The aging slow wave: a shifting amalgam of distinct slow wave and spindle coupling subtypes define slow wave sleep across the human lifespan

Abstract

Study Objectives Slow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. Methods Coupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. Results Two different subtypes of spindles were identified during the upstates of (distinct) slow waves: an “early-fast” spindle, more common in stage N2 sleep, and a “late-fast” spindle, more common in stage N3. We further found stages N2 and N3 sleep contain a mixture of discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails with increasing age. Conclusions Distinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease.

The Rise and Fall of Slow Wave Tides: Vacillations of Slow Wave/Spindle Coupling Shift the Composition of Slow Wave Activity Through Sleep Cycles in Accordance with Depth of Sleep

“…In addition, our results demonstrate that the event composition of SWA is quantitatively distinct between stages N2 and N3 sleep, with deeper sleep favoring a higher percentage of late-fast slow wave/spindle events. This is consistent with our prior observations that demonstrate the normalized EEG power differs in the late fast versus early fast ROI regions within slow wave/spindle events 20 , and suggests that the differences in EEG power may be, at least in part, attributable to differences in the number of each slow wave/spindle subtype that creates each sleep stage’s SWA composite.…”

“…Aging has been linked to changes in slow wave/spindle coupling 26,35 , and indeed, the continuum of the adult human lifespan demonstrates a shift in the composition of coupled spindle EEG power towards the late-fast subtype 20 . The results of this study support a conceptual model of a drift in the types of slow wave/spindle events that older adults produce, and a striking increase in the number of time periods that cycle disproportionately into late-fast spindle domination of SWA.…”

“…Slow waves were identified via automated zero-crossing detection as described in McConnell et al 20 Briefly, signals for slow wave detection were utilized from electrodes FP1, CZ, and C3 from stages N2 and N3 of slow wave sleep by AASM criteria. 34 Channels FP1 and CZ were selected for their relatively close positions to slow wave sources described in localization experiments, which demonstrated a frontal source near the left insula and a central source near the cingulate gyrus 13 .…”

“…Time-frequency wavelet plots of coupled spindles were created via established methods. 20,35,36 Troughs of each slow wave were centered in 5-second intervals of EEG data and matched to 5-second baseline intervals immediately preceding slow wave events (excluding baseline segments containing slow wave events). Morlet-wavelet transformation (8 cycles) was applied to the unfiltered EEG for slow wave and baseline segments between 4 Hz and 20 Hz in steps of 0.25Hz.…”

“…Individuals from CFS were selected from ages 18-35 for young adults (n=30; median age 24.19 (21.78-25.48 IQR)) and 60-70 for older adults (n=30; median age 65 (62.09-68.13 IQR)), given prior data indicating that these age ranges differ in slow wave/spindle coupling. 20 To minimize possible effects of sleep apnea, we selected 60 participants within the CFS by lowest oxygen desaturation apneas and hypopneas >= 3% oxygen desaturation or arousal per hour of sleep (AHI) scores within each age desired range (median AHI for young adults - 0.21 (0.15-0.50 IQR)); median AHI for older adults = 4.51 (2.80-9.15 IQR); Table 1).…”