Bimanual force variability in chronic stroke: With and without visual information

Kang, Nyeonju; Cauraugh, James H.

doi:10.1016/j.neulet.2014.12.028

Cited by 22 publications

(14 citation statements)

References 36 publications

(74 reference statements)

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“…Force production by individuals in the chronic phase after stroke reveals greater error and greater variability when using the impaired hand ( Kang and Cauraugh, 2015b , Lodha et al, 2010 ). Dependence on visual feedback increases after stroke ( Bonan et al, 2004a , Kang and Cauraugh, 2015a , Westerveld et al, 2013 ), with evidence suggesting that manipulating visual feedback can enhance motor function ( Brewer et al, 2005 , Brewer et al, 2008 , Patton et al, 2006 , Tunik et al, 2013 ) by decreasing motor error and motor variability after stroke ( Archer et al, 2016 ). Although these findings converge to suggest that modulating visual feedback is a viable option to improve motor output ( Carter et al, 2010 , Tunik et al, 2013 ), the neurophysiological basis for this improvement has not been examined.…”

Section: Introductionmentioning

confidence: 99%

Visual feedback alters force control and functional activity in the visuomotor network after stroke

Archer

Kang

Misra

et al. 2018

NeuroImage: Clinical

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Modulating visual feedback may be a viable option to improve motor function after stroke, but the neurophysiological basis for this improvement is not clear. Visual gain can be manipulated by increasing or decreasing the spatial amplitude of an error signal. Here, we combined a unilateral visually guided grip force task with functional MRI to understand how changes in the gain of visual feedback alter brain activity in the chronic phase after stroke. Analyses focused on brain activation when force was produced by the most impaired hand of the stroke group as compared to the non-dominant hand of the control group. Our experiment produced three novel results. First, gain-related improvements in force control were associated with an increase in activity in many regions within the visuomotor network in both the stroke and control groups. These regions include the extrastriate visual cortex, inferior parietal lobule, ventral premotor cortex, cerebellum, and supplementary motor area. Second, the stroke group showed gain-related increases in activity in additional regions of lobules VI and VIIb of the ipsilateral cerebellum. Third, relative to the control group, the stroke group showed increased activity in the ipsilateral primary motor cortex, and activity in this region did not vary as a function of visual feedback gain. The visuomotor network, cerebellum, and ipsilateral primary motor cortex have each been targeted in rehabilitation interventions after stroke. Our observations provide new insight into the role these regions play in processing visual gain during a precisely controlled visuomotor task in the chronic phase after stroke.

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Section: Introductionmentioning

confidence: 99%

Visual feedback alters force control and functional activity in the visuomotor network after stroke

Archer

Kang

Misra

et al. 2018

NeuroImage: Clinical

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“…Beyond the effects of offline-bandwidth visual feedback, we additionally confirmed that providing the online-bandwidth visual feedback with narrower BTR effectively minimized inconsistency of motor outputs during task execution. Greater amount of visual information (e.g., increased visual gain) may decrease motor variability during continuous isometric force production tasks [41,42] because of the reduced neural noise (e.g., synaptic noise of motor neurons pool) on motor unit discharge [43]. Similarly, given that the narrow BTR of bandwidth visual feedback may provide more frequent visual cues to a performer during isometric force control tasks [20], the increased amount of visual information presumably minimized neural noise contributing to less force variability.…”

Section: Discussionmentioning

confidence: 99%

Effects of online-bandwidth visual feedback on unilateral force control capabilities

Lee

Kang

2020

PLoS ONE

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The purpose of this study was to examine how different threshold ranges of online-bandwidth visual feedback influence unilateral force control capabilities in healthy young women. Methods Twenty-five right-handed young women (mean±standard deviation age = 23.6±1.5 years) participated in this study. Participants unilaterally executed hand-grip force control tasks with their dominant and non-dominant hands, respectively. Each participant completed four experimental blocks in a different order of block presentation for each hand condition: (a) 10% of maximum voluntary contraction (MVC) with ±5% bandwidth threshold range (BTR), (b) 10% of MVC with ±10% BTR, (c) 40% of MVC with ±5% BTR, and (d) 40% of MVC with ±10% BTR. Outcome measures on force control capabilities included: (a) force accuracy, (b) force variability, (c) force regularity, and (d) the number of times and duration out of BTR. Results The non-dominant hand showed significant improvements in force control capabilities, as indicated by higher force accuracy, less force variability, and decreased force regularity from ±10% BTR to ±5% BTR during higher targeted force level task. For both hands, the number of times and duration out of BTR increased from ±10% BTR to ±5% BTR. Conclusions The current findings suggested that the narrow threshold range of online-bandwidth visual feedback effectively revealed transient improvements in unilateral isometric force control capabilities during higher targeted force level tasks.

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“…In studies of gripping [ 18 ], reaching [ 36 , 37 ] and multi-joint arm movement [ 38 ], greater neuromotor noise was reported in subjects after stroke. Neuromotor noise causes more errors in force output, and post-stroke subjects would rely more on feedback control to correct the errors [ 39 ]. As reported by Kim et al [ 14 ], the decrease in smoothness was accompanied by an increase in the number of force corrections.…”

Section: Discussionmentioning

confidence: 99%

Characterization of the Stroke-Induced Changes in the Variability and Complexity of Handgrip Force

Zhu

Liang

et al. 2018

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Introduction:The variability and complexity of handgrip forces in various modulations were investigated to identify post-stroke changes in force modulation, and extend our understanding of stroke-induced deficits. Methods: Eleven post-stroke subjects and ten age-matched controls performed voluntary grip force control tasks (power-grip tasks) at three contraction levels, and stationary dynamometer holding tasks (stationary holding tasks). Variability and complexity were described with root mean square jerk (RMS-jerk) and fuzzy approximate entropy (fApEn), respectively. Force magnitude, Fugl-Meyer upper extremity assessment and Wolf motor function test were also evaluated. Results: Comparing the affected side with the controls, fApEn was significantly decreased and RMS-jerk increased across the three levels in power-grip tasks, and fApEn was significantly decreased in stationary holding tasks. There were significant strong correlations between RMS-jerk and clinical scales in power-grip tasks. Discussion: Abnormal neuromuscular control, altered mechanical properties, and atrophic motoneurons could be the main causes of the differences in complexity and variability in post-stroke subjects.

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Bimanual force variability in chronic stroke: With and without visual information

Cited by 22 publications

References 36 publications

Visual feedback alters force control and functional activity in the visuomotor network after stroke

Visual feedback alters force control and functional activity in the visuomotor network after stroke

Effects of online-bandwidth visual feedback on unilateral force control capabilities

Characterization of the Stroke-Induced Changes in the Variability and Complexity of Handgrip Force

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