Biology subjects

Cross, N. E.

Publications and source records attributed to Cross, N. E..

4 recordsLinked to original sources

bioRxiv2025

Whole-night gentle rocking improves sleep in poor sleepers with insomnia complaints.

Specific brain oscillations can be manipulated during sleep to improve sleep quality and memory performance. We previously demonstrated that continuous rocking stimulation (0.25Hz, lateral movement) applied to good sleepers during sleep enhanced stable deep sleep, boosted NREM oscillations (spindles and slow waves), and memory consolidation. Here, we investigated whether nocturnal rocking could benefit individuals suffering from sleep difficulties. We recruited sixteen young adults with subjective difficulties initiating and/or maintaining sleep and who presented with objective poor sleep quality. Each participant spent two nights of sleep at the laboratory, one rocking and one stationary, during which we assessed sleep and declarative memory consolidation. We found that a whole night of gentle rocking in individuals with poor sleep decreased sleep fragmentation, time spent awake and in light sleep (N1), with an associated increase in objective sleep efficiency and subjective sleep quality. Additionally, we replicated the neural entrainment or synchronizing effect of the rocking motion, yielding a boost in NREM fast spindles and slow oscillations. Yet, these changes in sleep did not modulate overnight memory performance. By alleviating some difficulties encountered in this population of poor sleepers (e.g., sleep maintenance and poor self-reported sleep), these findings provide preliminary evidence that rocking may represent an alternative or complementary intervention for the management of some forms of chronic insomnia. STATEMENT OF SIGNIFICANCEHere, we demonstrate that a gentle and continuous rhythmic rocking stimulation applied during a whole night improves sleep in young adults with sleep complaints and objective poor sleep quality. Rocking, compared to a normal stationary condition, promoted sleep maintenance and sleep efficiency with a parallel improvement in subjective sleep quality. As we previously found in healthy controls, the rocking stimulation had a mechanistic influence over the synchronisation of sleep oscillations in these individuals with insomnia complaints. These findings may be relevant for the development of non-pharmacological interventions in similar populations with insomnia complaints and poor sleep, including older adults, and clinical populations with neurological, psychiatric, or somatic conditions.

neuroscience↗

bioRxiv2024

EEG source imaging technique to investigate sleep oscillations for simultaneous EEG-fMRI

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a widely used non-invasive neuroimaging technique in sleep studies. However, EEG data are strongly influenced by two types of MRI-related artefacts: gradient artefacts (GA) and ballistocardiogram artefacts (BCG). If artefacts correction is suboptimal, the BCG obscures the EEG signals below 20Hz and could make it difficult to investigate sleep oscillations, especially sleep spindles, sleep specific oscillations occurring within 11-16Hz frequency band. We previously demonstrated the utility of beamforming spatial filtering in correcting MRI-related artefacts on EEG. Here, we investigated the use of beamforming spatial filtering for improving the detection of EEG oscillations during sleep, in particular, 1) to accurately estimate single-event spindle EEG power changes, and 2) to demonstrate the potential improvement of fMRI general linear model (GLM) analysis when involving such additional EEG information. We analysed EEG-fMRI data acquired during a recovery nap after sleep deprivation in 20 young healthy participants (12 females, 8 males, age = 21.3 {+/-} 2.5 years). Based on spindle events (onset and duration) detected by trained sleep scorers on BCG corrected EEG signals through a conventional average artefact subtraction (AAS) method, we compared four different EEG processing steps: non-BCG corrected; AAS BCG corrected; beamforming BCG corrected; beamforming+AAS BCG corrected. These processing steps consist of non-BCG corrected and AAS BCG corrected considered either at the sensor level or at the source-level (after beamformer localization) to evaluate the impact of the BCG artefact on the detection of spindle activity. Then we further investigated four different fMRI GLM approaches using 1) the spindle onset and duration (GLM1), 2) spindle onset, duration, and parametric modulation of single-spindle power change from the Cz electrode of the AAS BCG corrected data (GLM2), 3) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming+AAS BCG corrected (GLM3) and 4) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming BCG corrected data (GLM4). We found that the beamforming approach did not only attenuate the BCG artefacts, but also recovered sleep spindle activity occurring during NREM sleep. Furthermore, this beamforming approach allowed us to accurately estimate single-event power change of each spindle in the source space when compared to the channel level analysis, and therefore to further improve the specificity of fMRI GLM analysis, better localizing the recruited brain regions during spindles. Our findings show the benefit of applying beamforming source imaging technique to EEG-fMRI acquired during sleep. We demonstrate that this approach would be beneficial especially for long EEG-fMRI data acquisitions (i.e., sleep, resting-state), when the BCG correction becomes problematic due to inherent dynamic changes of heart rates. Our findings extend previous work regarding the application of the source imaging to the sleep EEG-fMRI. Combining with this advanced methodology and analysis, sleep EEG-fMRI will help us better understand the functional roles of human sleep.

neuroscience↗

bioRxiv2024

A multidimensional investigation of sleep and biopsychosocial profiles with associated neural signatures

Sleep is essential for optimal functioning and health. Interconnected to multiple biological, psychological and socio-environmental factors (i.e., biopsychosocial factors), the multidimensional nature of sleep is rarely capitalized on in research. Here, we deployed a data-driven approach to identify sleep-biopsychosocial profiles that linked self-reported sleep patterns to inter-individual variability in health, cognition, and lifestyle factors in 770 healthy young adults. We uncovered five profiles, including two profiles reflecting general psychopathology associated with either reports of general poor sleep or an absence of sleep complaints (i.e., sleep resilience) respectively. The three other profiles were driven by the use of sleep aids and social satisfaction, sleep duration and cognitive performance, and sleep disturbance linked to cognition and mental health. Furthermore, identified sleep-biopsychosocial profiles displayed unique patterns of brain network organization. In particular, somatomotor network connectivity alterations were involved in the relationships between sleep and biopsychosocial factors. These profiles can potentially untangle the interplay between individuals variability in sleep, health, cognition and lifestyle -- equipping research and clinical settings to better support individuals well-being.

neuroscience↗

bioRxiv2023

Phase-amplitude coupling of NREM sleep oscillations is unaffected by pre-sleep learning but related to overnight memory gains depending on the declarative learning paradigm

There is growing evidence in humans linking the temporal coupling between spindles and slow oscillations during NREM sleep with the overnight stabilization of memories encoded from daytime experiences in humans. However, whether the type and strength of learning influence that relationship is still unknown. Here we tested whether the amount or type of verbal word-pair learning prior to sleep affects subsequent phase-amplitude coupling (PAC) between spindles and slow oscillations (SO). We measured the strength and preferred timing of such coupling in the EEG of 41 healthy human participants over a post-learning and control night, to compare intra-individual changes with inter-individual differences. We leveraged learning paradigms of varying word-pair (WP) load: 40 WP learned to a minimum criterion of 60% correct (n=11); 40 WP presented twice (n=15); 120 WP presented twice (n=15). There were no significant differences in the preferred phase or strength between the control and post-learning nights, in all learning conditions. We observed an overnight consolidation effect (improved performance at delayed recall) for the criterion learning condition only, and only in this condition was the overnight change in memory performance significantly positively correlated with the phase of SO-spindle coupling. These results suggest that the coupling of brain oscillations during human NREM sleep are stable traits that are not modulated by the amount of pre-sleep learning, yet are implicated in the sleep-dependent consolidation of memory.

neuroscience↗