Cortical thinning and sleep slow wave activity reductions mediate age-related improvements in cognition during mid-late adolescence

Díaz‐Román

2023

EJIHPE

The relevance of cognitive performance during adolescence requires further studies that analyze potential associated factors. This study aimed to analyze inductive reasoning, reading comprehension, and mathematical thinking (problem-solving and number and calculation) in relation to sleep and depression in 244 students aged 12–17 years (47.6% boys and 52.4% girls). Daytime sleepiness, sleep quality, dysthymia, and euthymia (state and trait) were assessed by self-reported questionnaires. Moreover, correlations between these variables and cognitive performance, and differences depending on sociodemographic variables (sex, age, or academic year) were analyzed using non-parametric tests. Robust regression models were also conducted to evaluate the predictive role of significant variables on cognitive performance. The results showed significant bidirectional relationships between sleep- and depression-related variables, and between the latter ones and cognitive performance. Depression-trait was more related to cognitive performance than depression-state, and euthymia more than dysthymia, but neither daytime sleepiness nor sleep quality significantly correlated with it. As for sociodemographic variables, girls reported worse sleep and more depressive symptoms than boys did, and younger students reported better sleep but performed worse than the older ones. Although these findings should be further explored in forthcoming studies adding other promising variables, they highlight the importance of promoting euthymia to improve cognitive performance in adolescents.

Section: Discussionsupporting

confidence: 92%

Associations between Sleep, Depression, and Cognitive Performance in Adolescence

Díaz‐Román

2023

EJIHPE

“…In recent examinations of the brain-sleep structure relationship across development, an association was found between the decrease in gray matter thickness and a decline in slow-wave electroencephalogram in adolescence [86,87]. Ong and colleagues [88] found that age-related improvement in processing speed among adolescents was associated with reduced gray matter thickness as well as reduced sleep slow wave activity and was not affected by sleepiness levels. The synaptic elimination model posits that in adolescence, as synaptic pruning proceeds, the intensity of brain activity declines, leading to increased sleepiness.…”

Section: Discussionmentioning

confidence: 99%

The Role of Sleep for Age-Related Differences in Neurobehavioral Performance

Tzischinsky,

Barel

2024

Life

This study investigated developmental changes from childhood to adulthood in neurobehavioral performance and sleep measures. While many studies have examined age-related changes between childhood and adolescence and from mid-to-late adulthood, young adulthood has been overlooked. The main aim of this study was to investigate the effects of sleep loss on developmental changes in neurobehavioral performance and sleepiness in a natural setting. A total of 119 children, adolescents, and young adults (38 children aged 6–9; 38 adolescents aged 13–19; and 43 young adults aged 20–27) wore an actigraph for a continuous five-weekday night. Subjective sleepiness (Karolinska Sleepiness Scale) and neurobehavioral performance (using the psychomotor vigilance test and the digit symbol substitution test) were measured on five school days. The results showed that adolescents and young adults outperformed children on both the digit symbol substitution test and the psychomotor vigilance test measures. However, adolescents committed more errors of commission on the psychomotor vigilance test and reported higher levels of subjective sleepiness. The results are discussed in relation to brain maturation in various cognitive functions.

“…Nevertheless, while our current study does not test explanations of GM loss besides WM growth, evidence from other studies suggests a strong correspondence between GM shrinkage patterns and synaptic pruning patterns. For example, adolescent GM shrinkage is known to mediate a reduction in slow‐wave activity during sleep, which is a putative marker of synapse loss (Goldstone et al, 2018 ; Ong et al, 2021 ). Likewise, the GM shrinkage pattern is not only associated with expression profiles for genes related to myelin, but also with genes related to synaptic remodeling (Vidal‐Pineiro et al, 2020 ; Whitaker et al, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Can gray matter loss in early adolescence be explained by white matter growth?

Chad,

Lebel

2024

Human Brain Mapping

A fundamental puzzle about brain development is why the volume of gray matter (GM) apparently declines as white matter (WM) grows when children enter adolescence. Since pruned synapses are too small to affect GM volume, a prevailing theory posits that an expanded distribution of myelin causes the inner edge of the GM to “whiten” while total brain volume remains steady, shifting the MRI‐measured WM:GM boundary closer to the brain's outer surface. This theory inherently predicts that GM volume loss is concurrent with WM volume growth across regions, within sexes and over time, although these predictions have yet to be explicitly tested. In this study, we test these predictions by mapping regional GM and WM volumetric changes in 2333 participants of the Adolescent Brain Cognitive Development study aged 9–14 years who each received three MRI scans 2 years apart. We show that average GM and WM volume changes follow distinct spatial, temporal, and sex‐specific patterns, indicating that GM volume loss is not balanced by WM volume growth, although cortical GM thinning is weakly correlated with WM growth in some regions. We conclude that myelin is not the main source of measured GM volume loss, and we propose alternative candidates.