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.

Closing the Loop: From Motor Neuroscience to Neurorehabilitation

2018 ◽  
Vol 41 (1) ◽  
pp. 415-429 ◽  
Author(s):  
Ryan T. Roemmich ◽  
Amy J. Bastian
Keyword(s):  
Motor Learning ◽  
Neural Control ◽  
Behavioral Studies ◽  
Closing The Loop ◽  
Motor Learning And Control ◽  
Human Motor ◽  
Basic Studies ◽  
The Right ◽  
And Control ◽  
Neural Control Of Movement

The fields of human motor control, motor learning, and neurorehabilitation have long been linked by the intuition that understanding how we move (and learn to move) leads to better rehabilitation. In reality, these fields have remained largely separate. Our knowledge of the neural control of movement has expanded, but principles that can directly impact rehabilitation efficacy remain somewhat sparse. This raises two important questions: What can basic studies of motor learning really tell us about rehabilitation, and are we asking the right questions to improve the lives of patients? This review aims to contextualize recent advances in computational and behavioral studies of human motor learning within the framework of neurorehabilitation. We also discuss our views of the current challenges facing rehabilitation and outline potential clinical applications from recent theoretical and basic studies of motor learning and control.

scholarly journals Successful auditory motor adaptation requires task-relevant auditory errors

2019 ◽  
Vol 122 (2) ◽  
pp. 552-562 ◽  
Author(s):  
Ayoub Daliri ◽  
Jonathan Dittman
Keyword(s):  
Motor Learning ◽  
Categorical Perception ◽  
Production Systems ◽  
State Space Model ◽  
Motor Adaptation ◽  
Auditory Information ◽  
Speech Motor Learning ◽  
Task Irrelevant ◽  
The Brain ◽  
Speech Motor

When we produce speech movements, we also predict the auditory consequences of the movements. We use discrepancies between our predictions and incoming auditory information to modify our future movements (adapt). Although auditory errors are crucial for speech motor learning, not all perceived auditory errors are consequences of our own actions. Therefore, the brain needs to evaluate the relevance of perceived auditory errors. In this study, we examined error assessment processes involved in auditory motor adaptation by systematically manipulating the correspondence between speech motor outputs and their auditory consequences during speaking. Participants ( n = 30) produced speech while they received perturbed auditory feedback (e.g., produced “head” but heard a word that sounded like “had”). In one condition, auditory errors were related to participants’ productions (task-relevant errors). In another condition, auditory errors were defined by the experimenter and had no correspondence with participants’ speech output (task-irrelevant errors). We found that the extent of adaptation and error sensitivity (derived from a state-space model) were greater in the condition with task-relevant auditory errors compared with those in the condition with task-irrelevant auditory errors. Additionally, participants with smaller perceptual targets (derived from a categorical perception task) adapted more to auditory perturbations, and participants with larger perceptual targets adapted less. Similarly, participants with smaller perceptual targets were more sensitive to errors in the condition with task-relevant auditory errors. Together, our results highlight the intricate mechanisms, involving both perception and production systems, that the brain uses to optimally integrate auditory errors for successful speech motor learning. NEW & NOTEWORTHY Feedback monitoring is essential for accurate speech production. By providing empirical results and a computational framework, we show that 1) the brain evaluates relevance of auditory errors and responds more to relevant errors, and 2) smaller perceptual targets are associated with more sensitivity to errors and more auditory motor adaptation.

scholarly journals On the encoding capacity of human motor adaptation

2021 ◽  
Author(s):  
Seung-Yeon Kim ◽  
Jae-Woon Kwon ◽  
Jin-Min Kim ◽  
Frank Chong-Woo Park ◽  
Sang-Hoon Yeo
Keyword(s):  
Motor Learning ◽  
Force Field ◽  
Information Content ◽  
Motor Adaptation ◽  
Movement Speed ◽  
Limiting Factor ◽  
Information Encoding ◽  
Motor Primitives ◽  
Human Motor ◽  
Human Motor Adaptation

Primitive-based models of motor learning suggest that adaptation occurs by tuning the responses of motor primitives. Based on this idea, we consider motor learning as an information encoding procedure, that is, a procedure of encoding a motor skill into primitives. The capacity of encoding is determined by the number of recruited primitives, which depends on how many primitives are "visited" by the movement, and this leads to a rather counter-intuitive prediction that faster movement, where a larger number of motor primitives are involved, allows learning more complicated motor skills. Here we provide a set of experimental results that support this hypothesis. First, we show that learning occurs only with movement, i.e., only with non-zero encoding capacity. When participants were asked to counteract a rotating force applied to a robotic handle, they were unable to do so when maintaining a static posture but were able to adapt when making small circular movements. Our second experiment further investigated how adaptation is affected by movement speed. When adapting to a simple (low-information-content) force field, fast (high-capacity) movement did not have an advantage over slow (low-capacity) movement. However, for a complex (high-information-content) force field, the fast movement showed a significant advantage over slow movement. Our final experiment confirmed that the observed benefit of high-speed movement is only weakly affected by mechanical factors. Taken together, our results suggest that the encoding capacity is a genuine limiting factor of human motor adaptation.

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 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 Feedback adaptation to unpredictable force fields in 250ms

2019 ◽  
Author(s):  
Frédéric Crevecoeur ◽  
James Mathew ◽  
Marie Bastin ◽  
Philippe Lefevre
Keyword(s):  
Nervous System ◽  
Motor Learning ◽  
Force Field ◽  
Recent Work ◽  
Muscle Activity ◽  
Force Fields ◽  
Control Strategies ◽  
Motor Adaptation ◽  
Classical Studies ◽  
Learning And Adaptation

AbstractMotor learning and adaptation are important functions of the nervous system. Classical studies have characterized how humans adapt to changes in the environment during tasks such as reaching, and have documented improvements in behavior across movements. Yet little is known about how quickly the nervous system adapts to such disturbances. In particular, recent work has suggested that adaptation could be sufficiently fast to alter the control strategies of an ongoing movement. To further address the possibility that learning occurred within a single movement, we designed a series of human reaching experiments to extract in muscles recordings the latency of feedback adaptation. Our results confirmed that participants adapted their feedback responses to unanticipated force fields applied randomly. In addition, our analyses revealed that the feedback response was specifically and finely tuned to the ongoing perturbation not only across trials with the same force field, but also across different kinds of force fields. Finally, changes in muscle activity consistent with feedback adaptation occurred in about 250ms following reach onset. We submit this estimate as the latency of motor adaptation in the nervous system.

Sign in / Sign up

Export Citation Format

Share Document