Motor Learning

Comprehensive physiology, Journal Year: 2019, Volume and Issue: unknown, P. 613 - 663

Published: March 14, 2019

Motor learning encompasses a wide range of phenomena, ranging from relatively low-level mechanisms for maintaining calibration our movements, to making high-level cognitive decisions about how act in novel situation. We survey the major existing approaches characterizing motor at both behavioral and neural level. In particular, we critically review two long-standing paradigms used research-adaptation sequence learning. discuss extent which these can be considered models skill acquisition, defined as incremental improvement ability rapidly select then precisely execute appropriate actions, conclude that they fall short doing so. classes emerging research paradigms-learning arbitrary visuomotor mappings de novo movements with improved acuity-that more effectively address acquisition skill. Future work will needed determine degree laboratory-based studies skill, described this review, relate true expertise, is likely dependent on effects practice multiple processes go beyond traditional sensorimotor architecture. © 2019 American Physiological Society. Compr Physiol 9:613-663, 2019.

Language: Английский

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Learning and transfer of complex motor skills in virtual reality: a perspective review

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2019, Volume and Issue: 16(1)

Published: Oct. 18, 2019

Abstract The development of more effective rehabilitative interventions requires a better understanding how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for target. While these tasks facilitate stringent hypothesis testing laboratory settings, the results may not shed light performance complex skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms evaluate without sacrificing control. Specifically, VEs use models real-life afford controlled manipulations measure guide behavior with precision exceeds capabilities physical environments. This paper reviews recent insights VE into two pressing challenges rehabilitation research: 1) Which training strategies learning? 2) How can real be enhanced? Defining having nested redundancies, outline findings role movement variability acquisition discuss provide forms guidance enhance learning. We review typically developing neurologically-impaired populations view differences sensory-motor information influence strategies. actionable suggestions practicing broad areas where research is required. Finally, conclude present distinctive understand should enable therapeutic practice world.

Language: Английский

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It's not (only) the mean that matters: variability, noise and exploration in skill learning

Current Opinion in Behavioral Sciences, Journal Year: 2018, Volume and Issue: 20, P. 183 - 195

Published: March 1, 2018

Language: Английский

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Balancing exploration and exploitation with information and randomization

Current Opinion in Behavioral Sciences, Journal Year: 2020, Volume and Issue: 38, P. 49 - 56

Published: Nov. 6, 2020

Language: Английский

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The neural mechanisms of manual dexterity

Nature reviews. Neuroscience, Journal Year: 2021, Volume and Issue: 22(12), P. 741 - 757

Published: Oct. 28, 2021

Language: Английский

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Opportunities and challenges in the development of exoskeletons for locomotor assistance

Nature Biomedical Engineering, Journal Year: 2022, Volume and Issue: 7(4), P. 456 - 472

Published: Dec. 22, 2022

Language: Английский

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Vagus nerve stimulation drives selective circuit modulation through cholinergic reinforcement

Neuron, Journal Year: 2022, Volume and Issue: 110(17), P. 2867 - 2885.e7

Published: July 19, 2022

Language: Английский

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Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(8), P. 1581 - 1598

Published: May 29, 2024

Abstract Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, causal contribution of specific patterns oscillatory activity within human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep stimulation technique called transcranial temporal interference (tTIS) during reinforcement learning with concurrent neuroimaging, in randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, not 20 abolished benefits on learning. This effect was related to selective modulation neural striatum. Moreover, increased neuromodulatory influence frontal areas involved These results show that non-invasively and selectively modulate striatal mechanism expanding our tools for study relationships between structures behaviour.

Language: Английский

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Large-scale citizen science reveals predictors of sensorimotor adaptation

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(3), P. 510 - 525

Published: Jan. 30, 2024

Language: Английский

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A Basal Ganglia Circuit Sufficient to Guide Birdsong Learning

Neuron, Journal Year: 2018, Volume and Issue: 98(1), P. 208 - 221.e5

Published: March 15, 2018

Language: Английский

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