learning between the two contexts. In traditional tasks, a movement will translate a cursor across a static background, whereas FPS games use movements to pan and tilt the view of the environment. To this end, we designed an online experiment where participants used their mouse or trackpad to shoot targets in both visual contexts. Kinematic analysis showed player movements were nearly identical between contexts, with highly correlated spatial and temporal metrics. This similarity suggests a shared internal model based on comparing predicted and observed displacement vectors rather than primary sensory feedback. A second experiment, modeled on FPS-style aim-trainer games, found movements exhibited classic invariant features described within the sensorimotor literature. We found the spatial metrics tested were significant predictors of overall task performance. More broadly, these results show that FPS games offer a novel, engaging, and compelling environment to study sensorimotor skill, providing the same precise kinematic metrics as traditional planar reaching tasks.

Gravity-efficient motor control is associated with contraction-dependent intracortical inhibition

In humans, moving efficiently along the gravity axis requires shifts in muscular contraction modes. Raising the arm up involves shortening contractions of arm flexors, whereas the reverse movement can rely on lengthening contractions with the help of gravity. Although this control mode is universal, the neuromuscular mechanisms that drive gravity-oriented movements remain unknown. Here, we designed neurophysiological experiments that aimed to track the modulations of cortical, spinal, and muscular outputs of arm flexors during vertical movements with specific kinematics (i.e., optimal motor commands). We report a specific drop of corticospinal excitability during lengthening versus shortening contractions, with an increase of intracortical inhibition and no change in spinal motoneuron responsiveness. We discuss these contraction-dependent modulations of the supraspinal motor output in the light of feedforward mechanisms that may support gravity-tuned motor control. Generally, these results shed a new perspective on the neural policy that optimizes movement control along the gravity axis.

The nervous system tunes sensorimotor gains when reaching in variable mechanical environments

Humans often move in the presence of mechanical disturbances that can vary in direction and amplitude throughout movement. These disturbances can jeopardize the outcomes of our actions, such as when drinking from a glass of water on a turbulent flight or carrying a cup of coffee while walking on a busy sidewalk. Here, we examine control strategies that allow the nervous system to maintain performance when reaching in the presence of mechanical disturbances that vary randomly throughout movement. Healthy participants altered their control strategies to make movements more robust against disturbances. The change in control was associated with faster reaching movements and increased responses to proprioceptive and visual feedback that were tuned to the variability of the disturbances. Our findings highlight that the nervous system exploits a continuum of control strategies to increase its responsiveness to sensory feedback when reaching in the presence of increasingly variable physical disturbances.

Somatosensory Information in Skilled Motor Performance: A Narrative Review

Historically, research aimed at improving motor performance has largely focused on the neural processes involved in motor execution due to their role in muscle activation. However, accompanying somatosensory and proprioceptive sensory information is also vitally involved in performing motor skills. Here we review research from interdisciplinary fields to provide a description for how somatosensation informs the successful performance of motor skills as well as emphasize the need for careful selection of study methods to isolate the neural processes involved in somatosensory perception. We also discuss upcoming strategies of intervention that have been used to improve performance via somatosensory targets. We believe that a greater appreciation for somatosensation's role in motor learning and control will enable researchers and practitioners to develop and apply methods for the enhancement of human performance that will benefit clinical, healthy, and elite populations alike.

Humans need only 200 ms to generate posture-specific muscle activation patterns for successful vertical jumps in reaction to an auditory trigger

Introduction

It is currently unknown how the central nervous system controls ballistic whole-body movements like vertical jumps. Here we set out to study the time frame of generating muscle activation patterns for maximum-effort jumps from different initial postures.

Methods

We had ten healthy male participants make a slow countermovement from an upright position and initiate a maximal vertical jump as soon as possible following an auditory trigger. The trigger was produced when hip height dropped below one of three preselected values, unknown in advance to the participant, so that the participant was uncertain about the posture from which to initiate the jump. Furthermore, we determined the ensuing bottom postures reached during jumps, and from these postures had the participants perform maximum-effort squat jumps in two conditions: whenever they felt ready, or as soon as possible following an auditory trigger. Kinematics and ground reaction forces were measured, and electromyograms were collected from gluteus maximus, biceps femoris, rectus femoris, vastus lateralis, gastrocnemius and soleus. For each muscle, we detected activation onsets, as well as reaction times defined as the delay between trigger onset and activation onset.

Results

In the jumps preceded by a slow countermovement, the posture from which to initiate the jump was unknown before trigger onset. Nevertheless, in these jumps, posture-specific muscle activation patterns were already released within 200 ms after trigger onset and reaction times were not longer and jump heights not less than in squat jumps from corresponding bottom postures.

Discussion

Our findings suggest that the generation of muscle activation patterns for jumping does not start before trigger onset and requires only about 200 ms.

The integration of action-oriented multisensory information from target and limb within the movement planning and execution

The planning and execution of a grasping or reaching movement toward targets we sense with the other hand requires integrating multiple sources of sensory information about the limb performing the movement and the target of the action. In the last two decades, several sensory and motor control theories have thoroughly described how this multisensory-motor integration process occurs. However, even though these theories were very influential in their respective field, they lack a clear, unified vision of how target-related and movement-related multisensory information integrates within the action planning and execution phases. This brief review aims to summarize the most influential theories in multisensory integration and sensory-motor control by underscoring their critical points and hidden connections, providing new ideas on the multisensory-motor integration process. Throughout the review, I wll propose an alternative view of how the multisensory integration process unfolds along the action planning and execution and I will make several connections with the existent multisensory-motor control theories.

Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex

The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central open questions that need to be answered to understand the neural substrates of motor control. We develop a recurrent neural network model that recapitulates the temporal evolution of neuronal activity recorded from the primary motor cortex of a macaque monkey during an instructed delayed-reach task. In particular, it reproduces the observed dynamic patterns of covariation between neural activity and the direction of motion. We explore the hypothesis that the observed dynamics emerges from a synaptic connectivity structure that depends on the preferred directions of neurons in both preparatory and movement-related epochs, and we constrain the strength of both synaptic connectivity and external input parameters from data. While the model can reproduce neural activity for multiple combinations of the feedforward and recurrent connections, the solution that requires minimum external inputs is one where the observed patterns of covariance are shaped by external inputs during movement preparation, while they are dominated by strong direction-specific recurrent connectivity during movement execution. Our model also demonstrates that the way in which single-neuron tuning properties change over time can explain the level of orthogonality of preparatory and movement-related subspaces.

Large-scale high-density brain-wide neural recording in nonhuman primates

High-density, integrated silicon electrodes have begun to transform systems neuroscience, by enabling large-scale neural population recordings with single cell resolution. Existing technologies, however, have provided limited functionality in nonhuman primate species such as macaques, which offer close models of human cognition and behavior. Here, we report the design, fabrication, and performance of Neuropixels 1.0-NHP, a high channel count linear electrode array designed to enable large-scale simultaneous recording in superficial and deep structures within the macaque or other large animal brain. These devices were fabricated in two versions: 4416 electrodes along a 45 mm shank, and 2496 along a 25 mm shank. For both versions, users can programmatically select 384 channels, enabling simultaneous multi-area recording with a single probe. We demonstrate recording from over 3000 single neurons within a session, and simultaneous recordings from over 1000 neurons using multiple probes. This technology represents a significant increase in recording access and scalability relative to existing technologies, and enables new classes of experiments involving fine-grained electrophysiological characterization of brain areas, functional connectivity between cells, and simultaneous brain-wide recording at scale.

μ-band desynchronization in the contralateral central and central-parietal areas predicts proprioceptive acuity

Introduction

Position sense, which belongs to the sensory stream called proprioception, is pivotal for proper movement execution. Its comprehensive understanding is needed to fill existing knowledge gaps in human physiology, motor control, neurorehabilitation, and prosthetics. Although numerous studies have focused on different aspects of proprioception in humans, what has not been fully investigated so far are the neural correlates of proprioceptive acuity at the joints.

Methods

Here, we implemented a robot-based position sense test to elucidate the correlation between patterns of neural activity and the degree of accuracy and precision exhibited by the subjects. Eighteen healthy participants performed the test, and their electroencephalographic (EEG) activity was analyzed in its μ band (8–12 Hz), as the frequency band related to voluntary movement and somatosensory stimulation.

Results

We observed a significant positive correlation between the matching error, representing proprioceptive acuity, and the strength of the activation in contralateral hand motor and sensorimotor areas (left central and central-parietal areas). In absence of visual feedback, these same regions of interest (ROIs) presented a higher activation level compared to the association and visual areas. Remarkably, central and central-parietal activation was still observed when visual feedback was added, although a consistent activation in association and visual areas came up.

Conclusion

Summing up, this study supports the existence of a specific link between the magnitude of activation of motor and sensorimotor areas related to upper limb proprioceptive processing and the proprioceptive acuity at the joints.

Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: a preliminary study

An important window into sensorimotor function is how humans interact and stop moving projectiles, such as stopping a door from closing shut or catching a ball. Previous studies have suggested that humans time the initiation and modulate the amplitude of their muscle activity based on the momentum of the approaching object. However, real-world experiments are constrained by laws of mechanics, which cannot be manipulated experimentally to probe the mechanisms of sensorimotor control and learning. An augmented-reality variant of such tasks allows for experimental manipulation of the relationship between motion and force to obtain novel insights into how the nervous system prepares motor responses to interact with moving stimuli. Existing paradigms for studying interactions with moving projectiles use massless objects and are primarily focused on quantifying gaze and hand kinematics. Here, we developed a novel collision paradigm using a robotic manipulandum where participants mechanically stopped a virtual object moving in the horizontal plane. On each block of trials, we varied the virtual object's momentum by increasing either its velocity or mass. Participants stopped the object by applying a force impulse that matched the object momentum. We observed that hand force increased as a function of object momentum linked to changes in virtual mass or velocity, similar to results from studies involving catching free-falling objects. In addition, increasing object velocity resulted in later onset of hand force relative to the impending time-to-contact. These findings show that the present paradigm can be used to determine how humans process projectile motion for hand motor control.

A bicycle can be balanced by stochastic optimal feedback control but only with accurate speed estimates

Balancing a bicycle is typical for the balance control humans perform as a part of a whole range of behaviors (walking, running, skating, skiing, etc.). This paper presents a general model of balance control and applies it to the balancing of a bicycle. Balance control has both a physics (mechanics) and a neurobiological component. The physics component pertains to the laws that govern the movements of the rider and his bicycle, and the neurobiological component pertains to the mechanisms via which the central nervous system (CNS) uses these laws for balance control. This paper presents a computational model of this neurobiological component, based on the theory of stochastic optimal feedback control (OFC). The central concept in this model is a computational system, implemented in the CNS, that controls a mechanical system outside the CNS. This computational system uses an internal model to calculate optimal control actions as specified by the theory of stochastic OFC. For the computational model to be plausible, it must be robust to at least two inevitable inaccuracies: (1) model parameters that the CNS learns slowly from interactions with the CNS-attached body and bicycle (i.e., the internal noise covariance matrices), and (2) model parameters that depend on unreliable sensory input (i.e., movement speed). By means of simulations, I demonstrate that this model can balance a bicycle under realistic conditions and is robust to inaccuracies in the learned sensorimotor noise characteristics. However, the model is not robust to inaccuracies in the movement speed estimates. This has important implications for the plausibility of stochastic OFC as a model for motor control.

Sensorimotor feedback loops are selectively sensitive to reward

Although it is well established that motivational factors such as earning more money for performing well improve motor performance, how the motor system implements this improvement remains unclear. For instance, feedback-based control, which uses sensory feedback from the body to correct for errors in movement, improves with greater reward. But feedback control encompasses many feedback loops with diverse characteristics such as the brain regions involved and their response time. Which specific loops drive these performance improvements with reward is unknown, even though their diversity makes it unlikely that they are contributing uniformly. We systematically tested the effect of reward on the latency (how long for a corrective response to arise?) and gain (how large is the corrective response?) of seven distinct sensorimotor feedback loops in humans. Only the fastest feedback loops were insensitive to reward, and the earliest reward-driven changes were consistently an increase in feedback gains, not a reduction in latency. Rather, a reduction of response latencies only tended to occur in slower feedback loops. These observations were similar across sensory modalities (vision and proprioception). Our results may have implications regarding feedback control performance in athletic coaching. For instance, coaching methodologies that rely on reinforcement or 'reward shaping' may need to specifically target aspects of movement that rely on reward-sensitive feedback responses.

Dynamic motor practice improves movement accuracy, force control and leads to increased corticospinal excitability compared to isometric motor practice

The central nervous system has a remarkable ability to plan motor actions, to predict and monitor the sensory consequences during and following motor actions and integrate these into future actions. Numerous studies investigating human motor learning have employed tasks involving either force control during isometric contractions or position control during dynamic tasks. To our knowledge, it remains to be elucidated how motor practice with an emphasis on position control influences force control and vice versa. Furthermore, it remains unexplored whether these distinct types of motor practice are accompanied by differential effects on corticospinal excitability. In this study, we tested motor accuracy and effects of motor practice in a force or position control task allowing wrist flexions of the non-dominant hand in the absence of online visual feedback. For each trial, motor performance was quantified as errors (pixels) between the displayed target and the movement endpoint. In the main experiment, 46 young adults were randomized into three groups: position control motor practice (PC), force control motor practice (FC), and a resting control group (CON). Following assessment of baseline motor performance in the position and force control tasks, intervention groups performed motor practice with, augmented visual feedback on performance. Motor performance in both tasks was assessed following motor practice. In a supplementary experiment, measures of corticospinal excitability were obtained in twenty additional participants by application of transcranial magnetic stimulation to the primary motor cortex hot spot of the flexor carpi radialis muscle before and following either position or force control motor practice. Following motor practice, accuracy in the position task improved significantly more for PC compared to FC and CON. For the force control task, both the PC and FC group improved more compared to CON. The two types of motor practice thus led to distinct effects including positive between-task transfer accompanying dynamic motor practice The results of the supplementary study demonstrated an increase in corticospinal excitability following dynamic motor practice compared to isometric motor practice. In conclusion, dynamic motor practice improves movement accuracy, and force control and leads to increased corticospinal excitability compared to isometric motor practice.

Human Stabilization of Delay-Induced Instability of Haptic Rendering in a Stiffness Discrimination Task

Towards developing a coupled stability theory for haptic systems, we study the interaction of operators with time-delayed force feedback. In this work, we analyzed and validated experimentally the stability boundaries of an uncoupled system - without considering the human. We then designed an experiment in which the participants used a haptic device to interact with virtual elastic force fields in a stiffness discrimination task. We compared the performance and kinematics of users in uncoupled-unstable and uncoupled-stable conditions and characterized the stabilizing contribution of the users. We found that the users were able to perform the task regardless of the uncoupled-stability conditions. In addition, in uncoupled-unstable conditions, users maintained movement characteristics that were important for exploratory mediation, such as depth and duration of the movement, whereas other characteristics were not preserved. The results were reproduced in a simulation of the human controller that combined an inverse model and an optimal feedback controller. Adequate performance under the uncoupled-unstable yet coupled-stable conditions supports the potential benefit of designing for coupled stability of haptic systems. This could lead to the use of less conservative controllers than state-of-the-art solutions in haptic and teleoperation systems, and advance the fidelity of haptic feedback.

Tapping on a target: dealing with uncertainty about its position and motion

Reaching movements are guided by estimates of the target object's location. Since the precision of instantaneous estimates is limited, one might accumulate visual information over time. However, if the object is not stationary, accumulating information can bias the estimate. How do people deal with this trade-off between improving precision and reducing the bias? To find out, we asked participants to tap on targets. The targets were stationary or moving, with jitter added to their positions. By analysing the response to the jitter, we show that people continuously use the latest available information about the target's position. When the target is moving, they combine this instantaneous target position with an extrapolation based on the target's average velocity during the last several hundred milliseconds. This strategy leads to a bias if the target's velocity changes systematically. Having people tap on accelerating targets showed that the bias that results from ignoring systematic changes in velocity is removed by compensating for endpoint errors if such errors are consistent across trials. We conclude that combining simple continuous updating of visual information with the low-pass filter characteristics of muscles, and adjusting movements to compensate for errors made in previous trials, leads to the precise and accurate human goal-directed movements.

Integrated neural dynamics of sensorimotor decisions and actions

Recent theoretical models suggest that deciding about actions and executing them are not implemented by completely distinct neural mechanisms but are instead two modes of an integrated dynamical system. Here, we investigate this proposal by examining how neural activity unfolds during a dynamic decision-making task within the high-dimensional space defined by the activity of cells in monkey dorsal premotor (PMd), primary motor (M1), and dorsolateral prefrontal cortex (dlPFC) as well as the external and internal segments of the globus pallidus (GPe, GPi). Dimensionality reduction shows that the four strongest components of neural activity are functionally interpretable, reflecting a state transition between deliberation and commitment, the transformation of sensory evidence into a choice, and the baseline and slope of the rising urgency to decide. Analysis of the contribution of each population to these components shows meaningful differences between regions but no distinct clusters within each region, consistent with an integrated dynamical system. During deliberation, cortical activity unfolds on a two-dimensional "decision manifold" defined by sensory evidence and urgency and falls off this manifold at the moment of commitment into a choice-dependent trajectory leading to movement initiation. The structure of the manifold varies between regions: In PMd, it is curved; in M1, it is nearly perfectly flat; and in dlPFC, it is almost entirely confined to the sensory evidence dimension. In contrast, pallidal activity during deliberation is primarily defined by urgency. We suggest that these findings reveal the distinct functional contributions of different brain regions to an integrated dynamical system governing action selection and execution.

Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner

The spiking activity of populations of cortical neurons is well described by the dynamics of a small number of population-wide covariance patterns, the 'latent dynamics'. These latent dynamics are largely driven by the same correlated synaptic currents across the circuit that determine the generation of local field potentials (LFP). Yet, the relationship between latent dynamics and LFPs remains largely unexplored. Here, we characterised this relationship for three different regions of primate sensorimotor cortex during reaching. The correlation between latent dynamics and LFPs was frequency-dependent and varied across regions. However, for any given region, this relationship remained stable throughout the behaviour: in each of primary motor and premotor cortices, the LFP-latent dynamics correlation profile was remarkably similar between movement planning and execution. These robust associations between LFPs and neural population latent dynamics help bridge the wealth of studies reporting neural correlates of behaviour using either type of recordings.

Nonlinear optimal control of a mean-field model of neural population dynamics

We apply the framework of nonlinear optimal control to a biophysically realistic neural mass model, which consists of two mutually coupled populations of deterministic excitatory and inhibitory neurons. External control signals are realized by time-dependent inputs to both populations. Optimality is defined by two alternative cost functions that trade the deviation of the controlled variable from its target value against the “strength” of the control, which is quantified by the integrated 1- and 2-norms of the control signal. We focus on a bistable region in state space where one low- (“down state”) and one high-activity (“up state”) stable fixed points coexist. With methods of nonlinear optimal control, we search for the most cost-efficient control function to switch between both activity states. For a broad range of parameters, we find that cost-efficient control strategies consist of a pulse of finite duration to push the state variables only minimally into the basin of attraction of the target state. This strategy only breaks down once we impose time constraints that force the system to switch on a time scale comparable to the duration of the control pulse. Penalizing control strength via the integrated 1-norm (2-norm) yields control inputs targeting one or both populations. However, whether control inputs to the excitatory or the inhibitory population dominate, depends on the location in state space relative to the bifurcation lines. Our study highlights the applicability of nonlinear optimal control to understand neuronal processing under constraints better.