Biology subjects

Peigneux, P.

Publications and source records attributed to Peigneux, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Modulating Sleep Oscillations Through Targeted Memory Reactivation: Linking Functional Dynamics to Brain Microstructure

Background: Sleep-dependent memory consolidation reputedly rely on the coordinated activity of sleep oscillations, which may facilitate the reactivation and redistribution of newly acquired memories. Targeted memory reactivation (TMR) during sleep can experimentally modulate these processes, although effects remain variable. Moreover, how learning-related microstructural plasticity relates to sleep oscillatory activity and spindle-related network dynamics remains poorly understood. We investigated whether auditory TMR modulates sleep spindles, slow oscillations (SOs) and their co-occurrence, whether these changes relate to motor memory consolidation and diffusion MRI (dMRI) measures of brain microstructure, and whether learning and TMR alter the evolution of cortico-cortical connectivity during spindle development. Methods: Sixty healthy young adults underwent five dMRI sessions before and after motor sequence learning (Day 1), after a post-training night of regular sleep (RS) or TMR (Day 2), and before and after relearning (Day 5). Baseline and experimental nights were recorded with 256-channel high-density EEG. Oscillation densities were analyzed using mixed-design ANOVAs and related to behavioral and dMRI changes using Pearson or Spearman correlations. Intra-spindle connectivity between 148 source-reconstructed cortical regions was compared between spindle onset and end, across nights and between groups using Network-Based Statistics. Results: Spindle density, SO density and SO-spindle co-occurrence remained stable across nights in the RS group but decreased after TMR. Higher spindle density and co-occurrence were associated with greater overnight performance gains, and all oscillatory measures were associated with learning-related dMRI changes in subcortical regions, notably striatum and thalamus. Connectivity increased from the beginning to the end of the spindle duration during the baseline night in both groups, but during the experimental night only in the RS group. Conclusions: Motor learning is associated with coordinated changes in sleep oscillatory activity, within-spindle cortical connectivity and brain microstructure, supporting a dynamic interaction between learning-induced plasticity and sleep-dependent network reorganization. Under the present stimulation conditions, TMR did not enhance these processes but instead reduced sleep oscillatory activity and attenuated spindle-related connectivity dynamics, underscoring the importance of precisely targeting endogenous sleep rhythms when using TMR.

neuroscience↗

bioRxiv2026

Theta-band brain synchronization supports the immediate and post-sleep dynamics of memory recall in children

Memory engrams emerge from dynamic, coordinated interactions among synchronized functional brain networks. Yet, how these networks are selectively reactivated upon cued recall and gradually (re)organized over time, especially through sleep, remains poorly understood. Using magnetoencephalography (MEG), sleep electroencephalography (EEG) and behavioral measures, we investigated the spatiotemporal neural dynamics of cued recall memory during immediate and post-sleep (i.e., 90-minute post-learning nap) recall sessions in school-aged children. Results showed that immediate recall engaged a temporally ordered sequence of theta-band phase synchronization across two transiently synchronized networks: an early (150-350 ms) network involving the ventral visual pathway and left medial temporal lobe (MTL), followed by a later (550-750 ms) network encompassing the bilateral MTL and widespread neocortical associative regions. Post-sleep recall was associated, relative to wakefulness, with strengthened theta-band phase synchronization between the left MTL and widespread bilateral neocortical regions in a similar late window (450-650 ms). Post-sleep theta-band synchronization and memory gains in performance positively correlated with slow oscillation-spindle coupling during the post-learning nap. Altogether, these findings highlight oscillatory and spatiotemporal dynamics of memory recall networks and suggest that sleep, possibly driven by slow-oscillation-spindle coupling mechanisms, supports the efficient reinstatement of memory traces in the developing brain.

neuroscience↗

bioRxiv2025

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↗

bioRxiv2024

Shaping the structural dynamics of motor learning through cueing during sleep

Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted Memory Reactivation (TMR), involving cueing learned material during post-training sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and post-training sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during post-training sleep affects performance gains and delayed microstructural remodeling, using both standard Diffusion Tensor Imaging (DTI) and advanced Neurite Orientation Dispersion & Density Imaging (NODDI). Sixty healthy young adults participated in a five-day protocol, undergoing five Diffusion-Weighted Imaging (DWI) sessions, pre- and post-two motor sequence training sessions, and after a post-training night of either regular sleep (RS) or TMR. Results demonstrated rapid skill acquisition on Day 1, followed by performance stabilization on Day 2, and improvement on Day 5, in both RS and TMR groups. (Re)training induced widespread microstructural changes in motor-related areas, initially involving the hippocampus, followed by a delayed engagement of the caudate nucleus. Mean Diffusivity (MD) changes were accompanied by increased Neurite Density Index (NDI) in the putamen, suggesting increased neurite density, while Free Water Fraction (FWF) reduction indicated glial reorganization. TMR-related structural differences emerged in the dorsolateral prefrontal cortex (DLPFC) on Day 2 and the right cuneus on Day 5, suggesting unique sleep TMR-related neural reorganization patterns. Persistence of practice-related structural changes, although moderated over time, suggest a lasting neural network reorganization, partially mediated by sleep TMR. Statement of SignificanceThis study demonstrates how motor practice triggers short-term and long-term microstructural reorganization in (sub)cortical grey matter, with a focus on how sleep Targeted Memory Reactivation (TMR) influences these changes, particularly in motor-related areas. Combining standard Diffusion Tensor Imaging (DTI) with advanced Neurite Orientation Dispersion & Density Imaging (NODDI) imaging techniques, we highlight distinct patterns of neural reorganization, suggesting glial and/or synaptic changes, in response to motor practice, possibly partially mediated by TMR. This research enhances our understanding of motor practice-related structural plasticity mechanisms and highlights the potential of targeted sleep interventions to modulate brain reorganization, suggesting new avenues for optimizing motor skill acquisition.

neuroscience↗

bioRxiv2024

Sleep Fragmentation Modulates the Neurophysiological Correlates of Cognitive Fatigue

Cognitive fatigue (CF) is a critical factor affecting performance and well-being. It can be altered in suboptimal sleep quality conditions, e.g., in patients suffering from obstructive sleep apnea who experience both intermittent hypoxia and sleep fragmentation (SF). Understanding the neurophysiological basis of SF in healthy individuals can provide insights to improve cognitive functioning in disrupted sleep conditions. In this electroencephalographical (EEG) study, we investigated in 16 healthy young participants the impact of experimentally induced SF on the neurophysiological correlates of CF measured before, during, and after practice on the TloadDback, a working memory task tailored to each individuals maximal cognitive resources. Participants spent two times three consecutive nights in the laboratory, once in an undisrupted sleep (UdS) condition and once in a SF condition induced by non-awakening auditory stimulations, counterbalanced, and performed the TloadDback task both in a high (HCL) and a low (LCL) cognitive load condition. EEG activity was recorded during wakefulness in the 5-minutes resting state immediately before and after, as well as during the 16-minutes of the TloadDback task practice. In the high cognitive load under sleep fragmentation (HCL/SF) condition, high beta power increased during the TloadDback indicating heightened cognitive effort, and beta and alpha power increased in the post- vs. pre task resting state, suggesting a relaxation rebound. In the low cognitive load/undisturbed sleep (LCL/UdS) condition, low beta activity increased suggesting a relaxed focus, as well as mid beta activity associated with active thinking. These findings highlight the dynamic impact of SF on the neurophysiological correlates of CF and underscore the importance of sleep quality and continuity to maintain optimal cognitive functioning.

neuroscience↗

bioRxiv2023

Motor learning- and consolidation-related resting state fast and slow brain dynamics across wake and sleep

Learning and consolidation of motor skills dynamically evolve both online during practice and offline after training. We investigated, using magnetoencephalography, the neural dynamics underpinning motor learning and its consolidation in relation to sleep during resting-state periods shortly after the end of learning (short-term boost window, within 30 min) and at more delayed time scales (silent 4h and next day 24h windows) with an intermediate nap or wakefulness after the boost window. Resting-state neural dynamics in brain networks were investigated at fast (sub-second) and slower (supra-second) timescales using Hidden Markov modelling (HMM) and resting-state functional connectivity (rsFC), respectively, as well as their relationship with the evolution of motor performance. HMM results show that fast dynamic activities in a Temporal/Sensorimotor state network predict individual motor performance achievements, suggesting a trait-like association between rapidly recurrent neural patterns and motor behaviour. Short, post-training re-exposure to the task modulated fast and slow network characteristics during the boost but not in the silent window. These short practice-related induction effects were observed again on the next day, to a reduced extent as compared to the boost window. Daytime naps did not significantly modulate memory consolidation both at behavioural and neural levels. These results emphasise the critical role of the transient boost window in motor learning and subsequent memory consolidation processes and provide further insights into the relationship between the multiscale neural dynamics of brain networks, motor learning, and consolidation.

neuroscience↗

bioRxiv2023

Microstructural dynamics of motor learning and sleep-dependent consolidation: a diffusion imaging study

Diffusion-weighted magnetic resonance imaging (DWI) allows the observation of (micro)structural brain remodelling in cortical and subcortical regions after time-limited motor learning. Post-learning sleep consolidation should lead to long-term microstructural brain changes, but concrete evidence remains limited. Here, we used both conventional diffusion tensor imaging (DTI) and Neurite Orientation Dispersion & Density Imaging (NODDI), that estimates dendritic and axonal complexity in white and grey matter, to investigate the microstructural brain mechanisms underlying time- and sleep-dependent motor memory consolidation. Sixty-one young healthy adults underwent 2 DWI sessions, with sequential motor training in between, on day 1 followed by the experimental night of total sleep deprivation or regular sleep. After 3 recovery nights at home, they underwent 2 further DWI sessions separated by a motor retraining session. Sequential motor learning resulted in immediate modifications in structural parameters in occipitoparietal and temporal regions, as well as in subcortical regions of interest. Similar changes were observed following relearning but at a smaller magnitude. Regarding delayed consolidation effects, learning-related changes only partially persisted 3 days after initial learning, and no post-learning sleep effect was detected. Our results show rapid motor learning-related remodelling, reflecting temporary processes in learning-related neuronal brain plasticity. Post-learning sleep-related cellular changes remain to be evidenced, possibly using more sophisticated brain imaging measures and spanning more extended timescales to allow the expression of structural changes.

neuroscience↗

bioRxiv2023

Motor adaptation is facilitated by sleep-associated modulation of beta oscillations

Motor adaptation reflects the ability of the brains sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatized motor skill, i.e., typing. We hypothesized that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography (EEG). Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power (a) during mirrored typing as compared to regular typing, and (b) in the post-sleep vs. the pre-sleep mirrored typing sessions. Furthermore, the slope of the EEG signal, a measure of aperiodic brain activity, decreased during mirrored as compared to regular typing. Changes in the EEG spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity mechanisms supporting adaptive motor functions.

neuroscience↗

bioRxiv2023

A complementary contribution of REM sleep after targeted memory reactivation during NREM sleep for memory consolidation

Presentation of learning-related cues during NREM sleep has been shown to improve memory consolidation. Past studies suggest that REM sleep may contribute to the beneficial effect of reactivating memories during NREM sleep, but the relationship between REM sleep and induced reactivations in NREM remains unclear. We investigated whether a naturally ensuing episode of REM sleep is necessary for prior NREM targeted memory reactivation (TMR) to exert a beneficial effect on memory consolidation. Nineteen participants learned the association between prior or non-prior known objects and their names (pseudowords) in a within-subject multiple session experiment, in which TMR was subsequently performed either before (Pre-REM) or after (Post-REM) the final REM sleep episode of the night. While word-picture association recall measures did not differ between TMR conditions, we found better name recognition based on confidence ratings for words reactivated during Pre-REM TMR in contrast with associations cued during Post-REM TMR. In addition, we found distinct associations between cue-evoked sigma activity, subsequent REM theta power and TMR memory benefits which were contingent upon the level of relatedness with prior knowledge for the learned material. Although TMR may be less effective during the second half of the night, our findings suggest an interplay between NREM and REM sleep oscillatory activity for memory reactivation and consolidation processes.

neuroscience↗

bioRxiv2022

Correction of susceptibility distortion in EPI: a semi-supervised approach with deep learning.

Echo planar imaging (EPI) is the most common approach for acquiring diffusion and functional MRI data due to its high temporal resolution. However, this comes at the cost of higher sensitivity to susceptibility-induced B0 field inhomogeneities around air/tissue inter-faces. This leads to severe geometric distortions along the phase encoding direction (PED). To correct this distortion, the standard approach involves an analogous acquisition using an opposite PED leading to images with inverted distortions and then non-linear image registration, with a transformation model constrained along the PED, to estimate the voxelwise shift that undistorts the image pair and generates a distortion-free image. With conventional image registration approaches, this type of processing is computationally intensive. Recent advances in unsupervised deep learning-based approaches to image registration have been proposed to drastically reduce the computational cost of this task. However, they rely on maximizing an intensity-based similarity measure, known to be suboptimal surrogate measures of image alignment. To address this limitation, we propose a semi-supervised deep learning algorithm that directly leverages ground truth spatial transformations during training. Simulated and real data experiments demonstrate improvement to distortion field recovery compared to the unsupervised approach, improvement image similarity compared to supervised approach and precision similar to TOPUP but with much faster processing.

neuroscience↗

bioRxiv2022

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↗

bioRxiv2022

Connectivity in Large-Scale Resting State Brain Networks is Related to Motor Learning: a High-Density EEG Study

Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG) we addressed this question from a brain network perspective. Specifically, we examined frequency-dependent functional connectivity in resting-state networks from twenty-nine young healthy participants before and after they were trained on a motor sequence learning task. Consolidation was assessed with an overnight retest on the motor task. We showed training-related decreases in gamma band connectivity within the motor network, and between the motor and functionally distinct resting-state networks including the attentional network. Brain-behavior correlation analyses revealed that baseline beta, delta and theta rsFC was related to subsequent motor learning and memory consolidation such that lower connectivity within the motor network and between the motor and several distinct resting-state networks was correlated with better learning and overnight consolidation. Last, training-related increases in beta-band connectivity between the motor and the visual networks were related to greater consolidation. Altogether our results indicate that connectivity in large-scale resting-state brain networks is related to - and modulated by - motor learning and memory consolidation processes. These finding corroborate previous seed-based connectivity research and provide evidence that frequency-dependent functional connectivity in resting state networks is critically linked to motor learning and memory consolidation.

neuroscience↗

bioRxiv2021

Alpha peak frequency is linked to episodic memory impairment in pathological aging

The Free and Cued Selective Reminding Test (FCSRT) is a largely validated neuropsychological test for the identification of amnestic syndrome from the early stage of Alzheimers disease (AD). Previous electrophysiological data suggested a slowing down of the alpha rhythm in the AD-continuum as well as a key role of this rhythmic brain activity for episodic memory processes. This study therefore investigates the link between alpha brain activity and alterations in episodic memory as assessed by the FCSRT. For that purpose, 37 patients with altered FCSRT performance underwent a comprehensive neuropsychological assessment, supplemented by 18F-fluorodeoxyglucose positron emission tomography/structural magnetic resonance imaging (18FDG-PET/MR), and 10 minutes of resting-state magnetoencephalography (MEG). The individual alpha peak frequency (APF) in MEG resting-state data was positively correlated with patients encoding efficiency as well as with the efficacy of semantic cues in facilitating patients retrieval of previous stored word. The APF also correlated positively with patients hippocampal volume and their regional glucose consumption in the posterior cingulate cortex. Overall, this study demonstrates that alterations in the ability to learn and store new information for a relatively short-term period are related to a slowing down of alpha rhythmic activity, possibly due to altered interactions in the extended mnemonic system. As such, a decreased APF may be considered as an electrophysiological correlate of short-term episodic memory dysfunction accompanying pathological aging.

neuroscience↗

bioRxiv2021

Microstates and power envelope hidden Markov modeling probe bursting brain activity at different timescales

State modeling of whole-brain electroencephalography (EEG) or magnetoencephalography (MEG) allows to investigate transient, recurring neurodynamical events. Two widely-used techniques are the microstate analysis of EEG signals and hidden Markov modeling (HMM) of MEG power envelopes. Both reportedly lead to similar state lifetimes on the 100 ms timescale, suggesting a common neural basis. We addressed this issue by using simultaneous MEG/EEG recordings at rest and comparing the spatial signature and temporal activation dynamics of microstates and power envelope HMM states obtained separately from EEG and MEG. Results showed that microstates and power envelope HMM states differed both spatially and temporally. Microstates tend to exhibit spatio-temporal locality, whereas power envelope HMM states disclose network-level activity with 100-200 ms lifetimes. Further, MEG microstates do not correspond to the canonical EEG microstates but are better interpreted as split HMM states. On the other hand, both MEG and EEG HMM states involve the (de)activation of similar functional networks. Microstate analysis and power envelope HMM thus appear sensitive to neural events occurring over different spatial and temporal scales. As such, they represent complementary approaches to explore the fast, sub-second scale bursting electrophysiological dynamics in spontaneous human brain activity.

neuroscience↗

bioRxiv2020

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↗

bioRxiv2020

Beta-tACS does not impact the dynamics of motor memory consolidation

The consolidation of motor memory is a non-linear temporal dynamic. There are critical time points at which post-training performance can improve (e.g., 30 min and 24 h) or merely stabilize (e.g., 4 h). Besides, neuronal plasticity is supported by synchronized oscillatory activity in and between brain areas at play during the acquisition and consolidation of motor skills. Transcranial alternating current stimulation (tACS) can entrain cortical oscillatory activity, which may eventually modulate brain plasticity-related processes. Previous reports suggest that 20 Hz electrical stimulation over the primary motor cortex (M1) following training facilitates the consolidation of motor memories. To the best of our knowledge, the effect of tACS was not investigated when applied at critical post-training time points, nor its impact at longer time scales. In the present study, we investigated the effect of 20 Hz tACS applied over M1 within critical time periods (25min vs. 4h) on motor memory consolidation at immediate and delayed (24h) retrieval. Performance similarly evolved over time in all conditions, independently from the stimulation type (20 Hz tACS vs. Sham tACS) or the stimulation time point. As it stands, our results do not support the proposal that 20 Hz tACS exerts a positive, specific effect on the consolidation of motor memories.

neuroscience↗

bioRxiv2020

Alterations in resting-state network dynamics along the Alzheimer's disease continuum: a combined MEG-PET/MR approach

Human brain activity is intrinsically organized into resting-state networks (RSNs) that transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies have addressed how Alzheimers disease (AD) affects these fast temporal brain dynamics, and how they relate to the cognitive, structural and metabolic abnormalities characterizing AD. We aimed at closing this gap by investigating both brain structure and function using magnetoencephalography (MEG) and hybrid positron emission tomography-magnetic resonance (PET/MR) in 10 healthy elders, 10 patients with Subjective Cognitive Decline (SCD), 10 patients with amnestic Mild Cognitive Impairment (aMCI) and 10 patients with typical Alzheimers disease with dementia (AD). The fast activation/deactivation state dynamics of RSNs were assessed using hidden Markov modeling (HMM) of power envelope fluctuations at rest measured with MEG. HMM patterns were related to participants cognitive test scores, whole hippocampal grey matter volume and regional brain glucose metabolism. The posterior default-mode network (DMN) was less often activated and for shorter durations in AD patients than matched healthy elders. No significant difference was found in patients with SCD or aMCI. The time spent by participants in the activated posterior DMN state did not correlate significantly with cognitive scores. However, it correlated positively with the whole hippocampal volume and regional glucose consumption in the right temporo-parietal junctions and dorsolateral prefrontal cortex, and negatively with glucose consumption in the cerebellum. In AD patients, alterations of posterior DMN power activation dynamics at rest correlate with structural and neurometabolic abnormalities. These findings represent an additional electrophysiological correlate of AD-related synaptic and neural dysfunction.

neuroscience↗

bioRxiv2020

Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional integration were assessed using band-limited power envelope correlation, whereas those on transient functional dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (i) a strengthening of functional integration within and between resting-state networks and (ii) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamical stability within the visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

neuroscience↗