Motor learning and its sensory effects: time course of perceptual change and its presence with gradual introduction of load

A complex interplay has been demonstrated between motor and sensory systems. We showed recently that motor learning leads to changes in the sensed position of the limb (Ostry DJ, Darainy M, Mattar AA, Wong J, Gribble PL. J Neurosci 30: 5384–5393, 2010). Here, we document further the links between motor learning and changes in somatosensory perception. To study motor learning, we used a force field paradigm in which subjects learn to compensate for forces applied to the hand by a robotic device. We used a task in which subjects judge lateral displacements of the hand to study somatosensory perception. In a first experiment, we divided the motor learning task into incremental phases and tracked sensory perception throughout. We found that changes in perception occurred at a slower rate than changes in motor performance. A second experiment tested whether awareness of the motor learning process is necessary for perceptual change. In this experiment, subjects were exposed to a force field that grew gradually in strength. We found that the shift in sensory perception occurred even when awareness of motor learning was reduced. These experiments argue for a link between motor learning and changes in somatosensory perception, and they are consistent with the idea that motor learning drives sensory change.

Download Full-text

Neuronal Correlates of Motor Performance and Motor Learning in the Primary Motor Cortex of Monkeys Adapting to an External Force Field

Neuron ◽

10.1016/s0896-6273(01)00301-4 ◽

2001 ◽

Vol 30 (2) ◽

pp. 593-607 ◽

Cited By ~ 269

Author(s):

Chiang-Shan Ray Li ◽

Camillo Padoa-Schioppa ◽

Emilio Bizzi

Keyword(s):

Motor Cortex ◽

Motor Learning ◽

Force Field ◽

External Force ◽

Motor Performance ◽

Primary Motor Cortex ◽

External Force Field

Download Full-text

Somatosensory Perceptual Training Enhances Motor Learning by Observing

10.1101/319905 ◽

2018 ◽

Author(s):

Heather R. McGregor ◽

Joshua G.A. Cashaback ◽

Paul L. Gribble

Keyword(s):

Motor Learning ◽

Force Field ◽

Motor Performance ◽

Action Observation ◽

Somatosensory System ◽

Functional Plasticity ◽

Perceptual Training ◽

Learning Group ◽

Neurophysiological Studies ◽

Somatosensory Function

AbstractNeuroimaging and neurophysiological studies in humans have demonstrated that action observation activates brain regions involved in sensory-motor control. A growing body of work has shown that action observation can also facilitate motor learning; observing a tutor undergoing motor learning results in functional plasticity within the motor system and gains in subsequent motor performance. However, the effects of observing motor learning extend beyond the motor domain. Converging evidence suggests that learning also results in somatosensory functional plasticity and somatosensory perceptual changes. This work has raised the possibility that the somatosensory system is also involved in motor learning that results from observation. Here we tested this hypothesis using a somatosensory perceptual training paradigm. If the somatosensory system is indeed involved in motor learning by observing, then improving subjects' somatosensory function before observation should enhance subsequent observation-related gains in motor performance. Subjects performed a proprioceptive discrimination task in which a robotic manipulandum moved the subject’s passive upper limb and he or she made judgments about the position of the hand. Subjects in a Trained Learning group received trial-by-trial feedback to improve their proprioceptive acuity. Subjects in an Untrained Learning group performed the same task without feedback. All subjects then observed a learning video showing a tutor adapting her reaches to a left force field (FF). We found that subjects in the Trained Learning group, who had superior proprioceptive acuity prior to observation, benefited more from observing learning compared to subjects in the Untrained Learning group. Improving somatosensory function can therefore enhance subsequent observation-related gains in motor learning. This study provides further evidence in favor of the involvement of the somatosensory system in motor learning by observing.AbbreviationsFF:Force fieldPD:Maximum perpendicular deviationIQR:interquartile rangeThe authors report no financial interests or conflicts of interests.

Download Full-text

The 24-h savings of adaptation to novel movement dynamics initially reflects the recall of previous performance

Journal of Neurophysiology ◽

10.1152/jn.00569.2018 ◽

2019 ◽

Vol 122 (3) ◽

pp. 933-946 ◽

Cited By ~ 2

Author(s):

Katrina P. Nguyen ◽

Weiwei Zhou ◽

Erin McKenna ◽

Katrina Colucci-Chang ◽

Laurence C. Jayet Bray ◽

...

Keyword(s):

Force Field ◽

Motor Performance ◽

Time Course ◽

Reaching Movements ◽

Initial Training ◽

Single Trial ◽

Open Questions ◽

Movement Dynamics ◽

Force Profile ◽

Force Field Adaptation

Humans rapidly adapt reaching movements in response to perturbations (e.g., manipulations of movement dynamics or visual feedback). Following a break, when reexposed to the same perturbation, subjects demonstrate savings, a faster learning rate compared with the time course of initial training. Although this has been well studied, there are open questions on the extent early savings reflects the rapid recall of previous performance. To address this question, we examined how the properties of initial training (duration and final adaptive state) influence initial single-trial adaptation to force-field perturbations when training sessions were separated by 24 h. There were two main groups that were distinct based on the presence or absence of a washout period at the end of day 1 (with washout vs. without washout). We also varied the training duration on day 1 (15, 30, 90, or 160 training trials), resulting in 8 subgroups of subjects. We show that single-trial adaptation on day 2 scaled with training duration, even for similar asymptotic levels of learning on day 1 of training. Interestingly, the temporal force profile following the first perturbation on day 2 matched that at the end of day 1 for the longest training duration group that did not complete the washout. This correspondence persisted but was significantly lower for shorter training durations and the washout subject groups. Collectively, the results suggest that the adaptation observed very early in reexposure results from the rapid recall of the previously learned motor recalibration but is highly dependent on the initial training duration and final adaptive state. NEW & NOTEWORTHY The extent initial readaptation reflects the recall of previous motor performance is largely unknown. We examined early single-trial force-field adaptation on the second day of training and distinguished initial retention from recall. We found that the single-trial adaptation following the 24-h break matched that at the end of the first day, but this recall was modified by the training duration and final level of learning on the first day of training.

Download Full-text

Faculty Opinions recommendation of Time course of choice reaction time deficits in the Hdh(Q92) knock-in mouse model of Huntington's disease in the operant serial implicit learning task (SILT).

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1108415.564465 ◽

2008 ◽

Author(s):

Allan Tobin

Keyword(s):

Reaction Time ◽

Mouse Model ◽

Huntington's Disease ◽

Huntington’S Disease ◽

Implicit Learning ◽

Choice Reaction Time ◽

Time Course ◽

Learning Task

Download Full-text

Implicit motor learning within three trials

Scientific Reports ◽

10.1038/s41598-021-81031-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jennifer E. Ruttle ◽

Bernard Marius ’t Hart ◽

Denise Y. P. Henriques

Keyword(s):

Motor Learning ◽

Implicit Learning ◽

Time Course ◽

Skills Training ◽

Implicit Processes ◽

Training Performance ◽

Slow Development ◽

Implicit Motor Learning ◽

Implicit Motor ◽

And Shifts

AbstractIn motor learning, the slow development of implicit learning is traditionally taken for granted. While much is known about training performance during adaptation to a perturbation in reaches, saccades and locomotion, little is known about the time course of the underlying implicit processes during normal motor adaptation. Implicit learning is characterized by both changes in internal models and state estimates of limb position. Here, we measure both as reach aftereffects and shifts in hand localization in our participants, after every training trial. The observed implicit changes were near asymptote after only one to three perturbed training trials and were not predicted by a two-rate model’s slow process that is supposed to capture implicit learning. Hence, we show that implicit learning is much faster than conventionally believed, which has implications for rehabilitation and skills training.

Download Full-text

Motor learning in reaching tasks leads to homogenization of task space error distribution

10.1101/2021.09.01.458189 ◽

2021 ◽

Author(s):

Puneet Singh ◽

Oishee Ghosal ◽

Aditya Murthy ◽

Ashitava Ghodal

Keyword(s):

Motor Learning ◽

Force Field ◽

Error Distribution ◽

Task Space ◽

Field Perturbation ◽

Directional Dependence ◽

Reaching Tasks ◽

Space Error ◽

Human Arm ◽

Point To Point

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

Download Full-text