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REM and NREM sleep mentation.

Patrick Mcnamara, Patricia Johnson, Deirdre McLaren, Erica Harris, Catherine Beauharnais, Sanford Auerbach

International review of neurobiology 2010 DOI: 10.1016/s0074-7742(10)92004-7 (opens in new tab)

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AI-extracted from the abstract
Characteristics Review Peer reviewed
Keywords Humans Social behavior Mental processes Dreams Sleep, rem
Key findings The authors argue that REM and NREM sleep have distinct brain activation patterns that correspond to different dream content: REM dreams feature more dreamer-initiated aggressive social interactions, while NREM dreams feature more dreamer-initiated friendly interactions. They propose that both states simulate opposing types of social interactions, with REM specializing in aggression and NREM in friendliness, and they summarize evidence that dream content predicts daytime mood and social interactions.

Abstract

We review the literature on the neurobiology of rapid eye movement (REM) and non-rapid eye movement (NREM) sleep states and associated dreams. REM is associated with enhanced activation of limbic and amygdalar networks and decreased activation in dorsal prefrontal regions while stage II NREM is associated with greater cortical activation than REM. Not surprisingly, these disparate brain activation patterns tend to be associated with dramatically different dream phenomenologies and dream content. We present two recent studies which content-analyzed hundreds of dream reports from REM and NREM sleep states. These studies demonstrated that dreamer-initiated aggressive social interactions were more characteristic of REM than NREM, and dreamer-initiated friendliness was more characteristic of NREM than REM reports. Both REM and NREM dreams therefore may function to simulate opposing types of social interactions, with the REM state specializing in simulation of aggressive interactions and the NREM state specializing in simulation of friendly interactions. We close our review with a summary of evidence that dream content variables significantly predict daytime mood and social interactions.

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