Complex sound processing during human REM sleep by recovering information from long-term memory as revealed by the mismatch negativity (MMN)

Abstract

Perceptual learning is thought to be the result of neural changes that take place over a period of several hours or days, allowing information to be transferred to long-term memory. Evidence suggests that contents of long-term memory may improve attentive and pre-attentive sensory processing. Therefore, it is plausible to hypothesize that learning-induced neural changes that develop during wakefulness could improve automatic information processing during human REM sleep. The MMN, an objective measure of the automatic change detection in auditory cortex, was used to evaluate long-term learning effects on pre-attentive processing during wakefulness and REM sleep. When subjects learned to discriminate two complex auditory patterns in wakefulness, an increase in the MMN was obtained in both wake and REM states. The automatic detection of the infrequent complex auditory pattern may therefore be improved in both brain states by reactivating information from long-term memory. These findings suggest that long-term learning-related neural changes are accessible during REM sleep as well.