Journal of Cognitive NeuroscienceNeurosciencePeer-reviewed journal article
Timing between cortical slow oscillations and heart rate bursts during sleep predicts perceptual speed, but not offline consolidation
Mohsen NajiiD, Giri P. KrishnaniD, Elizabeth Ann McDevittiD, Maxim BazhenoviD, Sara Carole MednickiD
Abstract
Central and autonomic nervous system activity are coupled during sleep. Cortical slow oscillations (SOs, <1Hz) coincide with brief bursts in heart rate (HR), but the functional consequence of this coupling in cognition remains elusive. We measured SO-HR temporal coupling (i.e., the peak-to-peak interval between downstate of SO event and HR burst) during a daytime nap, and asked whether this SO-HR timing measure was associated with perceptual speed and learning on a texture discrimination task, by testing subjects before and after a nap. The coherence of SO-HR events during sleep strongly correlated with an individuals perceptual speed in the morning and evening test sessions, but not with their change in performance after the nap (i.e., consolidation). We confirmed this result in two additional experimental visits, and also discovered that this association was visit-specific, indicating a reliable state (not trait) marker. Thus, we introduce a novel physiological index that may be a useful marker of state-dependent processing speed of an individual.\n\nSignificance StatementStudies show that autonomic and central nervous system activity is coupled. For example, increases in heart rate follow cortical slow oscillations during sleep. However, the functional significance of this coupling for cognition is not understood. In three experimental visits, we show that the timing between these sleep events (the peak-to-peak delay between the slow oscillation and the heart rate burst) is highly correlated with waking perceptual processing speed. This reliable individual difference measure may be a useful marker of generalized processing speed.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 13
- FWCI
- 1.02
- Field percentile
- top 26%
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