scholarly journals Resting-state connectivity after visuo-motor skill learning is inversely associated with offline consolidation in Parkinson's disease and healthy controls

Cortex ◽  
2018 ◽  
Vol 106 ◽  
pp. 237-247 ◽  
Author(s):  
Aurélie L. Manuel ◽  
Nicolas Nicastro ◽  
Armin Schnider ◽  
Adrian G. Guggisberg
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Skill ◽  
Resting State ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Healthy Controls ◽  
Resting State Connectivity

Resting-state connectivity predicts visuo-motor skill learning

NeuroImage ◽  
2018 ◽  
Vol 176 ◽  
pp. 446-453 ◽  
Author(s):  
Aurélie L. Manuel ◽  
Adrian G. Guggisberg ◽  
Raphaël Thézé ◽  
Francesco Turri ◽  
Armin Schnider
Keyword(s):  
Motor Skill ◽  
Resting State ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Resting State Connectivity

scholarly journals Implicit perceptual-motor skill learning in mild cognitive impairment and Parkinson’s disease.

2013 ◽  
Vol 27 (3) ◽  
pp. 314-321 ◽  
Author(s):  
Eric W. Gobel ◽  
Kelsey Blomeke ◽  
Cindy Zadikoff ◽  
Tanya Simuni ◽  
Sandra Weintraub ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Motor Skill ◽  
Skill Learning ◽  
Motor Skill Learning

scholarly journals The contribution of nocturnal sleep to the consolidation of motor skill learning in healthy ageing and Parkinson's disease

2013 ◽  
Vol 22 (4) ◽  
pp. 398-405 ◽  
Author(s):  
Zoe Terpening ◽  
Sharon Naismith ◽  
Kerri Melehan ◽  
Catherine Gittins ◽  
Sam Bolitho ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Skill ◽  
Healthy Ageing ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Nocturnal Sleep

Corrigendum to “Resting-state connectivity predicts visuo-motor skill learning” [Neuroimage 176 (2018) 446–453]

NeuroImage ◽  
2019 ◽  
Vol 185 ◽  
pp. 83-84
Author(s):  
A.L. Manuel ◽  
A.G. Guggisberg ◽  
R. Thézé ◽  
F. Turri ◽  
A. Schnider
Keyword(s):  
Motor Skill ◽  
Resting State ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Resting State Connectivity

scholarly journals Motor Skill Learning, Retention, and Control Deficits in Parkinson's Disease

PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e21669 ◽  
Author(s):  
Lisa Katharina Pendt ◽  
Iris Reuter ◽  
Hermann Müller
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Skill ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Learning Retention ◽  
And Control

scholarly journals Sensorimotor cortex beta oscillations reflect motor skill learning ability after stroke

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Svenja Espenhahn ◽  
Holly E Rossiter ◽  
Bernadette C M van Wijk ◽  
Nell Redman ◽  
Jane M Rondina ◽  
...  
Keyword(s):  
Motor Learning ◽  
Sensorimotor Cortex ◽  
Motor Skill ◽  
Motor Performance ◽  
Skill Learning ◽  
Motor Skill Learning ◽  
Healthy Controls ◽  
Stroke Patients ◽  
Beta Oscillations ◽  
And Performance

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.

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