An implicit memory of errors limits human sensorimotor adaptation

• Published in: Nature human behaviour Vol. 5; no. 7; pp. 920 - 934
• Main Authors: Albert, Scott T., Jang, Jihoon, Sheahan, Hannah R., Teunissen, Lonneke, Vandevoorde, Koenraad, Herzfeld, David J., Shadmehr, Reza
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-07-2021; Nature Publishing Group
• Subjects: 631/378/1595; 631/378/2632; Adaptation; Adaptation, Physiological; Adolescent; Adult; Behavioral Sciences; Biomedical and Life Sciences; Experimental Psychology; Experiments; Explicit learning; Female; Humans; Hypotheses; Implicit learning; Implicit memory; Learning; Learning Curve; Life Sciences; Male; Medical research; Memory; Memory - physiology; Microeconomics; Middle Aged; Motor Skills; Neurosciences; Personality and Social Psychology; Psychomotor Performance - physiology; Young Adult
• ISSN: 2397-3374; 2397-3374
• DOI: 10.1038/s41562-020-01036-x

During extended motor adaptation, learning appears to saturate despite persistence of residual errors. This adaptation limit is not fixed but varies with perturbation variance; when variance is high, residual errors become larger. These changes in total adaptation could relate to either implicit or explicit learning systems. Here, we found that when adaptation relied solely on the explicit system, residual errors disappeared and learning was unaltered by perturbation variability. In contrast, when learning depended entirely, or in part, on implicit learning, residual errors reappeared. Total implicit adaptation decreased in the high-variance environment due to changes in error sensitivity, not in forgetting. These observations suggest a model in which the implicit system becomes more sensitive to errors when they occur in a consistent direction. Thus, residual errors in motor adaptation are at least in part caused by an implicit learning system that modulates its error sensitivity in response to the consistency of past errors.
Human motor adaptation reaches an upper limit. Albert et al. report that this limit is linked to implicit learning. When perturbations are variable, the adaptation limit decreases as subconscious learning systems become less sensitive to error.