Predicting Motor Sequence Learning in Individuals With Chronic Stroke

Background. Conventionally, change in motor performance is quantified with discrete measures of behavior taken pre- and postpractice. As a high degree of movement variability exists in motor performance after stroke, pre- and posttesting of motor skill may lack sensitivity to predict potential for motor recovery. Objective. Evaluate the use of predictive models of motor learning based on individual performance curves and clinical characteristics of motor function in individuals with stroke. Methods. Ten healthy and fourteen individuals with chronic stroke performed a continuous joystick-based tracking task over 6 days, and at a 24-hour delayed retention test, to assess implicit motor sequence learning. Results. Individuals with chronic stroke demonstrated significantly slower rates of improvements in implicit sequence-specific motor performance compared with a healthy control (HC) group when root mean squared error performance data were fit to an exponential function. The HC group showed a positive relationship between a faster rate of change in implicit sequence-specific motor performance during practice and superior performance at the delayed retention test. The same relationship was shown for individuals with stroke only after accounting for overall motor function by including Wolf Motor Function Test rate in our model. Conclusion. Nonlinear information extracted from multiple time points across practice, specifically the rate of motor skill acquisition during practice, relates strongly with changes in motor behavior at the retention test following practice and could be used to predict optimal doses of practice on an individual basis.

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Impact of Explicit Information on Implicit Motor-Sequence Learning Following Middle Cerebral Artery Stroke

Physical Therapy ◽

10.1093/ptj/83.11.976 ◽

2003 ◽

Vol 83 (11) ◽

pp. 976-989 ◽

Cited By ~ 87

Author(s):

Lara A Boyd ◽

Carolee J Winstein

Keyword(s):

Middle Cerebral Artery ◽

Cerebral Artery ◽

Sequence Learning ◽

Retention Test ◽

Skill Learning ◽

Motor Sequence Learning ◽

Motor Sequence ◽

Explicit Information ◽

Implicit Motor ◽

The Impact

Abstract Background and Purpose. Recovery of motor skills following stroke is supported, in part, by the implicit memory system. However, attempts to guide learning commonly use explicit instructions concerning “how to” perform a movement task. The purpose of this work was to systematically investigate the impact of explicit information (EI) on implicit motor-sequence learning using the ipsilesional arm in people with damage in the middle cerebral artery (MCA) distribution. Subjects and Methods. Ten people with unilateral stroke in the MCA distribution affecting the sensorimotor cortical areas and 10 people with no known pathology or impairment (control participants) were randomly divided into 2 groups. One group was provided with EI and one group was not (EI and No-EI groups, respectively) as the participants practiced an implicit motor-sequencing task over 3 days, with a retention test on day 4. Results. A 3-way interaction demonstrated that, across days of practice, EI had opposite effects on implicit motor-sequence performance for the 2 groups. Post hoc tests confirmed that EI facilitated the performance of the control participants in the EI group but interfered with the performance of the participants with stroke in the EI group. This interference effect persisted, and was evident during the retention test in the participants with stroke in the EI group. Discussion and Conclusion. Explicit information was detrimental for implicit motor-sequence learning following MCA stroke. Rehabilitation outcomes may benefit from consideration of stroke location when determining the degree to which EI can augment implicit motor skill learning.

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Inhibition of contralesional motor cortex improves motor sequence learning in chronic stroke patients

Klinische Neurophysiologie ◽

10.1055/s-0030-1250950 ◽

2010 ◽

Vol 41 (01) ◽

Author(s):

M Zimerman ◽

J Hoppe ◽

K Heise ◽

GP Liuzzi ◽

N Freundlieb ◽

...

Keyword(s):

Motor Cortex ◽

Sequence Learning ◽

Chronic Stroke ◽

Motor Sequence Learning ◽

Motor Sequence ◽

Stroke Patients

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Brain Activity and Functional Connectivity Patterns Associated With Fast and Slow Motor Sequence Learning in Late Middle Adulthood

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.778201 ◽

2022 ◽

Vol 13 ◽

Author(s):

Maite Aznárez-Sanado ◽

Luis Eudave ◽

Martín Martínez ◽

Elkin O. Luis ◽

Federico Villagra ◽

...

Keyword(s):

Functional Connectivity ◽

Sequence Learning ◽

Motor Performance ◽

Brain Activity ◽

Connectivity Pattern ◽

Elderly Subjects ◽

Middle Adulthood ◽

Motor Sequence Learning ◽

Motor Sequence ◽

Connectivity Patterns

The human brain undergoes structural and functional changes across the lifespan. The study of motor sequence learning in elderly subjects is of particularly interest since previous findings in young adults might not replicate during later stages of adulthood. The present functional magnetic resonance imaging (fMRI) study assessed the performance, brain activity and functional connectivity patterns associated with motor sequence learning in late middle adulthood. For this purpose, a total of 25 subjects were evaluated during early stages of learning [i.e., fast learning (FL)]. A subset of these subjects (n = 11) was evaluated after extensive practice of a motor sequence [i.e., slow learning (SL) phase]. As expected, late middle adults improved motor performance from FL to SL. Learning-related brain activity patterns replicated most of the findings reported previously in young subjects except for the lack of hippocampal activity during FL and the involvement of cerebellum during SL. Regarding functional connectivity, precuneus and sensorimotor lobule VI of the cerebellum showed a central role during improvement of novel motor performance. In the sample of subjects evaluated, connectivity between the posterior putamen and parietal and frontal regions was significantly decreased with aging during SL. This age-related connectivity pattern may reflect losses in network efficiency when approaching late adulthood. Altogether, these results may have important applications, for instance, in motor rehabilitation programs.

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