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.

Optimization of modularity during development to simplify walking control across multiple steps.

Introduction: Walking in adults relies on a small number of modules, reducing the number of degrees of freedom that needs to be regulated by the central nervous system (CNS). While walking in toddlers seems to also involve a small number of modules when considering averaged or single-step data, toddlers produce a high amount of variability across strides, and the extent to which this variability interacts with modularity remains unclear.

Methods: Electromyographic activity from 10 bilateral lower limb muscles was recorded in both adults ( = 12) and toddlers ( = 12) over 8 gait cycles.

Human movement modifications induced by different levels of transparency of an active upper limb exoskeleton.

Active upper limb exoskeletons are a potentially powerful tool for neuromotor rehabilitation. This potential depends on several basic control modes, one of them being . In this control mode, the exoskeleton must follow the human movement without altering it, which theoretically implies null interaction efforts.

Reoptimization of single-joint motor patterns to non-Earth gravity torques induced by a robotic exoskeleton.

Gravity is a ubiquitous component of our environment that we have learned to optimally integrate in movement control. Yet, altered gravity conditions arise in numerous applications from space exploration to rehabilitation, thereby pressing the sensorimotor system to adapt. Here, we used a robotic exoskeleton to reproduce the elbow joint-level effects of arbitrary gravity fields ranging from 1g to -1g, passing through Mars- and Moon-like gravities, and tested whether humans can reoptimize their motor patterns accordingly.

The value of time in the invigoration of human movements when interacting with a robotic exoskeleton.

Time and effort are thought to be subjectively balanced during the planning of goal-directed actions, thereby setting the vigor of volitional movements. Theoretical models predicted that the value of time should then amount to high levels of effort. However, the time-effort trade-off has so far only been studied for a narrow range of efforts.

Generating variability from motor primitives during infant locomotor development.

Motor variability is a fundamental feature of developing systems allowing motor exploration and learning. In human infants, leg movements involve a small number of basic coordination patterns called locomotor primitives, but whether and when motor variability could emerge from these primitives remains unknown. Here we longitudinally followed 18 infants on 2-3 time points between birth (~4 days old) and walking onset (~14 months old) and recorded the activity of their leg muscles during locomotor or rhythmic movements.

From Motivation to Action: Action Cost Better Predicts Changes in Premovement Beta-Band Activity than Speed.

Although premovement beta-band event-related desynchronization (β-ERD; 13-30 Hz) from sensorimotor regions is modulated by movement speed, current evidence does not support a strict monotonic association between the two. Given that β-ERD is thought to increase information encoding capacity, we tested the hypothesis that it might be related to the expected neurocomputational cost of movement, here referred to as action cost. Critically, action cost is greater both for slow and fast movements compared with a medium or "preferred" speed.

A Trade-Off between Complexity and Interaction Quality for Upper Limb Exoskeleton Interfaces.

Exoskeletons are among the most promising devices dedicated to assisting human movement during reeducation protocols and preventing musculoskeletal disorders at work. However, their potential is currently limited, partially because of a fundamental contradiction impacting their design. Indeed, increasing the interaction quality often requires the inclusion of passive degrees of freedom in the design of human-exoskeleton interfaces, which increases the exoskeleton's inertia and complexity.

On the perception of movement vigour.

It is common to get the impression that someone moves rather slowly or quickly in everyday life. In motor control, the natural pace of movement is captured by the concept of vigour, which is often quantified from the speed or duration of goal-directed actions. A common phenomenon, here referred to as the , is that preferred speed and duration idiosyncratically increase with the magnitude of the motion.

Evidence for a cost of time in the invigoration of isometric reaching movements.

How the brain determines the vigor of goal-directed movements is a fundamental question in neuroscience. Recent evidence has suggested that vigor results from a trade-off between a cost related to movement production (cost of movement) and a cost related to our brain's tendency to temporally discount the value of future reward (cost of time). However, whether it is critical to hypothesize a cost of time to explain the vigor of basic reaching movements with intangible reward is unclear because the cost of movement may be theoretically sufficient for this purpose.

Human Weight Compensation With a Backdrivable Upper-Limb Exoskeleton: Identification and Control.

Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb's weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis.

Machine Learning of Motion Statistics Reveals the Kinematic Signature of the Identity of a Person in Sign Language.

Sign language (SL) motion contains information about the identity of a signer, as does voice for a speaker or gait for a walker. However, how such information is encoded in the movements of a person remains unclear. In the present study, a machine learning model was trained to extract the motion features allowing for the automatic identification of signers.

Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision.

Human movements with or without vision exhibit timing (i.e. speed and duration) and variability characteristics which are not well captured by existing computational models.

A cross-species neural integration of gravity for motor optimization.

Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain shapes motor patterns that use gravity effects to minimize muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here, we specifically investigate gravity-related movement properties by analyzing muscular activation patterns during single-degree-of-freedom arm movements in various directions. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic electromyograms (EMGs) present systematic negative phases.

The Dorsal Striatum Energizes Motor Routines.

The dorsal striatum (dS) has been implicated in storing procedural memories and controlling movement kinematics. Since procedural memories are expressed through movements, the exact nature of the dS function has proven difficult to delineate. Here, we challenged rats in complementary locomotion-based tasks designed to alleviate this confound.

Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction.

Understanding the underpinnings of biological motor control is an important issue in movement neuroscience. Optimal control theory is a leading framework to rationalize this problem in computational terms. Previously, optimal control models have been devised either in deterministic or in stochastic settings to account for different aspects of motor control (e.

Modularity underlying the performance of unusual locomotor tasks inspired by developmental milestones.

Motor behaviors are often hypothesized to be set up from the combination of a small number of modules encoded in the central nervous system. These modules are thought to combine such that a variety of motor tasks can be realized, from reproducible tasks such as walking to more unusual locomotor tasks that typically exhibit more step-by-step variability. We investigated the impact of step-by-step variability on the modular architecture of unusual tasks compared with walking.

Vigor of reaching, walking, and gazing movements: on the consistency of interindividual differences.

Movement vigor is an important feature of motor control that is thought to originate from cortico-basal ganglia circuits and processes shared with decision-making, such as temporal reward discounting. Accordingly, vigor may be related to one's relationship with time, which may, in turn, reflect a general trait-like feature of individuality. While significant interindividual differences of vigor have been typically reported for isolated motor tasks, little is known about the consistency of such differences across tasks and movement effectors.

Vigour of self-paced reaching movement: cost of time and individual traits.

People usually move at a self-selected pace in everyday life. Yet, the principles underlying the formation of human movement vigour remain unclear, particularly in view of intriguing inter-individual variability. It has been hypothesized that how the brain values time may be the cornerstone of such differences, beyond biomechanics.

Deciphering the functional role of spatial and temporal muscle synergies in whole-body movements.

Voluntary movement is hypothesized to rely on a limited number of muscle synergies, the recruitment of which translates task goals into effective muscle activity. In this study, we investigated how to analytically characterize the functional role of different types of muscle synergies in task performance. To this end, we recorded a comprehensive dataset of muscle activity during a variety of whole-body pointing movements.

Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions.

The modular control hypothesis suggests that motor commands are built from precoded modules whose specific combined recruitment can allow the performance of virtually any motor task. Despite considerable experimental support, this hypothesis remains tentative as classical findings of reduced dimensionality in muscle activity may also result from other constraints (biomechanical couplings, data averaging or low dimensionality of motor tasks). Here we assessed the effectiveness of modularity in describing muscle activity in a comprehensive experiment comprising 72 distinct point-to-point whole-body movements during which the activity of 30 muscles was recorded.

Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint.

The study aimed at investigating the extent to which the brain adaptively exploits or compensates interaction torque (IT) during movement control in various velocity and load conditions. Participants performed arm pointing movements toward a horizontal plane without a prescribed reach endpoint at slow, neutral and rapid speeds and with/without load attached to the forearm. Experimental results indicated that IT overall contributed to net torque (NT) to assist the movement, and that such contribution increased with limb inertia and instructed speed and led to hand trajectory variations.