Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance

• Published in: Journal of neurophysiology Vol. 111; no. 10; pp. 2084 - 2093
• Main Authors: Wong, Aaron L., Shelhamer, Mark
• Format: Journal Article
• Language: English
• Published: United States American Physiological Society 01.05.2014
• Subjects: Adaptation, Psychological; Biomechanical Phenomena; Eye Movement Measurements; Female; Humans; Male; Models, Psychological; Neuropsychological Tests; Psychomotor Performance; Regression Analysis; Saccades; Task Performance and Analysis; Time Factors; adaptation; error-correction mechanism; saccades; predictive saccades
• ISSN: 0022-3077; 1522-1598; 1522-1598
• DOI: 10.1152/jn.00779.2013

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation.