bioRxiv Science⌕ Search

Biology subjects

Deantoni, M.

Publications and source records attributed to Deantoni, M..

5 recordsLinked to original sources

Napping alters Functional Brain Responses in the Aged

Circadian rhythms shape the temporal organization of sleep and wakefulness and evolve throughout the adult lifespan, leading to higher sleep-wake cycle fragmentation with ageing. The increasing prevalence of daytime napping represents a visible manifestation of such fragmentation and has been suggested to forecast age-related cognitive decline. Here, we assessed the impact of napping on functional brain correlates of performance on a Sternberg working memory (WM) task using functional magnetic resonance imaging in 60 healthy older individuals, prospectively recruited with respect to their napping habits (39 females, age: 59-82y). As compared to non-nappers, nappers showed reduced hemispheric asymmetry in the dorsolateral prefrontal cortex (DLPFC, p< 0.001) and decreased performance at high WM load levels. Only in non-nappers was increased ipsilateral activation in the DLPFC associated with better performance at high WM load levels (p < 0.05), while contralateral activation across all WM load levels was not associated with better performance. These findings indicate that functional brain compensation and dedifferentiation processes vary according to an individuals napping phenotype, potentially serving as a marker of inter-individual differences in cognitive and brain aging.

neuroscience↗

Napping and circadian sleep-wake regulation during healthy aging.

Study objectivesDaytime napping is frequently reported among the older population and has attracted increasing attention due to its association with multiple health conditions. Here, we tested whether napping in the aged is associated with altered circadian regulation of sleep, sleepiness and vigilance performance. MethodsSixty healthy older individuals (mean age: 69y., 39 women) were recruited with respect to their napping habits (30 nappers, 30 non-nappers). All participants underwent an in-lab 40-h multiple nap protocol (10 cycles of 80 mins of sleep opportunity alternating with 160 mins of wakefulness), preceded and followed by a baseline and recovery sleep period. Saliva samples for melatonin assessment, sleepiness and vigilance performance were collected during wakefulness and electrophysiological data were recorded to derive sleep parameters during scheduled sleep opportunities. ResultsThe circadian amplitude of melatonin secretion was reduced in nappers, compared to non-nappers. Furthermore, nappers were characterized by higher sleep efficiencies and REM sleep proportion during day-compared to night-time naps. The nap group also presented altered modulation in sleepiness and vigilance performance at specific circadian phases. DiscussionOur data indicate that napping is associated with an altered circadian sleep-wake propensity rhythm and thereby contribute to the understanding of the biological correlates underlying napping and/or sleep-wake cycle fragmentation during healthy aging. Altered circadian sleep-wake promotion can lead to a less distinct allocation of sleep into night-time and/or a reduced wakefulness drive during the day, thereby potentially triggering the need to sleep at adverse circadian phase. SIGNIFICANCE STATEMENTWhile napping has raised increasing interest as a health risk factor in epidemiological studies, its underlying regulation processes in the aged remain largely elusive. Here we assessed whether napping in the older population is associated with physiological and behavioral changes in circadian sleep-wake characteristics. Our data indicate that, concomitant to a reduced circadian amplitude in melatonin secretion, healthy older nappers are characterized by reduced day-night differences in sleep efficiency and more particularly in REM sleep, compared to their non-napping counterparts. These results suggest altered circadian response as a cause or consequence of chronic napping in the aged and thereby contribute to the understanding of nap regulation during healthy aging.

neuroscience↗

Sleep-dependent structural neuroplasticity after a spatial navigation task: A diffusion imaging study

Evidence for sleep-dependent changes in micro-structural neuroplasticity remains scarce, despite the fact that it is a mandatory correlate of the reorganization of learning-related functional networks. We investigated the effects of post-training sleep on structural neuroplasticity markers measuring standard diffusion tensor imaging (DTI) mean diffusivity (MD) and the revised biophysical neurite orientation dispersion and density imaging (NODDI) free water fraction (FWF) and neurite density (NDI) parameters that enable disentangling whether MD changes result from modifications in neurites or in other cellular components (e.g., glial cells). Thirty-four healthy young adults were scanned using diffusion weighted imaging [DWI] on Day1 before and after 40-minutes route learning (navigation) in a virtual environment, then were sleep deprived (SD) or slept normally (RS) for the night. After recovery sleep for 2 nights, they were scanned again (Day4) before and after 40-minutes route learning (navigation) in an extended environment. Sleep-related microstructural changes were computed on DTI (MD) and NODDI (NDI and FWF) parameters in the cortical ribbon and subcortical hippocampal and striatal regions of interest (ROIs). Results disclosed navigation learning-related decreased DWI parameters in the cortical ribbon (MD, FWF) and subcortical (MD, FWF, NDI) areas. Post-learning sleep-related changes were found at Day4 in the extended learning session (pre- to post-relearning percentage changes), suggesting a rapid sleep-related remodelling of neurites and glial cells subtending learning and memory processes in basal ganglia and hippocampal structures.

neuroscience↗

pyActigraphy: open-source python package for actigraphy data visualisation and analysis

Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy, a comprehensive toolbox for data visualization and analysis including multiple sleep detection algorithms and rest-activity rhythm variables. This open-source python package implements methods to read multiple data formats, quantify various properties of rest-activity rhythms, visualize sleep agendas, automatically detect rest periods and perform more advanced signal processing analyses. The development of this package aims to pave the way towards the establishment of a comprehensive open-source software suite, supported by a community of both developers and researchers, that would provide all the necessary tools for in-depth and large scale actigraphy data analyses. Required MetadataO_ST_ABSCurrent code versionC_ST_ABS

bioinformatics↗

Continued topographical learning- and relearning-dependent activity in the resting state after post-training sleep and wake

Continuation of experience-dependent neural activity during offline periods of sleep and wakefulness is a critical element of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioral and neurophysiological changes during memory retrieval, i.e. in the context of task practice. Resting state fMRI (rfMRI) further allows investigating the offline evolution of recently learned information, without confounding task-related effects. In the present study, we used rfMRI to investigate offline changes in functional connectivity (FC) and Amplitude of Low Frequency Fluctuation (ALFF) associated with learning and relearning in a spatial navigation task, following an episode of post-training wake or sleep, respectively. Resting state activity was measured immediately (i) before and (ii) after topographical learning in a virtual town, (iii) 4 days later after regular sleep (RS) vs. sleep deprivation (SD) on the first post-learning night, and (iv) after topographical re-learning in an extended town encompassing the initial map. Task (navigation)-based fMRI activity was also recorded on Day 1 and Day 4 during target retrieval. Our results highlight the continuation of navigation-related activity in the subsequent resting state, as evidenced by changes in FC and ALFF in task-related neural networks. Behavioural performance was not modulated by post-training SD vs RS. However, in line with prior reports, post-training SD was associated with increased FC between navigation-related brain structures when faced to the task of learning a novel but related environment in the extended version of the city at Day 4. These results suggest the use of compensatory resources to link novel information with SD-related less efficiently consolidated memory traces.

neuroscience↗