4.4 Article

Changing brain networks for visuomotor control with increased movement automaticity

Journal

JOURNAL OF NEUROPHYSIOLOGY
Volume 92, Issue 4, Pages 2405-2412

Publisher

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.01092.2003

Keywords

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Funding

  1. Medical Research Council [G9901399, G9409531] Funding Source: Medline
  2. Medical Research Council [G9409531, G9901399] Funding Source: researchfish
  3. MRC [G9901399, G9409531] Funding Source: UKRI

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Learning a motor skill is associated with changes in patterns of brain activation with movement. Here we have further characterized these dynamics during fast (short-term) learning of a visuomotor skill using functional magnetic resonance imaging. Subjects (n=15) were studied as they learned to visually track a moving target by varying the isometric force applied to a pressure plate held in the right hand. Learning was confirmed by demonstration of improved performance and automaticity (the relative lack of need for conscious attention during task execution). We identified two distinct, time-dependent patterns of functional changes in the brain associated with these behavioral changes. An initial, more attentionally demanding stage of learning was associated with the greatest relative activity in widely distributed, predominantly cortical regions including prefrontal, bilateral sensorimotor, and parietal cortices. The caudate nucleus and ipsilateral cerebellar hemisphere also showed significant activity. Over time, as performance improved, activity in these regions progressively decreased. There was an increase in activity in subcortical motor regions including that of the cerebellar dentate and the thalamus and putamen. Short-term motor-skill learning thus is associated with a progressive reduction of widely distributed activations in cortical regions responsible for executive functions, processing somatosensory feedback and motor planning. The results suggest that early performance gains rely strongly on prefrontal-caudate interactions with later increased activity in a subcortical circuit involving the cerebellum and basal ganglia as the task becomes more automatic. Characterization of these changes provides a potential tool for functional dissection of pathologies of movement and motor learning.

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