scholarly journals The mid-lateral cerebellum is necessary for reinforcement learning

2020 ◽  
Author(s):  
Naveen Sendhilnathan ◽  
Michael E. Goldberg
Keyword(s):  
Reinforcement Learning ◽  
Motor Learning ◽  
Hand Movement ◽  
Hand Movements ◽  
Cerebellar Hemisphere ◽  
Error Signal ◽  
Loss Of Function ◽  
Association Learning ◽  
New Associations ◽  
Crus I

SummaryThe cerebellum has long been considered crucial for supervised motor learning and its optimization1-3. However, new evidence has also implicated the cerebellum in reward based learning4-8, executive function9-12, and frontal-like clinical deficits13. We recently showed that the simple spikes of Purkinje cells (P-cells) in the mid-lateral cerebellar hemisphere (Crus I and II) encode a reinforcement error signal when monkeys learn to associate arbitrary symbols with hand movements4. However, it is unclear if the cerebellum is necessary for any process beyond motor learning. To investigate if the mid-lateral cerebellum is actually necessary for learning visuomotor associations, we reversibly inactivated the mid-lateral cerebellum of two primates with muscimol while they learned to associate arbitrary symbols with hand movements. Here we show that cerebellar inactivation impaired the monkey’s ability to learn new associations, although it had no effect on the monkeys’ performance on a task with overtrained symbols. A computational model corroborates our results. Cerebellar inactivation increased the reaction time, but there were no deficits in any motor kinematics such as the hand movement, licking or eye movement. There was no loss of function when we inactivated a more anterior region of the cerebellum that is implicated in motor control. We suggest that the mid-lateral cerebellum, which provides a reinforcement learning error signal4, is necessary for visuomotor association learning. Our results have implications for the involvement of cerebellum in cognitive control, and add critical constraints to brain models of non-motor learning14,15.

scholarly journals Mid-lateral Cerebellar Purkinje Cells Provide a Cognitive Error Signal When Monkeys Learn a New Visuomotor Association

2019 ◽  
Author(s):  
Naveen Sendhilnathan ◽  
Anna E. Ipata ◽  
Michael E. Goldberg
Keyword(s):  
Motor Learning ◽  
Purkinje Cells ◽  
Visual Cues ◽  
Hand Movement ◽  
Red Light ◽  
Population Level ◽  
Learning System ◽  
Error Signal ◽  
Association Learning ◽  
Cerebellar Purkinje Cells

AbstractHow do we learn to establish associations between arbitrary visual cues (like a red light) and movements (like braking the car)? We investigated the neural correlates of visuomotor association learning in the monkey mid-lateral cerebellum. Here we show that, during learning but not when the associations were overlearned, individual Purkinje cells reported the outcome of the monkey’s most recent decision, an error signal, which was independent of changes in hand movement or reaction time. At the population level, Purkinje cells collectively maintained a memory of the most recent decision throughout the entire trial period, updating it after every decision. This error signal decreased as the performance improved. Our results suggest a role of mid-lateral cerebellum in visuomotor associative learning and provide evidence that cerebellum could be a generalized learning system, essential in non-motor learning as well as motor learning.

scholarly journals Subthalamic neuromodulation improves short-term motor learning in Parkinson’s disease

Brain ◽  
2019 ◽  
Vol 142 (8) ◽  
pp. 2198-2206 ◽  
Author(s):  
Ana Luísa de Almeida Marcelino ◽  
Andreas Horn ◽  
Patricia Krause ◽  
Andrea A Kühn ◽  
Wolf-Julian Neumann
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Cortex ◽  
Motor Learning ◽  
Hand Movement ◽  
Cerebellar Hemisphere ◽  
Distributed Network ◽  
Short Term ◽  
Visuomotor Task ◽  
Motor Effects

Abstract The basal ganglia and cerebellum are implicated in both motor learning and Parkinson’s disease. Deep brain stimulation (DBS) is an established treatment for advanced Parkinson’s disease that leads to motor and non-motor effects by modulating specific neural pathways. Recently, a disynaptic projection from the subthalamic nucleus (STN) to cerebellar hemispheres was discovered. To investigate the functional significance of this pathway in motor learning, short-term improvement in motor execution in 20 patients with Parkinson’s disease on and off STN-DBS and 20 age-matched healthy controls was studied in a visuomotor task combined with whole-brain connectomics. Motor learning was impaired in Parkinson’s disease off stimulation but was partially restored through DBS. Connectivity between active DBS contacts and a distributed network of brain regions correlated with improvement in motor learning. Region of interest analysis revealed connectivity from active contact to cerebellar hemisphere ipsilateral to hand movement as the strongest predictor for change in motor learning. Peak predictive voxels in the cerebellum localized to Crus II of lobule VII, which also showed higher STN than motor cortex connectivity, suggestive of a connection surpassing motor cortex. Our findings provide new insight into the circuit nature of Parkinson’s disease and the distributed network effects of DBS in motor learning.

Context-dependent relationship in high-resolution micro-ECoG studies during finger movements

2020 ◽  
Vol 132 (5) ◽  
pp. 1358-1366
Author(s):  
Chao-Hung Kuo ◽  
Timothy M. Blakely ◽  
Jeremiah D. Wander ◽  
Devapratim Sarma ◽  
Jing Wu ◽  
...  
Keyword(s):  
High Resolution ◽  
Sensorimotor Cortex ◽  
Index Finger ◽  
Hand Movement ◽  
Cortical Activation ◽  
Hand Movements ◽  
Finger Movements ◽  
Thumb Movement ◽  
Neurosurgical Patients ◽  
The Relationship

OBJECTIVEThe activation of the sensorimotor cortex as measured by electrocorticographic (ECoG) signals has been correlated with contralateral hand movements in humans, as precisely as the level of individual digits. However, the relationship between individual and multiple synergistic finger movements and the neural signal as detected by ECoG has not been fully explored. The authors used intraoperative high-resolution micro-ECoG (µECoG) on the sensorimotor cortex to link neural signals to finger movements across several context-specific motor tasks.METHODSThree neurosurgical patients with cortical lesions over eloquent regions participated. During awake craniotomy, a sensorimotor cortex area of hand movement was localized by high-frequency responses measured by an 8 × 8 µECoG grid of 3-mm interelectrode spacing. Patients performed a flexion movement of the thumb or index finger, or a pinch movement of both, based on a visual cue. High-gamma (HG; 70–230 Hz) filtered µECoG was used to identify dominant electrodes associated with thumb and index movement. Hand movements were recorded by a dataglove simultaneously with µECoG recording.RESULTSIn all 3 patients, the electrodes controlling thumb and index finger movements were identifiable approximately 3–6-mm apart by the HG-filtered µECoG signal. For HG power of cortical activation measured with µECoG, the thumb and index signals in the pinch movement were similar to those observed during thumb-only and index-only movement, respectively (all p > 0.05). Index finger movements, measured by the dataglove joint angles, were similar in both the index-only and pinch movements (p > 0.05). However, despite similar activation across the conditions, markedly decreased thumb movement was observed in pinch relative to independent thumb-only movement (all p < 0.05).CONCLUSIONSHG-filtered µECoG signals effectively identify dominant regions associated with thumb and index finger movement. For pinch, the µECoG signal comprises a combination of the signals from individual thumb and index movements. However, while the relationship between the index finger joint angle and HG-filtered signal remains consistent between conditions, there is not a fixed relationship for thumb movement. Although the HG-filtered µECoG signal is similar in both thumb-only and pinch conditions, the actual thumb movement is markedly smaller in the pinch condition than in the thumb-only condition. This implies a nonlinear relationship between the cortical signal and the motor output for some, but importantly not all, movement types. This analysis provides insight into the tuning of the motor cortex toward specific types of motor behaviors.

Hand Movements and Nondominant Fluency in Bilinguals

1979 ◽  
Vol 48 (1) ◽  
pp. 207-214 ◽  
Author(s):  
Luis R. Marcos
Keyword(s):  
Cognitive Processes ◽  
Motor Behavior ◽  
Hand Movement ◽  
Movement Behavior ◽  
Hand Movements ◽  
Language Fluency ◽  
Movement Activity

16 subordinate bilingual subjects produced 5-min. monologues in their nondominant languages, i.e., English or Spanish. Hand-movement activity manifested during the videotape monologues was scored and related to measures of fluency in the nondominant language. The hand-movement behavior categorized as Groping Movement was significantly related to all of the nondominant-language fluency measures. These correlations support the assumption that Groping Movement may have a function in the process of verbal encoding. The results are discussed in terms of the possibility of monitoring central cognitive processes through the study of “visible” motor behavior.

scholarly journals Motor Learning Without Moving: Proprioceptive and Predictive Hand Localization After Passive Visuoproprioceptive Discrepancy Training

2018 ◽  
Author(s):  
Ahmed A. Mostafa ◽  
Bernard Marius ’t Hart ◽  
Denise Y.P. Henriques
Keyword(s):  
Motor Learning ◽  
Open Loop ◽  
Movement Planning ◽  
Hand Movements ◽  
Hand Position ◽  
Sources Of Information ◽  
Training Paradigm ◽  
Limb Position ◽  
Link Type ◽  
Active Localization

AbstractAn accurate estimate of limb position is necessary for movement planning, before and after motor learning. Where we localize our unseen hand after a reach depends on felt hand position, or proprioception, but in studies and theories on motor adaptation this is quite often neglected in favour of predicted sensory consequences based on efference copies of motor commands. Both sources of information should contribute, so here we set out to further investigate how much of hand localization depends on proprioception and how much on predicted sensory consequences. We use a training paradigm combining robot controlled hand movements with rotated visual feedback that eliminates the possibility to update predicted sensory consequences (‘exposure training’), but still recalibrates proprioception, as well as a classic training paradigm with self-generated movements in another set of participants. After each kind of training we measure participants’ hand location estimates based on both efference-based predictions and afferent proprioceptive signals with self-generated hand movements (‘active localization’) as well as based on proprioception only with robot-generated movements (‘passive localization’). In the exposure training group, we find indistinguishable shifts in passive and active hand localization, but after classic training, active localization shifts more than passive, indicating a contribution from updated predicted sensory consequences. Both changes in open-loop reaches and hand localization are only slightly smaller after exposure training as compared to after classic training, confirming that proprioception plays a large role in estimating limb position and in planning movements, even after adaptation. (data: https://doi.org/10.17605/osf.io/zfdth, preprint: https://doi.org/10.1101/384941)

scholarly journals Eye movements do not play an important role in the adaptation of hand tracking to a visuomotor rotation

2019 ◽  
Vol 121 (5) ◽  
pp. 1967-1976 ◽  
Author(s):  
Niels Gouirand ◽  
James Mathew ◽  
Eli Brenner ◽  
Frederic R. Danion
Keyword(s):  
Eye Movements ◽  
Time Course ◽  
Motor Behavior ◽  
Hand Movement ◽  
Visuomotor Adaptation ◽  
Online Control ◽  
Hand Movements ◽  
Hand Tracking ◽  
Gaze Fixation ◽  
The Gaze

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior. Although eye movements are known to assist hand movement control, how eye movements might contribute to the adaptation of hand movements remains largely unexplored. To determine to what extent eye movements contribute to visuomotor adaptation of hand tracking, participants were asked to track a visual target that followed an unpredictable trajectory with a cursor using a joystick. During blocks of trials, participants were either allowed to look wherever they liked or required to fixate a cross at the center of the screen. Eye movements were tracked to ensure gaze fixation as well as to examine free gaze behavior. The cursor initially responded normally to the joystick, but after several trials, the direction in which it responded was rotated by 90°. Although fixating the eyes had a detrimental influence on hand tracking performance, participants exhibited a rather similar time course of adaptation to rotated visual feedback in the gaze-fixed and gaze-free conditions. More importantly, there was extensive transfer of adaptation between the gaze-fixed and gaze-free conditions. We conclude that although eye movements are relevant for the online control of hand tracking, they do not play an important role in the visuomotor adaptation of such tracking. These results suggest that participants do not adapt by changing the mapping between eye and hand movements, but rather by changing the mapping between hand movements and the cursor’s motion independently of eye movements. NEW & NOTEWORTHY Eye movements assist hand movements in everyday activities, but their contribution to visuomotor adaptation remains largely unknown. We compared adaptation of hand tracking under free gaze and fixed gaze. Although our results confirm that following the target with the eyes increases the accuracy of hand movements, they unexpectedly demonstrate that gaze fixation does not hinder adaptation. These results suggest that eye movements have distinct contributions for online control and visuomotor adaptation of hand movements.

Hand Movement Training in Braille Reading

1981 ◽  
Vol 75 (8) ◽  
pp. 327-331 ◽  
Author(s):  
Diane P. Wormsley
Keyword(s):  
Character Recognition ◽  
Hand Movement ◽  
Movement Pattern ◽  
Hand Movements ◽  
Dramatic Decrease ◽  
Movement Training ◽  
Perceptual Ability ◽  
Tracking Movements

Twenty-one children ages 6 though 13 were taught to use their hands independently when reading braille to determine how this pattern of hand movements affected reading variables, excluding character recognition. Although all the children learned this pattern of hand movements during the 20 days scheduled for training, only nine children exhibited a dramatic decrease in inefficient tracking movements such as pauses and scrubbing motions. Because these children were younger and more intelligent than the others, read braille more slowly, and had received less training in braille at school, the results strongly suggested that skill in tracking and use of an efficient hand movement pattern is closely tied to perceptual ability. Thus when teaching children to read braille, the motor aspects of the task should be combined with the perceptual aspects from the beginning.

scholarly journals Distinct neuronal organizations of the caudal cingulate motor area and supplementary motor area in monkeys for ipsilateral and contralateral hand movements

2015 ◽  
Vol 113 (7) ◽  
pp. 2845-2858 ◽  
Author(s):  
Yoshihisa Nakayama ◽  
Osamu Yokoyama ◽  
Eiji Hoshi
Keyword(s):  
Neuronal Activity ◽  
Supplementary Motor Area ◽  
Functional Organization ◽  
Hand Movement ◽  
Motor Area ◽  
Hand Movements ◽  
Button Press ◽  
Cingulate Motor Area ◽  
Contralateral Hand ◽  
Hand Preferences

The caudal cingulate motor area (CMAc) and the supplementary motor area (SMA) play important roles in movement execution. The present study aimed to characterize the functional organization of these regions during movement by investigating laterality representations in the CMAc and SMA of monkeys via an examination of neuronal activity during a button press movement with either the right or left hand. Three types of movement-related neuronal activity were observed: 1) with only the contralateral hand, 2) with only the ipsilateral hand, and 3) with either hand. Neurons in the CMAc represented contralateral and ipsilateral hand movements to the same degree, whereas neuronal representations in the SMA were biased toward contralateral hand movement. Furthermore, recording neuronal activities using a linear-array multicontact electrode with 24 contacts spaced 150 μm apart allowed us to analyze the spatial distribution of neurons exhibiting particular hand preferences at the submillimeter scale. The CMAc and SMA displayed distinct microarchitectural organizations. The contralateral, ipsilateral, and bilateral CMAc neurons were distributed homogeneously, whereas SMA neurons exhibiting identical hand preferences tended to cluster. These findings indicate that the CMAc, which is functionally organized in a less structured manner than the SMA is, controls contralateral and ipsilateral hand movements in a counterbalanced fashion, whereas the SMA, which is more structured, preferentially controls contralateral hand movements.

Sign in / Sign up

Export Citation Format

Share Document