The Experts below are selected from a list of 391953 Experts worldwide ranked by ideXlab platform
Jeffrey M Hausdorff - One of the best experts on this subject based on the ideXlab platform.
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virtual reality for gait training can it induce Motor Learning to enhance complex walking and reduce fall risk in patients with parkinson s disease
Journals of Gerontology Series A-biological Sciences and Medical Sciences, 2011Co-Authors: Anat Mirelman, Inbal Maidan, Talia Herman, Judith E Deutsch, Nir Giladi, Jeffrey M HausdorffAbstract:234 PARKINSON’S disease (PD) impairs gait and Motor function while also impacting cognition, most notably executive function (EF) and attention (1,2). These deficits further exacerbate difficulties with mobility, especially during complex and “dual-task” (DT) gait activities when patients are required to walk while performing another task. As in the general elderly population (3–8), in PD, EF, attention, and DT abilities have been associated with fall risk (9–11). Traditional treatment approaches in PD have focused mainly on symptom relief to maximize function and minimize secondary complications. Indeed, until recently, the assumption has been that Motor Learning cannot take place in the presence of impaired basal ganglia (12,13). Evidence from animal models and patient studies suggests, however, that this may not be the case (14–17). Pathways involving the basal ganglia in PD may be capable of plasticity, and their activity patterns may be partly corrected with appropriate intensive training (18–20). To date, improvements in usual walking were reported following treadmill training (TT), while the effects of training on obstacle negotiation, complex walking, and DT abilities are still largely unexplored (21). In addition, it is not clear if training in patients with PD can transfer beyond the task that was specifically trained or if long-term retention is possible (17,22). To address these questions, we employed virtual reality (VR), a relatively new intervention modality in the field of neurorehabilitation. VR applications can provide visual, Virtual Reality for Gait Training: Can It Induce Motor Learning to Enhance Complex Walking and Reduce Fall Risk in Patients With Parkinson’s Disease?
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virtual reality for gait training can it induce Motor Learning to enhance complex walking and reduce fall risk in patients with parkinson s disease
Journals of Gerontology Series A-biological Sciences and Medical Sciences, 2011Co-Authors: Judith E Deutsch, Nir Giladi, Jeffrey M Hausdorff, Ana Mirelma, Inbal Maida, Talia HermaAbstract:BACKGROUND Gait and cognitive disturbances are common in Parkinson's disease (PD). These deficits exacerbate fall risk and difficulties with mobility, especially during complex or dual-task walking. Traditional gait training generally fails to fully address these complex gait activities. Virtual reality (VR) incorporates principles of Motor Learning while delivering engaging and challenging training in complex environments. We hypothesized that VR may be applied to address the multifaceted deficits associated with fall risk in PD. METHODS Twenty patients received 18 sessions (3 per week) of progressive intensive treadmill training with virtual obstacles (TT + VR). Outcome measures included gait under usual-walking and dual-task conditions and while negotiating physical obstacles. Cognitive function and functional performance were also assessed. RESULTS Patients were 67.1 ± 6.5 years and had a mean disease duration of 9.8 ± 5.6 years. Posttraining, gait speed significantly improved during usual walking, during dual task, and while negotiating overground obstacles. Dual-task gait variability decreased (ie, improved) and Trail Making Test times (parts A and B) improved. Gains in functional performance measures and retention effects, 1 month later, were also observed. CONCLUSIONS To our knowledge, this is the first time that TT + VR has been used for gait training in PD. The results indicate that TT + VR is viable in PD and may significantly improve physical performance, gait during complex challenging conditions, and even certain aspects of cognitive function. These findings have important implications for understanding Motor Learning in the presence of PD and for treating fall risk in PD, aging, and others who share a heightened risk of falls.
Paul L Gribble - One of the best experts on this subject based on the ideXlab platform.
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sensory plasticity in human Motor Learning
Trends in Neurosciences, 2016Co-Authors: David J Ostry, Paul L GribbleAbstract:There is accumulating evidence from behavioral, neurophysiological, and neuroimaging studies that the acquisition of Motor skills involves both perceptual and Motor Learning. Perceptual Learning alters movements, Motor Learning, and Motor networks of the brain. Motor Learning changes perceptual function and the sensory circuits of the brain. Here, we review studies of both human limb movement and speech that indicate that plasticity in sensory and Motor systems is reciprocally linked. Taken together, this points to an approach to Motor Learning in which perceptual Learning and sensory plasticity have a fundamental role.
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somatosensory plasticity and Motor Learning
The Journal of Neuroscience, 2010Co-Authors: David J Ostry, Mohammad Darainy, Andrew A G Matta, Jeremy D Wong, Paul L GribbleAbstract:Motor Learning is dependent upon plasticity in Motor areas of the brain, but does it occur in isolation, or does it also result in changes to sensory systems? We examined changes to somatosensory function that occur in conjunction with Motor Learning. We found that even after periods of training as brief as 10 min, sensed limb position was altered and the perceptual change persisted for 24 h. The perceptual change was reflected in subsequent movements; limb movements following Learning deviated from the preLearning trajectory by an amount that was not different in magnitude and in the same direction as the perceptual shift. Crucially, the perceptual change was dependent upon Motor Learning. When the limb was displaced passively such that subjects experienced similar kinematics but without Learning, no sensory change was observed. The findings indicate that Motor Learning affects not only Motor areas of the brain but changes sensory function as well.
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Motor Learning by observing
Neuron, 2005Co-Authors: Andrew A G Matta, Paul L GribbleAbstract:Learning complex Motor behaviors like riding a bicycle or swinging a golf club is based on acquiring neural representations of the mechanical requirements of movement (e.g., coordinating muscle forces to control the club). Here we provide evidence that mechanisms matching observation and action facilitate Motor Learning. Subjects who observed a video depicting another person Learning to reach in a novel mechanical environment (imposed by a robot arm) performed better when later tested in the same environment than subjects who observed similar movements but no Learning; moreover, subjects who observed Learning of a different environment performed worse. We show that this effect is not based on conscious strategies but instead depends on the implicit engagement of neural systems for movement planning and control.
Dianne M Broussard - One of the best experts on this subject based on the ideXlab platform.
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the bidirectionality of Motor Learning in the vestibulo ocular reflex is a function of cerebellar mglur1 receptors
Journal of Neurophysiology, 2010Co-Authors: Heather K Titley, Raquel Heskinsweezie, Dianne M BroussardAbstract:Bidirectional changes in synaptic transmission have the potential to optimize the control of movement. However, it can be difficult to establish a causal relationship between the bidirectionality of synaptic plasticity and bidirectional changes in the speed of actual movements. We asked whether metabotropic glutamate receptor 1 (mGluR1) receptors, which participate in cerebellar long-term depression (LTD), are necessary for bidirectional Motor Learning in the vestibulo-ocular reflex (VOR). Cerebellar LTD and long-term potentiation (LTP) are thought to cause increases and decreases, respectively, in the gain of the VOR; the direction of Learning depends on the behavioral protocol. We injected either the mGluR1 agonist (S)-DHPG or the antagonist YM 298198 bilaterally into the flocculus of alert cats, and then induced Motor Learning. In the presence of YM 298198, the VOR gain decreased in gain-up, as well as in gain-down protocols. (S)-DHPG augmented gain-up Learning. Gain-down Learning was not significantly affected by either drug. These results supported the hypothesis that gain-up Learning relies on cerebellar LTD, but gain-down Learning relies on a different mechanism. In the absence of mGluR1 activity, cerebellar LTD may be replaced with LTP, permitting Learning in only one direction.
David J Ostry - One of the best experts on this subject based on the ideXlab platform.
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sensory plasticity in human Motor Learning
Trends in Neurosciences, 2016Co-Authors: David J Ostry, Paul L GribbleAbstract:There is accumulating evidence from behavioral, neurophysiological, and neuroimaging studies that the acquisition of Motor skills involves both perceptual and Motor Learning. Perceptual Learning alters movements, Motor Learning, and Motor networks of the brain. Motor Learning changes perceptual function and the sensory circuits of the brain. Here, we review studies of both human limb movement and speech that indicate that plasticity in sensory and Motor systems is reciprocally linked. Taken together, this points to an approach to Motor Learning in which perceptual Learning and sensory plasticity have a fundamental role.
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functionally specific changes in resting state sensoriMotor networks after Motor Learning
The Journal of Neuroscience, 2011Co-Authors: Shahabeddi Vahda, Mohammad Darainy, Theodore E Milne, David J OstryAbstract:Motor Learning changes the activity of cortical Motor and subcortical areas of the brain, but does Learning affect sensory systems as well? We examined in humans the effects of Motor Learning using fMRI measures of functional connectivity under resting conditions and found persistent changes in networks involving both Motor and somatosensory areas of the brain. We developed a technique that allows us to distinguish changes in functional connectivity that can be attributed to Motor Learning from those that are related to perceptual changes that occur in conjunction with Learning. Using this technique, we identified a new network in Motor Learning involving second somatosensory cortex, ventral preMotor cortex, and supplementary Motor cortex whose activation is specifically related to perceptual changes that occur in conjunction with Motor Learning. We also found changes in a network comprising cerebellar cortex, primary Motor cortex, and dorsal preMotor cortex that were linked to the Motor aspects of Learning. In each network, we observed highly reliable linear relationships between neuroplastic changes and behavioral measures of either Motor Learning or perceptual function. Motor Learning thus results in functionally specific changes to distinct resting-state networks in the brain.
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somatosensory plasticity and Motor Learning
The Journal of Neuroscience, 2010Co-Authors: David J Ostry, Mohammad Darainy, Andrew A G Matta, Jeremy D Wong, Paul L GribbleAbstract:Motor Learning is dependent upon plasticity in Motor areas of the brain, but does it occur in isolation, or does it also result in changes to sensory systems? We examined changes to somatosensory function that occur in conjunction with Motor Learning. We found that even after periods of training as brief as 10 min, sensed limb position was altered and the perceptual change persisted for 24 h. The perceptual change was reflected in subsequent movements; limb movements following Learning deviated from the preLearning trajectory by an amount that was not different in magnitude and in the same direction as the perceptual shift. Crucially, the perceptual change was dependent upon Motor Learning. When the limb was displaced passively such that subjects experienced similar kinematics but without Learning, no sensory change was observed. The findings indicate that Motor Learning affects not only Motor areas of the brain but changes sensory function as well.
Lara A Boyd - One of the best experts on this subject based on the ideXlab platform.
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Motor Learning after stroke is skill acquisition a prerequisite for contralesional neuroplastic change
Neuroscience Letters, 2010Co-Authors: Lara A Boyd, Eric D Vidoni, B D WesselAbstract:Limited data directly characterize the dynamic evolution of brain activity associated with Motor Learning after stroke. The current study considered whether sequence-specific Motor skill Learning or increasing non-specific use of the hemiparetic upper extremity drive functional reorganization of the contralesional Motor cortex after stroke. Eighteen individuals with chronic middle cerebral artery stroke practiced one of two novel Motor tasks; a retention test occurred on a separate fifth day. Using the hemiparetic arm, participants performed a serial targeting task during two functional MRI scans (day one and retention). Participants were randomized into either a task-specific group, who completed three additional sessions of serial targeting practice, or a general arm use group, who underwent three training sessions of increased but non-task specific use of the hemiparetic arm. Both groups performed a repeated sequence of responses that may be learned, and random sequences of movement, which cannot be learned. Change in reaction and movement time for the repeated sequence indexed Motor Learning; shifts in the laterality index (LI) within primary Motor cortex (M1) for repeated and random sequences illustrated training effects on brain activity. Task-specific practice of the repeated sequence facilitated Motor Learning and shifted the LI for M1 as shown by a reduced volume of contralesional cortical activity. Random sequence performance did not stimulate Motor Learning or alter the LI within the task-specific training group. Further, between-group comparisons showed that increasing general arm use did not induce Motor Learning or alter brain activity for either random or repeated sequences. Motor skill Learning of a repeated sequence altered cortical activation by inducing a more normal, contralateral pattern of brain activation. Our data suggest that task-specific Motor Learning may be an important stimulant for neuroplastic change and can remediate maladaptive patterns of brain activity after stroke.
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role of the primary somatosensory cortex in Motor Learning an rtms study
Neurobiology of Learning and Memory, 2010Co-Authors: Eric D Vidoni, N E Acerra, Sean K Meehan, Lara A BoydAbstract:Abstract Somatosensation is thought to play an important role in skilled Motor Learning. The present study investigated how healthy adults learn a continuous implicit Motor task when somatosensation is altered by 1 Hz repetitive transcranial magnetic stimulation (rTMS) delivered over the primary somatosensory cortex (S1). Twenty-seven right-handed participants enrolled in a two-part experiment. In Experiment 1, we verified that 20 min of 1 Hz rTMS over S1 disrupted cutaneous somatosensation (indexed by two-point discrimination) in the wrist/hand; the impact of 1 Hz rTMS on wrist proprioception (tested by limb-position matching) was variable. Sham rTMS had no effect on either measure. We exploited these effects in Experiment 2 by pairing either 1 Hz or sham rTMS with practice of a continuous tracking task over two separate sessions on different days. Implicit Motor Learning was indexed on a third, separate retention test day when no rTMS was delivered. Across practice in Experiment 2, both the 1 Hz and sham rTMS groups showed improved tracking performance; however, 1 Hz rTMS was associated with less accurate tracking and smaller improvements in performance. Importantly, at the no rTMS retention test the effects of altering sensation with stimulation over S1 were still evident in the persistently less accurate tracking behavior of the 1 Hz rTMS group. The current study shows that disruption of somatosensation during task practice impairs the magnitude of change associated with Motor Learning, perhaps through the development of an inaccurate internal model.
