The Rise and Fall of Slow Wave Tides: Vacillations in Coupled Slow Wave/Spindle Pairing Shift the Composition of Slow Wave Activity in Accordance With Depth of Sleep

Abstract

Slow wave activity (SWA) during sleep is associated with synaptic regulation and memory processing functions. Each cycle of non-rapid-eye-movement (NREM) sleep demonstrates a waxing and waning amount of SWA during the transitions between stages N2 and N3 sleep, and the deeper N3 sleep is associated with an increased density of SWA. Further, SWA is an amalgam of different types of slow waves, each identifiable by their temporal coupling to spindle subtypes with distinct physiological features. The objectives of this study were to better understand the neurobiological properties that distinguish different slow wave and spindle subtypes, and to examine the composition of SWA across cycles of NREM sleep. We further sought to explore changes in the composition of NREM cycles that occur among aging adults. To address these goals, we analyzed subsets of data from two well-characterized cohorts of healthy adults: (1) The DREAMS Subjects Database (n = 20), and (2) The Cleveland Family Study (n = 60). Our analyses indicate that slow wave/spindle coupled events can be characterized as frontal vs. central in their relative distribution between electroencephalography (EEG) channels. The frontal predominant slow waves are identifiable by their coupling to late-fast spindles and occur more frequently during stage N3 sleep. Conversely, the central-associated slow waves are identified by coupling to early-fast spindles and favor occurrence during stage N2 sleep. Together, both types of slow wave/spindle coupled events form the composite of SWA, and their relative contribution to the SWA rises and falls across cycles of NREM sleep in accordance with depth of sleep. Exploratory analyses indicated that older adults produce a different composition of SWA, with a shift toward the N3, frontal subtype, which becomes increasingly predominant during cycles of NREM sleep. Overall, these data demonstrate that subtypes of slow wave/spindle events have distinct cortical propagation patterns and differ in their distribution across lighter vs. deeper NREM sleep. Future efforts to understand how slow wave sleep and slow wave/spindle coupling impact memory performance and neurological disease may benefit from examining the composition of SWA to avoid potential confounds that may occur when comparing dissimilar neurophysiological events.

“Deep Sleep”: A Comparative Approach to Defining Meaningful Rest

“…These qualities are seemingly not associated with only one sleep state, and furthermore, there is emerging evidence that other biophysical processes, subjective measures, or longterm outcomes are critical to determining when sleep was, in fact, deep. The arbitrary definitions of "deep sleep" also fail to adjust for context: developmental and aging timelines that make it difficult to apply across individuals (McConnell et al, 2022) and clearly there are differences between the slow-wave states induced by anesthesia or even waking tasks (Kirmizi-Alsan et al, 2006) than those that naturally arise in the late NREM period.…”

Mapping Sleep’s Oscillatory Events as a Biomarker of Alzheimer’s Disease

“…5,6 Briefly, EEG data was detrended and bandpass filtered in a forward and backward direction using a 3rd-order Butterworth filter between 10-13.5 Hz for late-fast spindles and 4-8 Hz for theta bursts. Note that early-fast spindles are more prominent in central recording locations 5 and were not consistently detected in the FP1-FP2 channel, and therefore were excluded from analysis. Maximum spindle envelopes were calculated and an amplitude threshold of 75% percentile of the root mean squared value with a length window of 0.5 sec to 3.0 sec was used to define spindle events and theta bursts.…”

“…Time-frequency wavelet spectrograms of slow wave-coupled spindles and theta bursts were created via established methods. 5,6 Briefly, 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). A Morlet-wavelet transformation (65 cycles from 4 Hz to 10 Hz) was applied to the unfiltered EEG for slow wave and baseline segments between 4 Hz and 20 Hz in steps of 0.25 Hz with varying wave numbers (65 cycles from 4 Hz to 10Hz with a step size of 0.0938 to match the frequency step size).…”

“…Sleep dysfunction is hypothesized to share a bidirectional relationship with Alzheimer's disease (AD) pathology 1,2 , and there is growing interest in understanding the neurophysiological properties of sleep that are most strongly associated with neurodegeneration. Among many putative neuroprotective attributes of sleep, slow wave activity (SWA) stands out for both the robust data supporting plausible neuroprotective mechanisms 2,3 , and the readily quantified SWA metrics that can be obtained from widely available single-channel electroencephalography (EEG) [4][5][6] . Loss of SWA correlates with age [7][8][9][10][11] and neurodegenerative processes including Alzheimer's and Parkinson's disease 2,12 .…”

“…Theta burst events are detectable prior to the troughs of SWs 5,6,25,26,37 and play a role in normal sleep-dependent memory processing 37,38 , although their relationships to SW subpopulations, and their potential changes in aging and neurodegenerative processes, have yet to be formally assessed.…”