scholarly journals Variable training but not sleep improves consolidation of motor adaptation

2018 ◽  
Author(s):  
Benjamin Thürer ◽  
Frederik D. Weber ◽  
Jan Born ◽  
Thorsten Stein
Keyword(s):  
Force Field ◽  
Motor Adaptation ◽  
Motor Memory ◽  
Alpha Power ◽  
Dominant Hand ◽  
Motor Tasks ◽  
Task Execution ◽  
Force Field Adaptation ◽  
Dependent Tasks ◽  
Adaptation Task

How motor memory consolidates still remains elusive. Motor tasks’ consolidation were shown to depend on periods of sleep, whereas pure non-hippocampal dependent tasks, like motor adaptation, might not. Some research suggests that the mode of training might affect the sleep dependency of motor adaptation tasks. Here we investigated whether sleep differentially impacts memory consolidation dependent on the variability during training. Healthy men were trained with their dominant, right hand on a force field adaptation task and re-tested after an 11-h consolidation period either involving overnight sleep (Sleep) or daytime wakefulness (Wake). Retesting also included a transfer to the non-dominant hand. Half of the subjects in each group adapted to different force field magnitudes with low inter-trial variability (Sleep-Blocked; Wake-Blocked), the other half with high variability (Sleep-Random; Wake-Random). EEG was recorded during task execution and overnight polysomnography. Motor adaptation was comparable between Wake and Sleep groups, although performance changes over sleep correlated with sleep spindles nesting in slow wave upstates. Higher training variability improved retest, including transfer learning, and these improvements correlated with higher alpha power in contralateral parietal areas. Enhanced consolidation after training might foster the ability to correct ongoing movements by responsive feedback rather than their pre-execution prediction.

scholarly journals Exploration of joint redundancy but not task space variability facilitates supervised motor learning

2016 ◽  
Vol 113 (50) ◽  
pp. 14414-14419 ◽  
Author(s):  
Puneet Singh ◽  
Sumitash Jana ◽  
Ashitava Ghosal ◽  
Aditya Murthy
Keyword(s):  
Motor Learning ◽  
Force Field ◽  
Visuomotor Adaptation ◽  
Dominant Hand ◽  
Task Space ◽  
Motor Variability ◽  
3D Space ◽  
Human Arm ◽  
Force Field Adaptation ◽  
Redundant Component

The number of joints and muscles in a human arm is more than what is required for reaching to a desired point in 3D space. Although previous studies have emphasized how such redundancy and the associated flexibility may play an important role in path planning, control of noise, and optimization of motion, whether and how redundancy might promote motor learning has not been investigated. In this work, we quantify redundancy space and investigate its significance and effect on motor learning. We propose that a larger redundancy space leads to faster learning across subjects. We observed this pattern in subjects learning novel kinematics (visuomotor adaptation) and dynamics (force-field adaptation). Interestingly, we also observed differences in the redundancy space between the dominant hand and nondominant hand that explained differences in the learning of dynamics. Taken together, these results provide support for the hypothesis that redundancy aids in motor learning and that the redundant component of motor variability is not noise.

scholarly journals No effects of cerebellar transcranial direct current stimulation on force field and visuomotor reach adaptation in young and healthy subjects

2019 ◽  
Vol 121 (6) ◽  
pp. 2112-2125 ◽  
Author(s):  
A. Mamlins ◽  
T. Hulst ◽  
O. Donchin ◽  
D. Timmann ◽  
J. Claassen
Keyword(s):  
Motor Learning ◽  
Force Field ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Healthy Subjects ◽  
Motor Adaptation ◽  
Visuomotor Rotation ◽  
Direct Current Stimulation ◽  
Cerebellar Tdcs ◽  
Adaptation Task

Previous studies have shown that cerebellar transcranial direct current stimulation (tDCS) leads to faster adaptation of arm reaching movements to visuomotor rotation and force field perturbations in healthy subjects. The first aim of the present study was to confirm a stimulation-dependent effect on motor adaptation. Second, we investigated whether tDCS effects differ depending on onset, that is, before or at the beginning of the adaptation phase. A total of 120 healthy and right-handed subjects (60 women, mean age 23.2 ± SD 2.7 yr, range 18–31 yr) were tested. Subjects moved a cursor with a manipulandum to one of eight targets presented on a vertically orientated screen. Three baseline blocks were followed by one adaptation block and three washout blocks. Sixty subjects did a force field adaptation task (FF), and 60 subjects did a visuomotor adaptation task (VM). Equal numbers of subjects received anodal, cathodal, or sham cerebellar tDCS beginning either in the third baseline block or at the start of the adaptation block. In FF and VM, tDCS and the onset of tDCS did not show a significant effect on motor adaptation (all P values >0.05). We were unable to support previous findings of modulatory cerebellar tDCS effects in reaching adaptation tasks in healthy subjects. Prior to possible application in patients with cerebellar disease, future experiments are needed to determine which tDCS and task parameters lead to robust tDCS effects. NEW & NOTEWORTHY Transcranial direct current stimulation (tDCS) is a promising tool to improve motor learning. We investigated whether cerebellar tDCS improves motor learning in force field and visuomotor tasks in healthy subjects and what influence the onset of stimulation has. We did not find stimulation effects of tDCS or an effect of onset of stimulation. A reevaluation of cerebellar tDCS in healthy subjects and at the end of the clinical potential in cerebellar patients is demanded.

scholarly journals The influence of catch trials on the consolidation of motor memory in force field adaptation tasks

2013 ◽  
Vol 4 ◽  
Author(s):  
Anne Focke ◽  
Christian Stockinger ◽  
Christina Diepold ◽  
Marco Taubert ◽  
Thorsten Stein
Keyword(s):  
Force Field ◽  
Motor Memory ◽  
Force Field Adaptation

scholarly journals Dissociating effects of error size, training duration, and amount of adaptation on the ability to retain motor memories

2019 ◽  
Vol 122 (5) ◽  
pp. 2027-2042 ◽  
Author(s):  
Laith Alhussein ◽  
Eghbal A. Hosseini ◽  
Katrina P. Nguyen ◽  
Maurice A. Smith ◽  
Wilsaan M. Joiner
Keyword(s):  
Force Field ◽  
Motor Memory ◽  
Exposure Rate ◽  
Performance Improvements ◽  
Training Schedule ◽  
Long Duration ◽  
Initial Learning ◽  
Effective Training ◽  
Different Types ◽  
Force Field Adaptation

Extensive computational and neurobiological work has focused on how the training schedule, i.e., the duration and rate at which an environmental disturbance is presented, shapes the formation of motor memories. If long-lasting benefits are to be derived from motor training, however, retention of the performance improvements gained during practice is essential. Thus a better understanding of mechanisms that promote retention could lead to the design of more effective training procedures. The few studies that have investigated how retention depends on the training schedule have suggested that the gradual exposure of a perturbation leads to improved retention of motor memory compared with an abrupt exposure. However, several of these previous studies showed small effects, and although some controlled the training duration and others the level of learning, none have controlled both. In the present study we disambiguated both of these effects from exposure rate by systematically varying the duration of training, type of trained dynamics, and exposure rate for these dynamics in human force-field adaptation. After controlling for both training duration and the amount of learning, we found essentially identical retention when comparing gradual and abrupt training for two different types of force-field dynamics. By contrast, we found that retention was markedly higher for long-duration compared with short-duration training for both types of dynamics. These results demonstrate that the duration of training has a far greater effect on the retention of motor memory than the exposure rate during training. We show that a multirate learning model provides a computational mechanism for these findings. NEW & NOTEWORTHY Previous studies have suggested that a gradual, incremental introduction of a novel environment is helpful for improving retention. However, we used experimental and computational approaches to demonstrate that previously reported improvements in retention associated with gradual introductions fail to persist when other factors, including the duration of training and the degree of initial learning, are accounted for.

scholarly journals Assessing explicit strategies in force field adaptation

2020 ◽  
Vol 123 (4) ◽  
pp. 1552-1565 ◽  
Author(s):  
Raphael Schween ◽  
Samuel D. McDougle ◽  
Mathias Hegele ◽  
Jordan A. Taylor
Keyword(s):  
Force Field ◽  
Force Production ◽  
Visuomotor Adaptation ◽  
Explicit Learning ◽  
Force Field Adaptation ◽  
Novel Methods ◽  
Adaptation Task

While the contribution of explicit learning has been increasingly studied in visuomotor adaptation, its contribution to force field adaptation has not been studied extensively. We employed two novel methods to assay explicit learning in a force field adaptation task and found that learners can voluntarily control aspects of compensatory force production and manually report it with their untrained limb. This supports the general viability of the contribution of explicit learning also in force field adaptation.

scholarly journals Identifying the neural representation of fast and slow states in force field adaptation via fMRI

2019 ◽  
Author(s):  
Andria J. Farrens ◽  
Fabrizio Sergi
Keyword(s):  
Motor Learning ◽  
Force Field ◽  
Motor Adaptation ◽  
Neural Representation ◽  
Control Processes ◽  
Behavioral Studies ◽  
Motor Learning And Control ◽  
Force Field Adaptation ◽  
The Brain ◽  
Slow Learning

AbstractNeurorehabilitation is centered on motor learning and control processes, however our understanding of how the brain learns to control movements is still limited. Motor adaptation is a rapid form of motor learning that is amenable to study in the laboratory setting. Behavioral studies of motor adaptation have coupled clever task design with computational modeling to study the control processes that underlie motor adaptation. These studies provide evidence of fast and slow learning states in the brain that combine to control neuromotor adaptation.Currently, the neural representation of these states remains unclear, especially for adaptation to changes in task dynamics, commonly studied using force fields imposed by a robotic device. Our group has developed the MR-Softwrist, a robot capable of executing dynamic adaptation tasks during functional magnetic resonance imaging (fMRI) that can be used to localize these networks in the brain.We simulated an fMRI experiment to determine if signal arising from a switching force field adaptation task can localize the neural representations of fast and slow learning states in the brain. Our results show that our task produces reliable behavioral estimates of fast and slow learning states, and distinctly measurable fMRI activations associated with each state under realistic levels of behavioral and measurement noise. Execution of this protocol with the MR-Softwrist will extend our knowledge of how the brain learns to control movement.

scholarly journals Increase in weighting of vision vs. proprioception associated with force field adaptation

2019 ◽  
Author(s):  
Brandon M. Sexton ◽  
Yang Liu ◽  
Hannah J. Block
Keyword(s):  
Force Field ◽  
Position Sense ◽  
Multisensory Perception ◽  
Hand Position ◽  
Null Field ◽  
Before And After ◽  
Force Field Adaptation ◽  
Perceptual Changes ◽  
The Brain ◽  
Straight Ahead

AbstractHand position can be encoded by vision, via an image on the retina, and proprioception (position sense), via sensors in the joints and muscles. The brain is thought to weight and combine available sensory estimates to form an integrated multisensory estimate of hand position with which to guide movement. Force field adaptation, a form of cerebellum-dependent motor learning in which reaches are systematically adjusted to compensate for a somatosensory perturbation, is associated with both motor and proprioceptive changes. The cerebellum has connections with parietal regions thought to be involved in multisensory integration; however, it is unknown if force adaptation is associated with changes in multisensory perception. One possibility is that force adaptation affects all relevant sensory modalities similarly, such that the brain’s weighting of vision vs. proprioception is maintained. Alternatively, the somatosensory perturbation might be interpreted as proprioceptive unreliability, resulting in vision being up-weighted relative to proprioception. We assessed visuo-proprioceptive weighting with a perceptual estimation task before and after subjects performed straight-ahead reaches grasping a robotic manipulandum. Each subject performed one session with a clockwise or counter-clockwise velocity-dependent force field, and one session in a null field to control for perceptual changes not specific to force adaptation. Subjects increased their weight of vision vs. proprioception in the force field session relative to the null field session, regardless of force field direction, in the straight-ahead dimension (F1,44 = 5.13, p = 0.029). This suggests that force field adaptation is associated with an increase in the brain’s weighting of vision vs. proprioception.

scholarly journals The effect of sequence learning on sensorimotor adaptation

2020 ◽  
Author(s):  
Yang Liu ◽  
Hannah J. Block
Keyword(s):  
Force Field ◽  
Sequence Learning ◽  
Target Position ◽  
Random Order ◽  
Neural Substrates ◽  
Skill Learning ◽  
Sensorimotor Learning ◽  
Sensorimotor Adaptation ◽  
Sequence Information ◽  
Force Field Adaptation

AbstractMotor skill learning involves both sensorimotor adaptation (calibrating the response to task dynamics and kinematics), and sequence learning (executing the task elements in the correct order at the necessary speed). These processes typically occur together in natural behavior and share much in common, such as working memory demands, development, and possibly neural substrates. However, sensorimotor and sequence learning are usually studied in isolation in research settings, for example as force field adaptation or serial reaction time tasks (SRTT), respectively. It is therefore unclear whether having predictive sequence information during sensorimotor adaptation would facilitate performance, perhaps by improving sensorimotor planning, or if it would impair performance, perhaps by occupying neural resources needed for sensorimotor learning. Here we evaluated adaptation to a distance-dependent force field in two different SRTT contexts: In Experiment 1, 28 subjects reached between 4 targets in a sequenced or random order. In Experiment 2, 40 subjects reached to one target, but 3 force field directions were applied in a sequenced or random order. We did not observe any consistent influence of target position sequence on force field adaptation in Experiment 1. However, sequencing of force field directions facilitated sensorimotor adaptation and retention in Experiment 2. This is inconsistent with the idea that sensorimotor and sequence learning share neural resources in any mutually exclusive fashion. These findings indicate that under certain conditions, perhaps especially when the sequence is related to the sensorimotor perturbation itself as in Experiment 2, sequence learning may interact with sensorimotor learning in a facilitatory manner.

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