Jaspar, M. | Search bioRxiv

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↗

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↗