scholarly journals Dual-tDCS Enhances Online Motor Skill Learning and Long-Term Retention in Chronic Stroke Patients

Author(s):  
S. Lefebvre ◽  
P. Laloux ◽  
A. Peeters ◽  
P. Desfontaines ◽  
J. Jamart ◽  
...  
2020 ◽  
Author(s):  
Svenja Espenhahn ◽  
Holly E Rossiter ◽  
Bernadette CM van Wijk ◽  
Nell Redman ◽  
Jane M Rondina ◽  
...  

AbstractRecovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study we firstly compared motor skill acquisition and retention between well-recovered stroke patients and age- and performance-matched healthy controls. We then tested whether beta oscillations (15–30Hz) from sensorimotor cortices contribute to predicting training-related motor performance.Eighteen well-recovered chronic stroke survivors (mean age 64±8 years, range 50–74 years) and twenty age- and sex-matched healthy controls were trained on a continuous tracking task and subsequently retested after initial training (45–60 min and 24 hours later). Scalp EEG was recorded during the performance of a simple motor task before each training and retest session. Stroke patients demonstrated capacity for motor skill learning, but it was diminished compared to age- and performance-matched healthy controls. Further, although the properties of beta oscillations prior to training were comparable between stroke patients and healthy controls, stroke patients did show less change in beta measures with motor learning. Lastly, although beta oscillations did not help to predict motor performance immediately after training, contralateral (ipsilesional) sensorimotor cortex post-movement beta rebound (PMBR) measured after training helped predict future motor performance, 24 hours after training. This finding suggests that neurophysiological measures such as beta oscillations can help predict response to motor training in chronic stroke patients and may offer novel targets for therapeutic interventions.


2013 ◽  
Vol 333 ◽  
pp. e571
Author(s):  
S. Lefebvre ◽  
L. Dricot ◽  
W. Gradkowski ◽  
P. Laloux ◽  
P. Desfontaines ◽  
...  

2005 ◽  
Vol 94 (1) ◽  
pp. 512-518 ◽  
Author(s):  
A. Floyer-Lea ◽  
P. M. Matthews

The acquisition of a new motor skill is characterized first by a short-term, fast learning stage in which performance improves rapidly, and subsequently by a long-term, slower learning stage in which additional performance gains are incremental. Previous functional imaging studies have suggested that distinct brain networks mediate these two stages of learning, but direct comparisons using the same task have not been performed. Here we used a task in which subjects learn to track a continuous 8-s sequence demanding variable isometric force development between the fingers and thumb of the dominant, right hand. Learning-associated changes in brain activation were characterized using functional MRI (fMRI) during short-term learning of a novel sequence, during short-term learning after prior, brief exposure to the sequence, and over long-term (3 wk) training in the task. Short-term learning was associated with decreases in activity in the dorsolateral prefrontal, anterior cingulate, posterior parietal, primary motor, and cerebellar cortex, and with increased activation in the right cerebellar dentate nucleus, the left putamen, and left thalamus. Prefrontal, parietal, and cerebellar cortical changes were not apparent with short-term learning after prior exposure to the sequence. With long-term learning, increases in activity were found in the left primary somatosensory and motor cortex and in the right putamen. Our observations extend previous work suggesting that distinguishable networks are recruited during the different phases of motor learning. While short-term motor skill learning seems associated primarily with activation in a cortical network specific for the learned movements, long-term learning involves increased activation of a bihemispheric cortical-subcortical network in a pattern suggesting “plastic” development of new representations for both motor output and somatosensory afferent information.


2019 ◽  
Vol 31 (4) ◽  
pp. 212-215
Author(s):  
Sung Min Son ◽  
Yoon Tae Hwang ◽  
Seok Hyun Nam ◽  
Yonghyun Kwon

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Svenja Espenhahn ◽  
Holly E Rossiter ◽  
Bernadette C M van Wijk ◽  
Nell Redman ◽  
Jane M Rondina ◽  
...  

Abstract Recovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study, we first compared motor skill acquisition and retention between well-recovered stroke patients and age- and performance-matched healthy controls. We then tested whether beta oscillations (15–30 Hz) from sensorimotor cortices contribute to predicting training-related motor performance. Eighteen well-recovered chronic stroke survivors (mean age 64 ± 8 years, range: 50–74 years) and 20 age- and sex-matched healthy controls were trained on a continuous tracking task and subsequently retested after initial training (45–60 min and 24 h later). Scalp electroencephalography was recorded during the performance of a simple motor task before each training and retest session. Stroke patients demonstrated capacity for motor skill learning, but it was diminished compared to age- and performance-matched healthy controls. Furthermore, although the properties of beta oscillations prior to training were comparable between stroke patients and healthy controls, stroke patients did show less change in beta measures with motor learning. Lastly, although beta oscillations did not help to predict motor performance immediately after training, contralateral (ipsilesional) sensorimotor cortex post-movement beta rebound measured after training helped predict future motor performance, 24 h after training. This finding suggests that neurophysiological measures such as beta oscillations can help predict response to motor training in chronic stroke patients and may offer novel targets for therapeutic interventions.


2002 ◽  
Vol 147 (4) ◽  
pp. 494-504 ◽  
Author(s):  
Hikosaka O. ◽  
Rand M. ◽  
Nakamura K. ◽  
Miyachi S. ◽  
Kitaguchi K. ◽  
...  

2020 ◽  
Vol 131 (4) ◽  
pp. 791-798
Author(s):  
Ronan A. Mooney ◽  
John Cirillo ◽  
Cathy M. Stinear ◽  
Winston D. Byblow

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