Neural correlates of device-based sleep characteristics in adolescents
Poster No:
1277
Submission Type:
Abstract Submission
Authors:
qing ma1, Wei Cheng1
Institutions:
1Fudan University, Shanghai, -- SELECT --
First Author:
Co-Author:
Introduction:
Adolescence is marked by significant transformations in sleep patterns, including shortened sleep duration, delayed sleep time and shifted circadian rhythm2. These predictable changes often coincide with ongoing development of key cognitive and regulatory neural systems that is essential for cognitive development preparing for adult life1,3. Therefore, investigating the relevance between sleep characteristics and the underlying brain development that facilitates cognitive development becomes particularly significant.
Methods:
3300 adolescents aged11-12 years old (the 2-year follow-up data) from Adolescent Brain Cognitive Development (ABCD 5.0) study, integrating extensive device-based sleep characteristics and multimodal imaging data. The replication sample consisted of 1,271 adolescents aged 13-14 years old (the 4-year follow-up data). Sleep characteristics were objectively collected through wristband records using Fitbit. An average of 18 sleep indicators were collected daily over the three-weeks period. For brain imaging, we collected 85 regional volumes, including 68 cortical and 17 subcortical areas, respectively. Resting state functional connectivity among 12 networks and subcortical regions were also involved. Specific functional networks are auditory, cingulo-opercular, cingulo-parietal, default-mode, dorsal-attention, fronto-parietal, retrosplenial-temporal, salience, sensorimotor-hand, sensorimotor-mouth, ventral-attention, and visual networks. Cognitive performance was measured using NIH Toolbox. Here, we first applied sparse canonical correlation (sCCA) analysis to obtain the relationship between dimensional sleep and brain structure and function. Subsequently, significant canonical variates derived from brain imaging data were used to cluster adolescents into distinct biotypes. Then, we used one-way analysis of covariance (ANCOVA) to identify sleep characteristics, cognitive performance, academic attainment, and brain imaging measures that differed between relatively homogeneous biotypes.
Results:
1. Two sleep-brain dimensions.
We revealed two sleep-brain dimensions: one characterized by later being asleep and shorter duration, linked to decreased subcortical-cortical network functional connectivities; the other showed higher heart rate and shorter light sleep duration, associated with lower brain volumes and decreased functional connectivities.
2. Three adolescent biotypes based on dimension of brain measures.
Hierarchical clustering based on brain dimension associated with sleep characteristics revealed three biotypes of adolescents, marked by unique sleep profiles: biotype 1 exhibited delayed and shorter sleep, coupled with higher heart rate during sleep; biotype 3 with earlier and longer sleep, accompanied by lower heart rate; and biotype 2 with intermediate pattern.
3. Biotype-specific cognitive performance, academic attainment, and brain measures.
Results showed that the three biotypes differed significantly in the cognitive performances (FDR correction at P < 0.05), including crystalized intelligence (F = 22.21, P <0.001), picture vocabulary (F = 20.04, P < 0.001), and oral reading recognition (F = 13.35, P <0.001.
4. Longitudinal analyses revealed that all three biotypes exhibited progressive improvements in cognitive ability, specifically in crystallized intelligence, picture vocabulary, and oral reading recognition, over the four-year span.
We revealed two sleep-brain dimensions: one characterized by later being asleep and shorter duration, linked to decreased subcortical-cortical network functional connectivities; the other showed higher heart rate and shorter light sleep duration, associated with lower brain volumes and decreased functional connectivities.
2. Three adolescent biotypes based on dimension of brain measures.
Hierarchical clustering based on brain dimension associated with sleep characteristics revealed three biotypes of adolescents, marked by unique sleep profiles: biotype 1 exhibited delayed and shorter sleep, coupled with higher heart rate during sleep; biotype 3 with earlier and longer sleep, accompanied by lower heart rate; and biotype 2 with intermediate pattern.
3. Biotype-specific cognitive performance, academic attainment, and brain measures.
Results showed that the three biotypes differed significantly in the cognitive performances (FDR correction at P < 0.05), including crystalized intelligence (F = 22.21, P <0.001), picture vocabulary (F = 20.04, P < 0.001), and oral reading recognition (F = 13.35, P <0.001.
4. Longitudinal analyses revealed that all three biotypes exhibited progressive improvements in cognitive ability, specifically in crystallized intelligence, picture vocabulary, and oral reading recognition, over the four-year span.
Conclusions:
Collectively, our novel findings delineate a linkage between objective sleep characteristics and developing brain in adolescents, underscoring their significance in cognitive development and academic attainment, which could serve as references for individuals with sleep difficulties and offer insights for optimizing sleep routines to enhance better cognitive development and school achievement.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence
Lifespan Development Other 1
Novel Imaging Acquisition Methods:
Anatomical MRI
BOLD fMRI
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 2
Keywords:
Cognition
Cortex
Development
MRI
PEDIATRIC
Sleep
1|2Indicates the priority used for review
·Fig. 1 Patterns of brain volumes and functional network connectivities contribute to linked sleep dimension.
·Fig. 2 Hierarchical clustering on brain canonical variate reveals three biotypes of adolescents and sleep patterns in three biotypes.
Provide references using author date format
2 Galván, A. The Need for Sleep in the Adolescent Brain. Trends Cogn Sci 24, 79-89, doi:10.1016/j.tics.2019.11.002 (2020).
3 Anastasiades, P. G., de Vivo, L., Bellesi, M. & Jones, M. W. Adolescent sleep and the foundations of prefrontal cortical development and dysfunction. Prog Neurobiol 218, 102338, doi:10.1016/j.pneurobio.2022.102338 (2022).