 The Decay of Motor Memories Is Independent of Context Change DetectionAndrew E Brennan and Maurice A Smith PLOS Computational Biology, 2015, vol. 11, issue 6, 1-31 Abstract: When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected; and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection.Author Summary: Suppose you are asked to shoot free throws with a basketball. If you’re an unskilled shooter, you may at first miss in a consistent way for consecutive shots—perhaps a bit to the right—but you will soon learn to correct that error. However, an often-repeated finding is that if error information is withheld, such as if you close your eyes just after releasing the ball, performance will regress toward baseline. One explanation is that newly-formed motor memories are intrinsically volatile, decaying away if there is no continued performance feedback. However, recent work proposed an alternative mechanism: that newly-formed motor memories are intrinsically stable, but people change their behavior upon detecting a context change. This hypothesis predicts decay will occur only after the change is detected, leading to delayed decay if the context change is purposefully masked in an experiment. We show that previous estimates of decay onset delay, which provided support for the context-dependent decay hypothesis, were systematically biased and that decay instead begins immediately, without delay, even when context changes are effectively masked, in stark contrast to the 40+ trial delays previously reported. Thus, we show that recent memories decay independently of context change detection, suggesting that they are indeed intrinsically volatile. Date: 2015 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1004278 DOI: 10.1371/journal.pcbi.1004278 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.