Motor Skill Learning

Seidler, Rachael D.; Benson, Bryan L.; Boyden, Nathaniel B; Kwak, Youngbin

doi:10.1093/oxfordhb/9780199988693.013.0020

Cited by 3 publications

(1 citation statement)

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“…In healthy control (HC) individuals, practice-related learning typically follows a characteristic staged process: early, rapid, and effortful learning engaging widespread cortical–subcortical areas with a later shift to more automatic processes and a reduced number of prefrontal regions (4, 5, 9–13). This process is characteristic of both motor skill and cognitive skill-based learning where ongoing practice leads to incremental learning of associations.…”

Section: Introductionmentioning

confidence: 99%

Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia

2017

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BackgroundUnderstanding how practice mediates the transition of brain–behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ).MethodsParticipants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings.ResultsWith practice, HC participants transitioned to a brain–accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions.ConclusionThere is a different spatiotemporal unfolding of brain–learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, “higher level” cognition.

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