Biology subjects

Salmon, E.

Publications and source records attributed to Salmon, E..

6 recordsLinked to original sources

bioRxiv2026

Cognitive Fitness in Ageing (COFITAGE): A Multimodal and Longitudinal Neuroimaging Dataset

Purpose: Brain aging involves interrelated changes in molecular processes, neuroinflammatory mechanisms, brain macro- and microstructure, sleep physiology, and cognition. The 50 to 70 years age range represents a critical transition period, in which these subtle alterations may precede measurable cognitive decline and the onset of clinical neurodegenerative disease. To allow systematic investigation of these early alterations and the subsequent progression in brain aging, we provide an open-access data resource from a multidisciplinary longitudinal study integrating neuroimaging, genetics, sleep, and neuropsychological phenotyping with assessments at baseline and at 2-year follow-up. Acquisition and Validation Methods: The baseline cohort comprises 101 community-dwelling participants (50-69 years old) who underwent magnetic resonance imaging (MRI) using a 3T protocol that included high-resolution structural imaging (T1- and T2-weighted), quantitative multi-parametric acquisitions with B1 mapping, and multi-shell diffusion-weighted imaging. Moreover, positron emission tomography (PET) imaging was performed using [18F]Flutemetamol or [18F]Florbetapir (amyloid-beta tracers) in all participants, with a subset also undergoing [18F]THK-5351 PET (tau-related/neuroinflammation). The dataset was complemented by extensive phenotypic data, including sleep and neuropsychological assessments, and by genotype data through genetic analysis. 66 participants underwent a 2-year cognitive follow-up, enabling longitudinal analyses of cognitive trajectories. Data acquisition and curation were performed using standardized procedures, with systematic quality control to support reliable cross-sectional and longitudinal analyses. Data Format and Usage Notes: All data are distributed in a BIDS-compliant format, and released in open-access (EBRAINS). Potential Applications: This dataset supports multimodal analyses, allowing the identification of interpretable patterns characterizing brain aging from multiple perspectives. It enables the comparison of different models to derive (semi)quantitative MRI parameters, the discovery of imaging biomarkers associated with early cognitive decline, and the monitoring or prediction of brain aging progression. In addition, it offers focused coverage of adults aged 50-70 years, which is often underrepresented in existing healthy subjects public datasets.

neuroscience↗

bioRxiv2023

In vivo marker of brainstem myelin is associated to quantitative sleep parameters in healthy young men

Brain structural integrity has been suggested to contribute to the variability in human sleep quality and composition. The associations between sleep parameters and the regional integrity of subcortical structures implicated in sleep-wake regulation remain, however, largely unexplored. The present study aimed at assessing association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem with the variability in the sleep electrophysiology in a large sample of healthy young men (N=321;[~]22y). Generalized Additive Model for Location, Scale and Shape (GAMLSS) was used to seek associations between sleep metrics and Magnetisation Transfer saturation (MTsat) qMRI values, proxy for myelin content. Separate GAMLSS revealed that sleep onset latency and slow wave sleep intensity were significantly associated with MTsat-derived myelin estimates in the brainstem (pcorrected[≤].03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction - pcorrected[≤].03), with higher MTsat value linked to better values in the two sleep metrics in the individuals of our sample aged [~]18 to 20y. Similar associations were detected across different parts of the brainstem (pcorrected[≤].03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the many reticular nuclei of the brainstem essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.

neuroscience↗

bioRxiv2023

In vivo Locus Coeruleus activity while awake is associated with REM sleep quality in healthy older individuals

The locus coeruleus (LC) is the primary source of norepinephrine (NE) in the brain, and the LC-NE system is involved in regulating arousal and sleep. It plays key roles in the transition between sleep and wakefulness, and between slow wave sleep (SWS) and rapid eye movement sleep (REMS). However, it is not clear whether the LC activity during the day predicts sleep quality and sleep properties during the night, and how this varies as a function of age. Here, we used 7 Tesla functional Magnetic Resonance Imaging (7T fMRI), sleep electroencephalography (EEG) and a sleep questionnaire to test whether the LC activity during wakefulness was associated with sleep quality in 52 healthy younger (N=33; ~22y; 28 women) and older (N=19; ~61y; 14 women) individuals. We find that, in older, but not in younger participants, higher LC activity, as probed during an auditory mismatch negativity task, is associated with worse subjective sleep quality and with lower power over the EEG theta band during REMS (4-8Hz), which are two sleep parameters significantly correlated in our sample of older individuals. The results remain robust even when accounting for the age-related changes in the integrity of the LC. These findings suggest that the activity of the LC may contribute to the perception of the sleep quality and to an essential oscillatory mode of REMS, and that the LC may be an important target in the treatment of sleep disorders and age-related diseases.

neuroscience↗

bioRxiv2022

Timely sleep coupling: spindle-slow wave synchrony is linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimers disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves is associated with early amyloid-beta (A{beta}) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50-70y; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation slow waves is associated with higher medial prefrontal cortex A{beta} burden (p=0.014, r2{beta}*=0.06), and is predictive of greater longitudinal memory decline (p=0.032, r2{beta}*=0.07). These findings unravel early links between sleep, AD-related processes and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.

neuroscience↗

bioRxiv2019

Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations

Age-related cognitive decline arises from alterations in brain integrity as well as in sleep-wake regulation. Here, we investigated whether preserved sleep-wake regulation of cortical function during wakefulness could represent a positive factor for cognitive fitness in aging, independently of early age-related changes in brain structure. We quantified cortical excitability dynamics during prolonged wakefulness as a sensitive marker of age-related alteration in sleep-wake regulation in 60 healthy older individuals (50-69y; 42 women). Brain structural integrity was assessed with amyloid-beta- and tau-PET, and with MRI. Participants cognition was extensively investigated. We show that individuals with preserved cortical excitability dynamics exhibit better cognitive performance, particularly in the executive domain, which is essential to successful cognitive aging. Critically, this association remained significant after accounting for brain integrity measures. Preserved dynamics of basic brain function during wakefulness could be essential to cognitive fitness in aging, independently from age-related brain structural modifications that can ultimately lead to dementia.

neuroscience↗

bioRxiv2019

Looking for a reference for large datasets: relative reliability of visual and automatic sleep scoring

Study ObjectivesNew challenges in sleep science require to describe fine grain phenomena or to deal with large datasets. Beside the human resource challenge of scoring huge datasets, the inter- and intra-expert variability may also reduce the sensitivity of such studies. Searching for a way to disentangle the variability induced by the scoring method from the actual variability in the data, visual and automatic sleep scorings of healthy individuals were examined.\n\nMethodsA first dataset (DS1, 4 recordings) scored by 6 experts plus an autoscoring algorithm was used to characterize inter-scoring variability. A second dataset (DS2, 88 recordings) scored a few weeks later was used to investigate intra-expert variability. Percentage agreements and Congers kappa were derived from epoch-by-epoch comparisons on pairwise, consensus and majority scorings.\n\nResultsOn DS1 the number of epochs of agreement decreased when the number of expert increased, in both majority and consensus scoring, where agreement ranged from 86% (pairwise) to 69% (all experts). Adding autoscoring to visual scorings changed the kappa value from 0.81 to 0.79. Agreement between expert consensus and autoscoring was 93%. On DS2 intra-expert variability was evidenced by the kappa systematic decrease between autoscoring and each single expert between datasets (0.75 to 0.70).\n\nConclusionsVisual scoring induces inter- and intra-expert variability, which is difficult to address especially in big data studies. When proven to be reliable and if perfectly reproducible, autoscoring methods can cope with intra-scorer variability making them a sensible option when dealing with large datasets.\n\nStatement of SignificanceWe confirmed and extended previous findings highlighting the intra- and inter-expert variability in visual sleep scoring. On large datasets those variability issues cannot be completely addressed by neither practical nor statistical solutions such as group training, majority or consensus scoring.\n\nWhen an automated scoring method can be proven to be as reasonably imperfect as visual scoring but perfectly reproducible, it can serve as a reliable scoring reference for sleep studies.

neuroscience↗