The effect of interference, offline sleep, and wake on spatial statistical learning

Elsevier

Available online 7 June 2022, 107650

Neurobiology of Learning and MemoryHighlights•

Sleep does not benefit spatial statistical learning when learning occurs in a low interference condition.

Spatial statistical learning may be vulnerable to interference when two visuospatial configurations are trained in close temporal succession.

An offline period of active wake or rapid eye movement sleep, but not quiet wake or non-rapid eye movement sleep alone, may help protect or recover learning disrupted by interference.

Abstract

Statistical learning, the ability of the human brain to uncover patterns organized according to probabilistic relationships between elements and events of the environment, is a powerful learning mechanism underlying many cognitive processes. Here we examined how memory for statistical learning of probabilistic spatial configurations is impacted by interference at the time of initial exposure and varying degrees of wakefulness and sleep during subsequent offline processing. We manipulated levels of interference at learning by varying the time between exposures of different spatial configurations. During the subsequent offline period, participants either remained awake (active wake or quiet wake) or took a nap comprised of either non-rapid eye movement (NREM) sleep only or NREM and rapid eye movement (REM) sleep. Recognition of the trained spatial configurations, as well as a novel configuration exposed after the offline period, was tested approximately 6-7 hours after initial exposure. We found that the sleep conditions did not provide any additional memory benefit compared to wakefulness for spatial statistical learning with low interference. For high interference, we found some evidence that memory may be impaired following quiet wake and NREM sleep only, but not active wake or combined NREM and REM sleep. These results indicate that learning conditions may interact with offline brain states to influence the long-term retention of spatial statistical learning.

Keywords

memory consolidation

statistical learning

interference

REM sleep

napping

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© 2022 Published by Elsevier Inc.

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