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.

Paradoxically, some individuals who experience pathological worry also have good capacity for top-down control over their thoughts. Why such individuals would nevertheless worry excessively remains unclear. One explanation is suggested by research showing that those experiencing pathological worry are set apart from healthy controls by their beliefs that worry has utility and that effective worrying requires them to consider all possibilities before terminating a worry bout. This suggests that worriers with good capacity for cognitive control may engage in prolonged worry because they believe it is adaptive to do so. In a sample of 109 college students, among whom individuals reporting pathological worry were overrepresented, we tested this hypothesis using an objective index of top-down control capacity (i.e., resting vagally mediated heart rate variability [vmHRV]) and self-report measures of beliefs about worry and generalized anxiety disorder (GAD) symptom severity/status. As predicted, GAD symptom severity and vmHRV interacted to predict beliefs about worry. Specifically, high GAD symptoms were most strongly associated with beliefs that worry has utility at higher levels of vmHRV. Furthermore, this pattern was mostly a function of the belief that worry serves to distract the worrier from more emotional things. Similarly, high GAD symptoms were most strongly associated with endorsement of an ‘as many as can’ (AMAC) problem-solving rule when vmHRV was high . From the opposite perspective, both worry utility beliefs and AMAC rule endorsement were associated with the highest GAD symptom severity at higher levels of vmHRV. This was also true for the belief that worry distracts from more emotional things predicting analog GAD status. These results suggest that worriers who have higher levels of top-down control capacity may initiate and persist in worry, at least initially, because they value it. However, why they nevertheless rate their worry as excessive and uncontrollable is an important question for future research.

Study ObjectivesSlow 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. MethodsCoupling 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. ResultsTwo 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 are composed of two 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 during old age. ConclusionsDistinct 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. Statement of SignificanceSlow waves of nonrapid eye movement sleep couple with sleep spindles in a process hypothesized to support memory functions. This coupling has recently gained interest as a possible biomarker of cognitive aging and onset of Alzheimer's disease. Most studies have been limited by an assumption that all slow waves (and coupled spindles) are fundamentally the same physiological events. Here we demonstrate that distinct subtypes of slow waves and their coupled spindles can be identified in human sleep. A mixture of different slow wave and spindle subtypes shifts in composition during lighter versus deeper sleep, and aging favors the deep sleep subtypes. These data should inform any future attempts to use slow wave sleep as a biomarker or clinical interventional target. Background: Slow waves occur during stages N2 and N3 Non-Rapid Eye Movement (NREM) sleep and are associated with large-scale synchronization of neuronal populations. 1-3 Spindlesare generated and propagated via cortical-thalamic loops, with timing input from the reticular nucleus of the thalamus. 4,5 In the process of aging, loss of slow waves and sleep spindles is highly correlated with cognitive decline, and abnormal slow wave neuronal circuitry is implicated in the pathogenesis of Alzheimer's disease 6 .