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Sensorimotor Learning: Neurocognitive Mechanisms and Individual Differences.

R D Seidler1, R G Carson2,3

  • 1University of Florida, P.O. Box 118205, Gainesville, FL, 32611-8205, USA. rachaelseidler@ufl.edu.

Journal of Neuroengineering and Rehabilitation
|July 15, 2017
PubMed
Summary
This summary is machine-generated.

Sensorimotor learning involves strategic brain networks and long-term neural changes. Individual differences in learning rates, influenced by genetics and behavior, are key to personalized rehabilitation.

Keywords:
AdaptationBANCOMGenetic predictorsGenotypeMotor learningSNP

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Area of Science:

  • Biomechanics and Neural Control of Movement
  • Neuroscience
  • Human Motor Performance

Background:

  • Sensorimotor learning research has expanded, recognizing roles for neural systems beyond primary motor pathways.
  • Strategic processes involving frontoparietal and anterior cingulate networks are crucial for sensorimotor adaptation.
  • Long-term training induces functional and morphological changes in motor and somatosensory cortices.

Purpose of the Study:

  • To provide an overview of findings on sensorimotor learning mechanisms presented at the 2016 BANCOM conference.
  • To highlight the growing importance of individual differences in understanding sensorimotor performance.
  • To advocate for the integration of genomic analyses into sensorimotor learning research.

Main Methods:

  • Review of findings and viewpoints from the 2016 Biomechanics and Neural Control of Movement conference.
  • Discussion of established knowledge regarding neural contributions to sensorimotor learning.
  • Exploration of emerging trends in predicting individual differences in learning rates.

Main Results:

  • Neural systems outside primary motor pathways, including frontoparietal and anterior cingulate networks, contribute significantly to learning.
  • Individual differences in learning rates are influenced by neural, behavioral, and genetic factors.
  • Genomic analyses offer potential for deeper understanding of cellular processes in human behavior and skill learning.

Conclusions:

  • Understanding individual differences in sensorimotor performance is crucial for advancing personalized medicine and refining rehabilitation strategies.
  • Integrating genomic approaches, despite challenges with sample sizes, can yield new insights into neural control.
  • Personalized approaches to rehabilitation are likely to be more effective than generalized treatments.