James Kozloski, Konstantinos Sfyrakis, et al.
IBM J. Res. Dev
Sleep after learning often enhances task performance, but the underlying mechanisms remain unclear. Using a well-characterized rotation learning paradigm implemented both behaviorally and in computer simulations, we compared two main hypotheses: the first, that off-line replay during sleep leads to further potentiation of synaptic circuits involved in learning; the second, that sleep enhances performance by uniformly downscaling synaptic strength. A simple computer model implemented synaptic changes associated with rotation adaptation (30°), yielding a reduction in mean directional error. Simulating further synaptic potentiation led to a further reduction of mean directional error, but not of directional variability. By contrast, simulating sleep-dependent synaptic renormalization by scaling down all synaptic weights by 15% decreased both mean directional error and variability. Two groups of subjects were tested after either two rotation adaptation training sessions or after a single training session followed by sleep. After two training sessions, mean direction error decreased, but directional variability remained high. However, subjects who slept after a single training session showed a reduction in both directional error and variability, consistent with a downscaling mechanism during sleep. © 2008 Elsevier Inc. All rights reserved.
James Kozloski, Konstantinos Sfyrakis, et al.
IBM J. Res. Dev
Umberto Olcese, Steve K. Esser, et al.
Journal of Neurophysiology
James S. Albus, George A. Bekey, et al.
Science