Biology subjects

Schoch, S. F.

Publications and source records attributed to Schoch, S. F..

7 recordsLinked to original sources

bioRxiv2026

How Awakenings Shape Dream Recall: A Multilevel Study

Dream recall varies substantially both between individuals and from night to night within the same individual. Although nocturnal awakenings are thought to facilitate the encoding and later retrieval of dream experiences, it remains unclear whether dream recall is shaped primarily by awakening frequency or by more specific awakening characteristics, including duration, sleep stage, and timing within the night. Here, we analyzed two cohorts: cohort 1 consisted of 708 adults spanning the full range of dream recall frequency, assessed across three waves with home sleep recordings and questionnaire-based dream recall frequency measures; cohort 2 consisted of 124 adults with high dream recall frequency, assessed across multiple nights with home sleep recordings and daily dream reports. Using multilevel models with within-between decomposition, we examined trait-like and state-like associations between awakening measures and dream recall outcomes. At the trait level, both questionnaire-based dream recall frequency in cohort 1 and daily dream recall (i.e., a sense of having dreamed) in cohort 2 were associated with a specific nocturnal awakening profile: more habitual long REM awakenings and short NREM awakenings, with REM awakening effects remaining robust after adjustment for sleep duration. At the state level, in cohort 2, nights with more short and medium REM awakenings than usual increased the likelihood of morning dream recall, whereas nights with more long REM awakenings than usual increased the likelihood of morning dream content recall (i.e., remembering dream content). These findings support the arousal-retrieval and functional state-shift models, while highlighting important nuances in the associations between nocturnal awakenings and different dream recall outcomes.

neuroscience↗

bioRxiv2025

Simultaneous stomach-brain electrophysiology reveals dynamic coupling in human sleep

Sleep involves coordinated interactions between the brain and body, yet whether and how peripheral physiology is organized during human sleep is poorly understood. Because gastric rhythms are strongly modulated by arousal states during wakefulness, we hypothesized that gastric electrical rhythms exhibit structured dynamics aligned with cortical oscillations during sleep. Using simultaneous high-density electroencephalography and electrogastrography, we find that gastric activity persists throughout sleep, increases during non-rapid eye movement (NREM), and exhibits infraslow fluctuations that are amplified during NREM. Moreover, gastric activity is synchronized with slow oscillations and sleep spindles, with gastric power tracking spindle occurrence and cortical infraslow cycles. Stomach-brain coupling predicted next-day memory recall beyond cortical measures, whereas gastric infraslow dynamics predicted subjective sleep quality beyond polysomnographic measures. Together, our findings show that even as the brain disconnects from the external world, it maintains structured communication with peripheral organs, reframing sleep as a coordinated, multi-organ physiological state.

neuroscience↗

bioRxiv2025

Charting infant sleep cycle development using actigraphy: Longitudinal evidence for cycle lengthening within the first year of life from 35,000 hours of sleep

Sleep is marked by ultradian cycles, coinciding with the alternation of rapid eye movement (REM) and non-rapid eye movement sleep (NREM). These sleep cycles are a striking feature exhibited from infancy through adulthood, yet their underlying mechanisms and functional relevance remain elusive, calling for large-scale longitudinal studies. Here we leverage Locomotor Inactivity During Sleep (LIDS), previously established in adults as an accessible means to track sleep cycles, to chart ultradian sleep cycle dynamics within the first year of life at scale. Specifically, we analyzed > 35, 000 hours of sleep from a longitudinal dataset of 152 infants with 10 days of actigraphy at 3, 6, and 12 months of age. Using advanced signal processing techniques, we demonstrate the existence of rhythmic patterns in LIDS in infants with a cycle length of[~] 60 minutes. Cycles were not only shorter in infants than parents (- 11.8 min, 95% C.I. [- 13.8, - 9.8]) but also increased by[~] 10 min from 3 to 12 months of age, mirroring previous results in smaller samples for NREM-REM sleep cycles. This increase was found to be partially mediated by an increase in sleep bout duration with age (+1.0 min/h, [+0.9, +1.2]). Longer cycles were also found in infants still breastfed at 12 months (+2.5 min [+0.4, +4.5]) and their breastfeeding mothers (+6.7 min [+0.5, +12.9]). We also explored variations in non-rhythmic LIDS patterns in relation to endogenous and exogenous factors. Overall, our results provide evidence of a link between rhythmic patterns in limb inactivity and sleep cycles in infancy, underscoring the potential of studying these in large-scale population cohorts for developmental and health outcomes.

physiology↗

bioRxiv2025

Tracing infant sleep neurophysiology longitudinally from 3 to 6 months: EEG insights into brain development

1.Sleep is critical for brain plasticity during early development, yet the individual maturation of sleep neurophysiology in infancy remains poorly characterized. In particular, slow wave activity (SWA) has emerged as a key marker of both cortical maturation and experience-dependent plasticity. Understanding the regional dynamics of sleep neurophysiology early in life could yield critical insights into neurodevelopmental health. We conducted a longitudinal high-density EEG study in 11 healthy infants (3-6 months) assessing non-rapid eye movement (NREM) sleep. We analyzed the maturation of SWA (0.75-4.25 Hz), theta power (4.5-7.5 Hz), and sigma power (9.75-14.75 Hz) across scalp regions and examined their association with behavioral development. From 3 to 6 months, SWA increased maximally in occipital regions, while theta power exhibited a global increase. Sigma power, initially concentrated centrally, dispersed towards frontal regions. Greater power increases over frontal regions correlated with higher motor (theta) and personal-social skill scores (sigma) at 6 months. These findings establish a framework for typical infant sleep EEG maturation, highlighting frequency-specific and regionally distinct developmental patterns. This study provides the first longitudinal evidence that early changes in sleep EEG topography reflect individual developmental trajectories, supporting its utility as a non-invasive and yet precise biomarker for early identification of atypical neurodevelopment at preverbal ages.

neuroscience↗

bioRxiv2021

An Infant Sleep Electroencephalographic Marker of Thalamocortical Connectivity Predicts Behavioral Outcome in Late Infancy

Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, spindle density in central and frontocentral regions at age 6 months predicts later behavioral outcomes at 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict behavioral development. Our results propose spindle density as an early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are complemented by our companion paper that demonstrates the linkage of spindle density to infant nighttime movement, framing the possible role of spindles in sensorimotor microcircuitry development. Together, our studies suggest that early sleep habits, thalamocortical maturation, and behavioral outcome are closely interwoven. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk. HighlightsO_LISlow waves and spindles occur in a temporally coupled manner in infancy C_LIO_LISlow wave slope, spindle density, and slow wave-spindle coupling are not related to concurrent behavioral development C_LIO_LISpindle density at 6 months predicts behavioral status at 12 and 24 months C_LIO_LISlow wave slope and slow wave-spindle coupling are not predictive of behavioral development C_LI

neuroscience↗

bioRxiv2021

Bedtime to the brain: How infants sleep habits intertwine with sleep neurophysiology

Adequate sleep is critical for development and facilitates the maturation of the neurophysiological circuitries at the basis of cognitive and behavioral function. Observational research has associated sleep problems in early life with worse later cognitive, psychosocial, and somatic health outcomes. Yet, the extent to which day-to-day sleep habits in early life relate to neurophysiology - acutely and long-term - remains to be explored. Here, we report that sleep habits in 32 healthy 6-month-olds assessed with actimetry are linked to fundamental aspects of their neurophysiology measured with high-density electroencephalography (hdEEG). Our study reveals four key findings: First, daytime sleep habits are linked to EEG slow wave activity (SWA). Second, habits of nighttime movement and awakenings from sleep are connected with spindle density. Third, habitual sleep timing is linked to neurophysiological connectivity quantified as Delta-coherence. And lastly, Delta-coherence at age 6 months predicts nighttime sleep duration at age 12 months. These novel findings widen our understanding that infants sleep habits are closely intertwined with three particular levels of neurophysiology: sleep pressure (determined by SWA), the maturation of the thalamocortical system (spindles), and the maturation of cortical connectivity (coherence). Our companion paper complements this insight in the perspective of later developmental outcomes: early thalamocortical connectivity (spindle density) at age 6 months predicts later behavioural status at 12 and 24 months. The crucial next step is to extend this concept to clinical groups to objectively characterize infants sleep habits "at risk" that foster later neurodevelopmental problems. HighlightsO_LIInfants habitual sleep behavior (actimetry) is linked with their sleep neurophysiology (EEG) C_LIO_LIHabits of daytime sleeping (naps) are related to slow wave activity C_LIO_LIInfants movements and awakenings at nighttime are linked to their sleep spindles C_LIO_LISleep timing (infants bedtimes) is associated with cortical connectivity in the EEG C_LI

neuroscience↗

bioRxiv2020

Which are the central aspects of infant sleep? Thedynamic of sleep composites across infancy

Sleep is ubiquitous during infancy and important for the well-being of both infant and parent. Therefore, there is large interest to characterize infant sleep with reliable tools, for example by means of combining actigraphy with 24-h-diaries. However, it is critical to select the right variables to characterize sleep. With a principal component analysis, we identified 5 underlying sleep composites from 48 commonly used sleep variables: Sleep Night, Sleep Day, Sleep Activity, Sleep Timing and Sleep Variability. These composites accurately reflect the known changes of sleep throughout infancy as Sleep Day (representing naps), Sleep Activity (representing sleep efficiency and consolidation) and Sleep Variability (representing day-to-day stability) decrease across infancy, while Sleep Night (representing nighttime sleep) slightly increases and Sleep Timing becomes earlier with increasing age. Additionally, we uncover interesting dynamics between the sleep composites and demonstrate that infant sleep is not only highly variable between infants but also considerably dynamic within infants across time. Interestingly, Sleep Day is associated with behavioral development and therefore a potential marker for maturation. We recommend the use of sleep composites or of those specific single variables, which are solid representatives of the sleep composites for more reliable research.

neuroscience↗