Brennan AE, Smith MA (2015) The Decay of Motor Memories Is Independent of Context Change Detection.
PLoS Computational Biology 11(6):e1004278. doi:10.1371/journal.pcbi.1004278.
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 grouplevel
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.
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