Biology subjects

Gaveau, J.

Publications and source records attributed to Gaveau, J..

15 recordsLinked to original sources

bioRxiv2026

Reward and punishment differentially shape basketball free-throw learning

Motor learning is shaped by motivational context: punishment can accelerate initial learning, whereas reward enhances memory retention. Yet it remains unclear whether the dissociable effects of reward and punishment observed in laboratory tasks generalize to complex real-world skills. Here, we tested this idea using a naturalistic motor task--basketball free-throw shooting. Sixty-eight participants trained under four motivational contexts that differed only in how points were awarded for each pair of consecutive shots: control (standard scoring), reward (bonus points for two consecutive successful shots), punishment (penalty for two consecutive missed shots), or mixed (both bonus and penalty). Performance was assessed before training, immediately after, and 1 and 3 days later. Punishment and mixed schedules significantly improved early acquisition, resulting in higher accuracy immediately after training compared to the control and reward conditions. This advantage emerged during the first training block, indicating a rapid motivational influence on performance. In contrast, reward selectively enhanced offline consolidation: three days after training, the reward group showed the largest gains in accuracy, outperforming both the control and punishment groups. The mixed schedule produced quick early gains similar to punishment, but achieved smaller long-term improvements than reward. Consistent with these findings, individual punishment sensitivity was associated with gains in acquisition, while reward sensitivity correlated with offline improvements. Together, these findings demonstrate dissociable effects of motivational valence on the acquisition and consolidation of a complex real-world motor skill. More generally, they position motivational interventions as simple and cost-effective strategies to enhance rehabilitation and sports training.

neuroscience↗

bioRxiv2025

Following the Robot's Lead: Predicting Human and Robot Movement from EEG in a Motor Learning HRI Task

Human-robot interaction (HRI) offers unique opportunities to study the neuroscience of human motor control through controlled and reproducible sensory stimuli. In this study, we introduce an innovative neuroscience-HRI framework inspired by the Serial Reaction Time (SRT) task, that combines EEG with a task where a humanoid robot performs preprogrammed movement sequences that are mirrored by a human participant in real time. The use of a humanoid robot ensures precise and repeatable sensory-motor stimuli in the 3D peripersonal space of the participant, providing experimental conditions that may be challenging to replicate with traditional methods. Behavioral performance is assessed by measuring the temporal lag between human and robot movements, which decreases with training, reflecting motor sequence learning. Concurrently, EEG data from the human participant is analyzed to reveal neural correlates of learning and movement dynamics. Event-Related Spectral Perturbations (ERSP) in theta, mu, and beta frequency bands demonstrate distinct patterns associated with rest, fixation, and movement. Furthermore, the ERSP changes over successive trials reflect the progression of sequence learning, highlighting the relationship between neural oscillations and motor learning. A Markov-Switching Linear Regression model further decodes EEG signals to predict movement parameters including both human and robot position and velocity in a time-resolved manner. Our findings highlight the potential of HRI as a robust platform for neuroscience research and underscore the value of EEG-based neural decoding in understanding motor sequence learning. This work suggests further advances for integrating robotics into neuroscience and rehabilitation research.

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bioRxiv2024

Evidence for flexible motor costs in vertical arm movements: reduced gravity-related effort minimization under high accuracy constraints

The central nervous system (CNS) is thought to use motor strategies that minimize several criteria, such as end-point variability or effort, to plan optimal motor patterns. In the case of vertical arm movements, a large body of literature demonstrated that the brain uses a motor strategy that takes advantage of the mechanical effects of gravity to minimize muscle effort. Results from other studies suggested that the relative importance of each criterion may vary according to the tasks constraints. For example, it could be hypothesized that reduced end-point variability driven by high accuracy demands is detrimental to effort minimization. The present study probes this specific hypothesis using the framework of gravity-related effort minimization. We asked twenty young healthy participants to perform vertical arm reaching movements towards targets whose size varied across conditions. We recorded the arm kinematics and electromyographic activities of the anterior deltoid to study two well-known motor signatures of the gravity-related optimization process; i.e., directional asymmetries on velocity profiles and negative epochs on phasic muscular activities. The results showed that both indices were reduced as target size decreased, demonstrating that the gravity-related optimization process was reduced under high accuracy constraints. This phenomenon is consistent with the use of a trade-off strategy between effort and end-point variability. More generally, it suggests that the CNS is able to appropriately modulate the relative importance of varied motor costs when facing varying task demands.

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bioRxiv2024

Targeting a specific motor control process reveals an age-related compensation that adapts movement to gravity environment

As the global population ages, it is crucial to understand sensorimotor compensation mechanisms. These mechanisms are thought to enable older adults to remain in good physical health, but despite important research efforts, they remain essentially chimeras. A major problem with their identification is the ambiguous interpretation of age-related alterations. Whether a change reflects deterioration or compensation is difficult to determine. Here we compared the electromyographic and kinematic patterns of different motor tasks in younger (n = 20; mean age = 23.6 years) and older adults (n = 24; mean age = 72 years). Building on the knowledge that humans take advantage of gravity effects to minimize their muscle effort, we probed the ability of younger and older adults to plan energetically efficient movement during arm-only and whole-body movements. In line with previous studies and compared to younger adults, muscle activation patterns revealed that older adults used a less efficient movement strategy during whole-body movement tasks. We found that this age-related alteration was task-specific. It did not affect arm movements, thereby supporting the hypothesis that healthy older adults maintain the ability to plan energetically efficient movements. More importantly, we found that the reduced whole-body movement efficiency was correlated with kinematic measures of balance control (i.e., the center-of-mass movement amplitude and speed). The more efficient the movement strategy, the more challenging the balance. Overall, these results suggest that reduced movement efficiency in healthy older adults does not reflect a deterioration but rather a compensation process that adapts movement strategy to the task specificities. When balance is at stake, healthy older adults prefer stability to energy efficiency.

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bioRxiv2023

Tuning for Pointing Direction in Phasic Muscular Activity: Insights From Machine Learning

Arm movements in our daily lives have to be adjusted for several factors in response to the demands of the environment, for example, speed, direction or distance. Previously, we had shown that arm movement kinematics is optimally tuned to take advantage of gravity effects and minimize muscle effort in various pointing directions and gravity contexts (Gaveau et al., 2016). Here we build upon these results and focus on muscular adjustments. We used Machine Learning to analyze the ensemble activities of multiple muscles recorded during pointing in various directions. The advantage of such a technique would be the observation of patterns in collective muscular activity that may not be noticed using univariate statistics. By providing an index of multimuscle activity, the Machine Learning analysis brought to light several features of tuning for pointing direction. In attempting to trace tuning curves, all comparisons were done with respects to pointing in the horizontal, gravity free plane. We demonstrated that tuning for direction does not take place in a uniform fashion but in a modular manner in which some muscle groups play a primary role. The antigravity muscles were more finely tuned to pointing direction than the gravity muscles. Of note, was their tuning during the first half of downward pointing. As the antigravity muscles were deactivated during this phase, it supported the idea that deactivation is not an on-off function but is tuned to pointing direction. Further support for the tuning of the portions of the phasic EMG containing only negative activity was provided by progressively improving classification accuracies with increasing angular distance from the horizontal. Overall, these results show that the motor system tunes muscle commands to exploit gravity effects and reduce muscular effort. It quantitatively demonstrates that phasic EMG negativity is an essential feature of muscle control.

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bioRxiv2023

Speed-dependent optimization of gravity effects for motor control

Several sensorimotor control studies have provided evidence supporting that the central nervous system optimizes gravitys effects to minimize muscle effort. Recently, this hypothesis has been supported by the consistent observation of direction-specific negative epochs in the phasic electromyographic signal of antigravity muscles during vertical arm movements. This suggests that gravity torque is harvested to produce some of the arms motion. However, further investigation is needed to more finely understand how the CNS integrates gravity effects into muscle commands. Here, we aimed to analyze the phasic muscular activity across varying movement speeds during horizontal and vertical arm movements. We quantified the amount of negativity during acceleration and deceleration phases for all movement directions during fast, natural, and slow movements. We found that the negativity was more important during the acceleration phase of downward movements and during the deceleration phase of upward movements, resulting in diminished phasic activity compared to horizontal movements. Concomitantly, we found direction-specific effects of movement speed on phasic EMG activity of gravity muscles. This resulted in altered EMG to kinematics relationships in vertical movements compared to horizontal ones. These results support the Effort-minimization hypothesis and confirm that the negativity of phasic EMG is an important aspect of the motor command. Furthermore, the present results reveal that the CNS finely tunes this feature across a range of movement speeds and directions.

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bioRxiv2022

Too Much Information Is No Information: How Machine Learning and Feature Selection Could Help in Understanding the Motor Control of Pointing

The aim of this study was to develop the use of Machine Learning techniques as a means of multivariate analysis in studies of motor control. These studies generate a huge amount of data, the analysis of which continues to be largely univariate. We propose the use of machine learning classification and feature selection as a means of uncovering feature combinations that are altered between conditions. High dimensional electromyograms (EMG) vectors were generated as several arm and trunk muscles were recorded while subjects pointed at various angles above and below the gravity neutral horizontal plane. We used Linear Discriminant Analysis (LDA) to carry out binary classifications between the EMG vectors for pointing at a particular angle, versus pointing at the gravity neutral direction. Classification success provided a composite index of muscular adjustments for various task constraints - in this case, pointing angles. In order to find the combination of features that were significantly altered between task conditions, we conducted a post classification feature selection i.e. investigated which combination of features had allowed for the classification. Feature selection was done by comparing the representations of each category created by LDA for the classification. In other words computing the difference between the representations of each class. We propose that this approach will help with comparing high dimensional EMG patterns in two ways; i) quantifying the effects of the entire pattern rather than using single arbitrarily defined variables and ii) identifying the parts of the patterns that convey the most information regarding the investigated effects.

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bioRxiv2022

Time-of-day effects on motor learning

While the time-of-day significantly impacts motor performance, its effect on motor learning has not yet been elucidated. Here, we investigated the influence of the time-of-day on skill acquisition (i.e., skill improvement immediately after a training-session) and consolidation (i.e., skill retention after a time interval). Three groups were trained at 10 a.m. (G10am), 3 p.m. (G3pm), or 8 p.m. (G8pm) on a finger-tapping task. We recorded the skill (i.e. the ratio between movement duration and accuracy), before and immediately after the training to evaluate skill acquisition, and after 24 hours, to measure skill consolidation. We did not observe any difference in acquisition according to the time of the day. However, we found an improvement in performance 24 hours after the evening training (G8pm) while the morning (G10am) and the afternoon (G3pm) groups deteriorated and stabilized their performance, respectively. Furthermore, two control experiments (G8wake and G8sleep) supported the idea that a night of sleep contributes to the skill consolidation of the evening group. These results show an influence of time-of-day on the consolidation process, with better consolidation when the training is carried out in the evening. This finding may have an important impact on the planning of training programs in sports, clinical, or experimental domains.

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bioRxiv2021

Gravity effects are better optimized by older than young adults when reaching with the non-dominant arm

Motor lateralization refers to differences in the neural organization of cerebral hemispheres, resulting in different control specializations between the dominant and the non-dominant motor systems. Multiple studies proposed that the dominant hemisphere is specialized for open-loop optimization-like processes. Recently, comparing arm kinematics between upward and downward movements, we found that the dominant arm outperformed the non-dominant one regarding gravity-related motor optimization in healthy young participants. The literature about aging effects on motor control presents several neurophysiological and behavioral evidences for an age-related reduction of motor lateralization. Here, we compare the lateralization of a well-known gravity-related optimal motor control process between young and older adults. Forty-one healthy young (mean age = 24.3 {+/-} 3 years) and forty-two healthy older adults (mean age = 72.0 {+/-} 6 years) performed single degree-of-freedom vertical arm movements between two targets (upward and downward). Participants alternatively reached with their dominant and non-dominant arms. We recorded arm kinematics and electromyographic activities of the prime movers (Anterior and Posterior Deltoids) and we analyzed parameters thought to represent the hallmark of the gravity-related optimization process (i.e directional asymmetries and negative epochs on the phasic EMG activity). We found strong age x arm interaction effects on all parameters; i.e., relative durations to peak acceleration and peak velocity and the negativity of antigravity muscles phasic signals. Although all three parameters showed a lateralization effect where the dominant arm was superior to the non-dominant arm in young adults (as in Poirier et al. 2022), we found no such effect in older adults. With both arms, the results of older adults lied between those of the dominant and non-dominant arm of young adults. These results add to those of recent literature showing that feedforward motor control remains functional in older adults. More, the results obtained with the non-dominant arm may support a previously hypothesized increased reliance on predictive mechanisms in older adults.

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bioRxiv2021

Smoothness discriminates physical from motor imagery practice of arm-reaching movements.

Physical practice (PP) and motor imagery practice (MP) lead to the execution of fast and accurate arm movements. However, there is currently no information about the influence of MP on movement smoothness, nor about which performance parameters best discriminate these practices. In the current study, we assessed motor performances with an arm pointing task with constrained precision before and after PP (n= 15), MP (n= 15), or no practice (n= 15). We analyzed gains between Pre- and Post-Test for five performance parameters: movement duration, mean and maximal velocities, total displacements, and the number of velocity peaks characterizing movement smoothness. The results showed an improvement of performance after PP and MP for all parameters, except for total displacements. The gains for movement duration, and mean and maximal velocities were statistically higher after PP and MP than after no practice, and comparable between practices. However, motor gains for the number of velocity peaks were higher after PP than MP, suggesting that movements were smoother after PP than after MP. A discriminant analysis also identified the number of velocity peaks as the most relevant parameter that differentiated PP from MP. The current results provide evidence that PP and MP specifically modulate movement smoothness during arm reaching tasks. This difference may rely on online corrections through sensory feedback integration, available during PP but not during MP.

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bioRxiv2021

Muscle effort is best minimized by the right-dominant arm in the gravity field

The central nervous system (CNS) is thought to develop motor strategies that minimize various hidden criteria, such as end-point variance or effort. A large body of literature suggests that the dominant arm is specialized for such open-loop optimization-like processes whilst the non-dominant arm is specialized for closed-loop control. Building on recent results suggesting that the brain plans arm movements that takes advantage of gravity effects to minimize muscle effort, the present study tests the hypothesized superiority of the dominant arm motor system for effort minimization. Thirty participants (22.5 {+/-} 2.1 years old; all right-handed) performed vertical arm movements between two targets (40{degrees} amplitude), in two directions (upwards and downwards) with their two arms (dominant and non-dominant). We recorded the arm kinematics and the electromyographic activity of the anterior and posterior deltoid to compare two motor signatures of the gravity-related optimization process; i.e., directional asymmetries and negative epochs on phasic muscular activity. We found that these motor signatures were still present during movements performed with the non-dominant arm, indicating that the effort-minimization process also occurs for the non-dominant motor system. However, these markers were reduced compared with movements performed with the dominant arm. This difference was especially prominent during downward movements, where the optimization of gravity effects occurs early in the movement. Assuming that the dominant arm is optimal to minimize muscle effort, as suggested by previous studies, the present results support the hypothesized superiority of the dominant arm motor system for effort-minimization.

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bioRxiv2021

Contraction-dependent intracortical inhibition supports gravity-efficient motor control

Efficient control of voluntary movements along the gravity axis requires adapted shifts in muscular contraction modes. In daily life, rising the arm up involves shortening (i.e., concentric) contractions of arm flexors, while the reverse movement can rely on lengthening (i.e., eccentric) contractions of the same muscles with the help of gravity force. Although this muscular-control mode is universal, the neuromuscular mechanisms that subserve the control of such gravity-oriented movements remain unknown. In this study, we designed two neurophysiological experiments that allowed tracking modulations of cortical, spinal, and muscular outputs of arm flexors while healthy humans carried out vertical pointing movements. In conditions where upward and downward movements revealed kinematic features reminiscent of optimal motor commands (i.e., directional asymmetries), we report fine contraction-dependent modulations of the corticospinal output. The overall corticospinal excitability dropped during lengthening contractions (downward movements) compared with shortening contractions (upward movements). Specifically, we did not observe any change in spinal motoneuron responsiveness from cervicomedullary stimulations but a specific increase in intracortical inhibition during lengthening vs. shortening contractions. We discuss these fine 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 optimize movement control along the gravity axis.

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bioRxiv2019

Motor planning of vertical arm movements in healthy older adults: does effort optimization persist with aging?

Several sensorimotor modifications are known to occur with aging, possibly leading to adverse outcomes such as falls. Recently, some of those modifications have been proposed to emerge from motor planning deteriorations. Motor planning of vertical movements is thought to engage an internal model of gravity to anticipate its mechanical effects on the body-limbs and thus to genuinely produce movements that minimize muscle effort. This is supported, amongst other results, by direction-dependent kinematics where relative durations to peak accelerations and peak velocity are shorter for upward than for downward movements. The present study compares motor planning of fast and slow vertical arm reaching movements between eighteen young (24 {+/-} 3 years old) and seventeen older adults (70 {+/-} 5 years old). We found that older participants still exhibit directional asymmetries (i.e., differences between upward and downward movements), indicating that optimization processes during motor planning persist with healthy aging. However, the size of these differences was increased in older participants, indicating that gravity-related motor planning changes with age. We discuss this increase as the possible result of an overestimation of gravity torque or increased weight of the effort cost in the optimization process. Overall, these results support the hypothesis that feedforward processes and, more precisely, optimal motor planning, remain active with healthy aging.

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bioRxiv2019

A cross-species neural integration of gravity for motor optimisation

Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain uses an internal model of gravity to shape motor patterns that minimise muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here we analyse muscular activation patterns during single-degree-of-freedom arm movements in various directions, which allow to specifically investigating gravity-related movement properties. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic EMGs present systematic negative phases. This negativity demonstrates that gravity effects are harvested to save muscle effort and reveals that the brain implements an optimal motor plan using gravity to accelerate downward and decelerate upward movements. Furthermore, for the first time, we compare experimental findings in humans to monkeys, thereby generalising the Effort-optimization strategy across species.

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bioRxiv2019

Motor learning without doing: use-dependent plasticity induced by motor imagery

Motor imagery, defined as the mental representation of an action without movement-related sensory inputs, is a well-known intervention to improve motor performance. In the current study, we tested whether use-dependent plasticity, a mechanism underlying motor learning, could be induced by an acute session of motor imagery. By means of transcranial magnetic stimulation (TMS) over the left primary motor cortex, we evoked isolated thumb movements in the right hand and assessed corticospinal excitability in the flexor and extensor pollicis brevis muscles. We measured the mean TMS-induced movement direction before and after an acute session of motor imagery practice. In a first experiment, participants of the imagery group were instructed to repeatedly imagine their thumb moving in a direction deviated by 90{degrees} from the pre-test movement. This group, but not the control group, deviated the post-training TMS-induced movements toward the training target direction (+44{degrees} {+/-}62{degrees} and -1{degrees} {+/-}23{degrees}, respectively). Interestingly, the deviation magnitude was driven by the corticospinal excitability increase in the agonist muscle. In a second experiment, we found that post-training TMS-induced movements were proportionally deviated toward the trained direction and returned to baseline 30 minutes after the motor imagery training. These findings suggest that motor imagery induces use-dependent plasticity and, this neural process is accompanied by corticospinal excitability increase in the agonist muscle.

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