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Strength of baseline inter-trial correlations forecasts adaptive capacity in the vestibulo-ocular reflex

Individual differences in sensorimotor adaptability may permit customized training protocols for optimum learning. Here, we sought to forecast individual adaptive capabilities in the vestibulo-ocular reflex (VOR). Subjects performed 400 head-rotation steps (400 trials) during a baseline test, follow...

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Detalles Bibliográficos
Autores principales: Beaton, Kara H., Wong, Aaron L., Lowen, Steven B., Shelhamer, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5381898/
https://www.ncbi.nlm.nih.gov/pubmed/28380076
http://dx.doi.org/10.1371/journal.pone.0174977
Descripción
Sumario:Individual differences in sensorimotor adaptability may permit customized training protocols for optimum learning. Here, we sought to forecast individual adaptive capabilities in the vestibulo-ocular reflex (VOR). Subjects performed 400 head-rotation steps (400 trials) during a baseline test, followed by 20 min of VOR gain adaptation. All subjects exhibited mean baseline VOR gain of approximately 1.0, variable from trial to trial, and showed desired reductions in gain following adaptation with variation in extent across individuals. The extent to which a given subject adapted was inversely proportional to a measure of the strength and duration of baseline inter-trial correlations (β). β is derived from the decay of the autocorrelation of the sequence of VOR gains, and describes how strongly correlated are past gain values; it thus indicates how much the VOR gain on any given trial is informed by performance on previous trials. To maximize the time that images are stabilized on the retina, the VOR should maintain a gain close to 1.0 that is adjusted predominantly according to the most recent error; hence, it is not surprising that individuals who exhibit smaller β (weaker inter-trial correlations) also exhibited the best adaptation. Our finding suggests that the temporal structure of baseline behavioral data contains important information that may aid in forecasting adaptive capacities. This has significant implications for the development of personalized physical therapy protocols for patients, and for other cases when it is necessary to adjust motor programs to maintain movement accuracy in response to pathological and environmental changes.