scholarly journals Electroencephalographic connectivity measures predict learning of a motor sequencing task

2018 ◽  
Vol 119 (2) ◽  
pp. 490-498 ◽  
Author(s):  
Jennifer Wu ◽  
Franziska Knapp ◽  
Steven C. Cramer ◽  
Ramesh Srinivasan
Keyword(s):  
Motor Learning ◽  
Resting State ◽  
Societal Implications ◽  
Motor Training ◽  
Dominant Hand ◽  
Single Session ◽  
Motor Practice ◽  
Motor Improvement ◽  
Event Related Coherence ◽  
Sequencing Task

Individuals vary significantly with respect to rate and degree of improvement with motor practice. While the regions that underlie motor learning have been well described, neurophysiological factors underlying differences in response to motor practice are less well understood. The present study examined both resting-state and event-related EEG coherence measures of connectivity as predictors of response to motor practice on a motor sequencing task using the dominant hand. Thirty-two healthy young right-handed participants underwent resting EEG before motor practice. Response to practice was evaluated both across the single session of motor practice and 24 h later at a retention test of short-term motor learning. Behaviorally, the group demonstrated statistically significant gains both in single-session “motor improvement” and across-session “motor learning.” A resting-state measure of whole brain coherence with primary motor cortex (M1) at baseline robustly predicted subsequent motor improvement (validated R2 = 0.55) and motor learning (validated R2 = 0.68) in separate partial least-squares regression models. Specifically, greater M1 coherence with left frontal-premotor cortex (PMC) at baseline was characteristic of individuals likely to demonstrate greater gains in both motor improvement and motor learning. Analysis of event-related coherence with respect to movement found the largest changes occurring in areas implicated in planning and preparation of movement, including PMC and frontal cortices. While event-related coherence provided a stronger prediction of practice-induced motor improvement (validated R2 = 0.73), it did not predict the degree of motor learning (validated R2 = 0.16). These results indicate that connectivity in the resting state is a better predictor of consolidated learning of motor skills. NEW & NOTEWORTHY Differences in response to motor training have significant societal implications across a lifetime of motor skill practice. By evaluating both resting-state and event-related measures of brain function, our findings highlight interindividual differences in brain connectivity providing unique insights into differences in response to motor training. These findings have wide-ranging implications in settings ranging from advanced professional motor training to rehabilitation after brain injury.

scholarly journals Resting State Connectivity Is Modulated by Motor Learning in Individuals After Stroke

2021 ◽  
pp. 154596832110067
Author(s):  
Sarah N. Kraeutner ◽  
Cristina Rubino ◽  
Shie Rinat ◽  
Bimal Lakhani ◽  
Michael R. Borich ◽  
...  
Keyword(s):  
Motor Learning ◽  
Motor Function ◽  
Resting State ◽  
Brain Regions ◽  
Control Group ◽  
Network Efficiency ◽  
Resting State Functional Connectivity ◽  
Sensorimotor Network ◽  
Motor Practice ◽  
Stroke Group

Objective Activity patterns across brain regions that can be characterized at rest (ie, resting-state functional connectivity [rsFC]) are disrupted after stroke and linked to impairments in motor function. While changes in rsFC are associated with motor recovery, it is not clear how rsFC is modulated by skilled motor practice used to promote recovery. The current study examined how rsFC is modulated by skilled motor practice after stroke and how changes in rsFC are linked to motor learning. Methods Two groups of participants (individuals with stroke and age-matched controls) engaged in 4 weeks of skilled motor practice of a complex, gamified reaching task. Clinical assessments of motor function and impairment, and brain activity (via functional magnetic resonance imaging) were obtained before and after training. Results While no differences in rsFC were observed in the control group, increased connectivity was observed in the sensorimotor network, linked to learning in the stroke group. Relative to healthy controls, a decrease in network efficiency was observed in the stroke group following training. Conclusions Findings indicate that rsFC patterns related to learning observed after stroke reflect a shift toward a compensatory network configuration characterized by decreased network efficiency.

scholarly journals Multiple bouts of high-intensity interval exercise reverse age-related functional connectivity disruptions without affecting motor learning in older adults

2021 ◽  
Author(s):  
Brian Greeley ◽  
Briana Chau ◽  
Christina B. Jones ◽  
Jason L. Neva ◽  
Sarah N. Kraeutner ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Exercise Group ◽  
Resting State Functional Connectivity ◽  
Interval Exercise ◽  
Age Related ◽  
Motor Practice ◽  
High Intensity Interval

AbstractOlder adults show both age-related decreases in resting state functional connectivity and diminished sensorimotor function. Exercise has emerged as an intervention that may mitigate or even reverse these age-related declines. Here we sought to understand whether exercise impacts resting state functional connectivity, and motor acquisition and learning in older adults. Forty-two healthy older adults rested or completed 3 sets of high-intensity interval exercise (3 minutes at 75% maximal power output and 3 minutes light intensity) for a total of 23 minutes, then immediately practiced a complex, implicit motor task with their non-dominant hand across five separate sessions. Participants completed resting stage functional MRI before the first and after the fifth day of practice; they also returned 24-hours and 35-days following their fifth day of practice to complete short- and long-term retention tests to assess motor learning. Independent component analysis of resting state functional MRI revealed increased connectivity in the frontoparietal, the dorsal attentional, and cerebellar networks in the exercise group relative to the rest group. Seed-based analysis showed strengthened connectivity between the limbic system and right cerebellum, and between the right cerebellum and bilateral middle temporal gyri. There was no motor learning advantage for the exercise group; both rest and exercise groups demonstrated motor learning as measured at the short- and long-term retention tests. Our data suggest that exercise paired with a challenging implicit motor learning task in older adults can augment resting state functional connectivity without enhancing behaviour beyond that stimulated by skilled motor practice.Significance statementAging is accompanied by significant declines in the capacity for motor learning and changes in resting state functional connectivity; the net result is poor motor performance. Here, we show that five separate bouts of exercise paired with skilled motor practice strengthens resting state networks in brain regions that are susceptible to declines in older adults without affecting motor acquisition or learning. Overall, our results suggest that exercise may be effective in reducing age-related disruptions to resting state networks but not in enhancing motor learning beyond that stimulated by practice alone in older adults.

scholarly journals Explicit motor sequence learning after stroke: a neuropsychological study

2021 ◽  
Author(s):  
Cristina Russo ◽  
Laura Veronelli ◽  
Carlotta Casati ◽  
Alessia Monti ◽  
Laura Perucca ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Motor Learning ◽  
Upper Limb ◽  
Motor Recovery ◽  
Finger Tapping ◽  
Control Group ◽  
Stroke Severity ◽  
Motor Sequence ◽  
Stroke Patients ◽  
Motor Practice

AbstractMotor learning interacts with and shapes experience-dependent cerebral plasticity. In stroke patients with paresis of the upper limb, motor recovery was proposed to reflect a process of re-learning the lost/impaired skill, which interacts with rehabilitation. However, to what extent stroke patients with hemiparesis may retain the ability of learning with their affected limb remains an unsolved issue, that was addressed by this study. Nineteen patients, with a cerebrovascular lesion affecting the right or the left hemisphere, underwent an explicit motor learning task (finger tapping task, FTT), which was performed with the paretic hand. Eighteen age-matched healthy participants served as controls. Motor performance was assessed during the learning phase (i.e., online learning), as well as immediately at the end of practice, and after 90 min and 24 h (i.e., retention). Results show that overall, as compared to the control group, stroke patients, regardless of the side (left/right) of the hemispheric lesion, do not show a reliable practice-dependent improvement; consequently, no retention could be detected in the long-term (after 90 min and 24 h). The motor learning impairment was associated with subcortical damage, predominantly affecting the basal ganglia; conversely, it was not associated with age, time elapsed from stroke, severity of upper-limb motor and sensory deficits, and the general neurological condition. This evidence expands our understanding regarding the potential of post-stroke motor recovery through motor practice, suggesting a potential key role of basal ganglia, not only in implicit motor learning as previously pointed out, but also in explicit finger tapping motor tasks.

Error-related Persistence of Motor Activity in Resting-state Networks

2018 ◽  
Vol 30 (12) ◽  
pp. 1883-1901 ◽  
Author(s):  
Nicolò F. Bernardi ◽  
Floris T. Van Vugt ◽  
Ricardo Ruy Valle-Mena ◽  
Shahabeddin Vahdat ◽  
David J. Ostry
Keyword(s):  
Motor Learning ◽  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Neural Activation ◽  
Resting State Functional Connectivity ◽  
Movement Training ◽  
Movement Error ◽  
Human Participants

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.

scholarly journals Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study

2021 ◽  
Author(s):  
ATP Jäger ◽  
JM Huntenburg ◽  
SA Tremblay ◽  
U Schneider ◽  
S Grahl ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Control Group ◽  
Motor Execution ◽  
Motor Sequence ◽  
Resting State Functional Connectivity ◽  
Fast Learning ◽  
Slow Learning

AbstractIn motor learning, sequence-specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific increases in functional connectivity during fast learning in the sensorimotor territory of the internal segment of right globus pallidus (GPi), and sequence-specific decreases in right supplementary motor area (SMA) in overall learning. We found that connectivity changes in key regions of the motor network including the superior parietal cortex (SPC) and primary motor cortex (M1) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA and GPi that has previously been identified in online task-based learning studies in humans and primates, and extends it to resting state network changes after sequence-specific MSL. Finally, our results shed light on a timing-specific plasticity mechanism between GPi and SMA following MSL.

scholarly journals Serum BDNF’s Role as a Biomarker for Motor Training in the Context of AR-Based Rehabilitation after Ischemic Stroke

2020 ◽  
Vol 10 (9) ◽  
pp. 623
Author(s):  
Ekaterina S. Koroleva ◽  
Ivan V. Tolmachev ◽  
Valentina M. Alifirova ◽  
Anastasiia S. Boiko ◽  
Lyudmila A. Levchuk ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Functional Disability ◽  
Motor Impairment ◽  
Motor Training ◽  
Training Methods ◽  
Motion Sensors ◽  
Early Recovery ◽  
Active Rehabilitation ◽  
Motor Improvement ◽  
Serum Bdnf

Background: brain-derived neurotrophic factor (BDNF) may play a role during neurorehabilitation following ischemic stroke. This study aimed to elucidate the possible role of BDNF during early recovery from ischemic stroke assisted by motor training. Methods: fifty patients were included after acute recovery from ischemic stroke: 21 first received classical rehabilitation followed by ‘motor rehabilitation using motion sensors and augmented reality’ (AR-rehabilitation), 14 only received AR-rehabilitation, and 15 were only observed. Serum BDNF levels were measured on the first day of stroke, on the 14th day, before AR-based rehabilitation (median, 45th day), and after the AR-based rehabilitation (median, 82nd day). Motor impairment was quantified clinically using the Fugl–Meyer scale (FMA); functional disability and activities of daily living (ADL) were measured using the Modified Rankin Scale (mRS). For comparison, serum BDNF was measured in 50 healthy individuals. Results: BDNF levels were found to significantly increase during the phase with AR-based rehabilitation. The pattern of the sequentially measured BDNF levels was similar in the treated patients. Untreated patients had significantly lower BDNF levels at the endpoint. Conclusions: the fluctuations of BDNF levels are not consistently related to motor improvement but seem to react to active treatment. Without active rehabilitation treatment, BDNF tends to decrease.

Nonvisual Motor Learning Improves Visual Motion Perception: Evidence From Violating the Two-Thirds Power Law

2010 ◽  
Vol 104 (3) ◽  
pp. 1612-1624 ◽  
Author(s):  
I.A.M. Beets ◽  
F. Rösler ◽  
K. Fiehler
Keyword(s):  
Motor Learning ◽  
Velocity Profile ◽  
Power Law ◽  
Visual Discrimination ◽  
Discrimination Task ◽  
Visual Motion ◽  
Visual Discrimination Task ◽  
Control Group ◽  
Motor Training ◽  
Training Groups

Few studies have reported direct effects of motor learning on visual perception, especially when using novel movements for the motor system. Atypical motor behaviors that violate movement constraints provide an excellent opportunity to study action-to-perception transfer. In our study, we passively trained blindfolded participants on movements violating the 2/3 power law. Before and after motor training, participants performed a visual discrimination task in which they decided whether two consecutive movements were same or different. For motor training, we randomly assigned the participants to two motor training groups or a control group. The motor training group experienced either a weak or a strong elliptic velocity profile on a circular trajectory that matched one of the visual test stimuli. The control group was presented with linear trajectories unrelated to the viewed movements. After each training session, participants actively reproduced the movement to assess motor learning. The group trained on the strong elliptic velocity profile reproduced movements with increasing elliptic velocity profiles while circular geometry remained constant. Furthermore, both training groups improved in visual discrimination ability for the learned movement as well as for highly similar movements. Participants in the control group, however, did not show any improvements in the visual discrimination task nor did participants who did not acquire the trained movement. The present results provide evidence for a transfer from action to perception which generalizes to highly related movements and depends on the success of motor learning. Moreover, under specific conditions, it seems to be possible to acquire movements deviating from the 2/3 power law.

scholarly journals Optimal Schedules in Multitask Motor Learning

2016 ◽  
Vol 28 (4) ◽  
pp. 667-685 ◽  
Author(s):  
Jeong Yoon Lee ◽  
Youngmin Oh ◽  
Sung Shin Kim ◽  
Robert A. Scheidt ◽  
Nicolas Schweighofer
Keyword(s):  
Motor Learning ◽  
Computational Models ◽  
Practical Importance ◽  
State Space Model ◽  
Retention Performance ◽  
Single Session ◽  
Term Retention ◽  
Long Term Retention ◽  
Do So

Although scheduling multiple tasks in motor learning to maximize long-term retention of performance is of great practical importance in sports training and motor rehabilitation after brain injury, it is unclear how to do so. We propose here a novel theoretical approach that uses optimal control theory and computational models of motor adaptation to determine schedules that maximize long-term retention predictively. Using Pontryagin’s maximum principle, we derived a control law that determines the trial-by-trial task choice that maximizes overall delayed retention for all tasks, as predicted by the state-space model. Simulations of a single session of adaptation with two tasks show that when task interference is high, there exists a threshold in relative task difficulty below which the alternating schedule is optimal. Only for large differences in task difficulties do optimal schedules assign more trials to the harder task. However, over the parameter range tested, alternating schedules yield long-term retention performance that is only slightly inferior to performance given by the true optimal schedules. Our results thus predict that in a large number of learning situations wherein tasks interfere, intermixing tasks with an equal number of trials is an effective strategy in enhancing long-term retention.

scholarly journals A single session of exercise increases connectivity in sensorimotor-related brain networks: a resting-state fMRI study in young healthy adults

2014 ◽  
Vol 8 ◽  
Author(s):  
Ahmad S. Rajab ◽  
David E. Crane ◽  
Laura E. Middleton ◽  
Andrew D. Robertson ◽  
Michelle Hampson ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Healthy Adults ◽  
Single Session ◽  
Fmri Study
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