Neuroplasticity subserving motor skill learning

Abstract

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 occur 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 brain 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.

Copyright © 2011 Elsevier Inc. All rights reserved.

Figures

Figure 1. The different stages of motor skill learning

(A) Motor skill learning can be divided into stages: a fast/early stage where typically significant improvements can be seen within a single training session and a later slower stage where further gains are achieved across multiple sessions of practice. Skill can be retained after a single or multiple training sessions. (B) The relative duration of fast and slow learning is highly task specific. For example, the fast stage of learning an explicit sequence of key-press movements could last minutes, while the fast stage of learning to play a complex musical piece may last months. Although the shape of the learning curves for these two different tasks could theoretically be the same, the time bases of the fast stages of learning may be substantially different. (C) Performance improvements during skill acquisition can occur during training (online learning) but also in between sessions, with no further practice (offline learning).

Figure 2. Shifts in speed-accuracy response functions as a measure of skill

(A) Simulated learning curve, where performance improvements were defined in terms of speed. Thus, performance at time point t2, shows clear improvements relative to performance at time point t1. (B) Inspecting the task’s speed-accuracy response function reveals that these performance changes may reflect sampling of two points, along the same function, thus simply reflecting a switch from movements which are relatively slow but accurate to movements which are relatively fast but inaccurate. (C) A more reliable measure for skill acquisition may estimate whether learning was associated with a shift in the speed-accuracy responses, from the red to the blue function.

Figure 3. Neural substrates of fast motor skill learning

Schematic depiction of the major brain regions recruited during the initial stages of motor skill learning, as identified using fMRI and PET: dorsolateral prefrontal cortex (DLPFC), primary motor cortex (M1), premotor cortex (PM), supplementary motor area (SMA) and pre-supplementary motor area (preSMA), posterior parietal cortex (PPC), dorsomedial striatum (DMS) and posterior cerebellum. The arrows depict documented increases or decreases in activation associated with fast skill learning. Inflated cortical and cerebellar surfaces were rendered using CARET (http://brainmap.wustl.edu/caret).

Figure 4. Neural substrates of slow motor skill learning

Schematics of the major brain regions active in slow stages of motor skill learning, as identified using fMRI: primary motor cortex (M1), primary somatosensory cortex (S1) supplementary motor area (SMA), dorsolateral striatum (DLS) and lateral cerebellum. Arrows depict documented increases or decreases in activation. Inflated cortical and cerebellar surfaces were rendered using CARET (http://brainmap.wustl.edu/caret).