Neuroplasticity subserving motor skill learning

By Eran Dayan, Leonardo G. Cohen. 2011

1,306 citations recorded by the source corpus.

Summary Recent years have seen significant progress in our understanding of the neural substrates of motor skill learning. Advances in neuroimaging provide new insight into functional reorganization associated with the acquisition, consolidation and retention of motor skills. Plastic changes involving structural reorganization in gray and white matter architecture that occurs over shorter time periods than previously thought have been documented as well. Data from experimental animals provided crucial information on plausible cellular and molecular substrates contributing to large-scale reorganization underlying skill acquisition in humans. Here, we review findings demonstrating functional and structural plasticity across different spatial and temporal scales that mediate motor skill learning, while identifying converging areas of interest, and possible avenues for future research.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Statistics and Probability

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Citations in the corpus

Weight Agnostic Neural Networks (2019, background): “For humans it is evident, especially during early childhood [46, 107], that we learn skills and form memories by forming new synaptic connections, and our brain rewires itself based on our new experiences [5, 11, 18, 50].”
Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation (2015, background): “Prior research has divided motor learning into an early phase, associated with the establishment of gross kinematic patterns and rapid gains in motor performance, and a later phase, associated more strongly with subtle refinements of kinematic patterns and more incremental changes in skill acquisiti”
A quantitative meta-analysis and review of motor learning in the human brain (2013, result): “Thus, the results of the present study do not allow us to test the proposal that brain structures will contribute differentially to motor learning over time (see Danielle et al., 2011; Dayan and Cohen, 2011; Grafton et al., 1995, 2002; Hikosaka et al., 2002).”
Real-time fMRI neurofeedback: Progress and challenges (2013, background): “…M anuscript A uthor M anuscript A uthor M anuscript A uthor M anuscript above, with the greater involvement of information representation in the learning process with greater complexity of self-regulation, a hypothesis that could be investigated with future rtfMRI studies (Dayan and Cohen, 2011).”
Task-Based Core-Periphery Organization of Human Brain Dynamics (2012, background): “A negative value of k indicates a decrease in MT, which is thought to indicate that learning is occurring [74,75].”