Reduced Brain Entropy in Insula is Associated with Worse Sleep Quality
Poster No:
2094
Submission Type:
Abstract Submission
Authors:
Emily Wang1, Annie Wang2, Gianpaolo Del Mauro3
Institutions:
1Lower Merion School District, Wynnewood, PA, 2Pennsylvania State University, State College, PA, 3University of Maryland Baltimore, Baltimore, MD
First Author:
Co-Author(s):
Introduction:
Sleep is fundamental to normal body and brain function. Short-term sleep loss may affect cognitive function and long-term sleep loss is associated with neurodegeneration. Even in adolescence, insufficient sleep can have long-lasting effects on the brain and cognition. Based on neuroimaging, extensive knowledge about sleep brain mechanisms has been accumulated. However, previous studies are often limited by small sample sizes and inconsistent findings. The goal of this study was to use the large data provided by Human Connectome Project (HCP)(Van Essen, Smith et al. 2013) to study the regional brain patterns associated with sleep quality. We used brain entropy (BEN) mapping (Wang, Li et al. 2014) to characterize regional brain activity at rest. Entropy indicates irregularity and has been demonstrated to be related to cognitive function and disease alterations.
Methods:
Preprocessed resting state fMRI (rsfMRI) data were downloaded from HCP(Glasser, Sotiropoulos et al. 2013, Smith, Beckmann et al. 2013). Sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI) total score collected in HCP. Higher PSQI score means worse sleep quality. BEN maps were calculated using BENtbx (Wang, Li et al. 2014) using the default parameters. 863 subjects (age 22-37 yrs, male/female=401/462) were included. Voxel-wise regression was performed using SPM (Friston, Holmes et al. 1995) to assess the regional BEN vs sleep quality association. Significance level was set to be p<0.005 with a cluster size > 150 voxels. Multiple comparison was conducted at the cluster level through Monte-Carlo simulations (q<0.05) provided by AFNI.
Results:
. PSQI was negatively correlated to cognitions including the general cognition measured by MMSE, inhibition control by Flanker test, fluid capability by card sorting and Penn Matrix Test, decision making by Flanker and delayed discount, episodic memory by picture sequencing, working memory by list sorting, and processing speed. Fig. 1 shows that BEN is negatively correlated with PSQI score with lower BEN in medial prefrontal cortex, amygdala, putamen, posterior thalamus, insula, middle temporal cortex, left dorso-lateral prefrontal cortex (DLPFC), dorsal anterior cingulate cortex (dACC), and left angular gyrus was related to worse sleep quality. Medial prefrontal cortex, temporal cortex, and angular gyrus are part of the default mode network (DMN). dACC, anterior insula, amygdala, striatum are part of the salience network. DLPFC is part of the attention network. Previous studies have shown increased resting state activity magnitude, regional coherence, and functional connectivity in insula(Wang, Li et al. 2022), salience network(Chen, Chang et al. 2014, Liu, Guo et al. 2018, Yin, Jiang et al. 2024), and DMN(Callow, Spira et al. 2024) in sleep deprivation or patients with insomnia. As lower entropy corresponds to higher coherence, the negative BEN vs PSQI correlation means that more coherent (lower entropy) resting state brain activity is correlated with worse sleep quality, which is consistent with the aforementioned studies, but differed from previous studies by identifying sleep related patterns in the three major networks in a single study.
·Fig. 1. BEN is negatively related to PSQI. Lower BEN correlates with worse sleep quality.
Conclusions:
This study for the first time identified sleep quality related regional brain activity patterns in DLPFC, DMN, and salience network. One reason for the higher resting state activity coherence in worse sleep could be the brain's attempt to maintain stable cognitive and emotional functioning despite sleep disruptions. This postulation is supported by the negative correlation between sleep quality and cognitive function. Another explanation for the negative correlation could be the reduced flexibility and vigilance after sleep disruptions. Vigilance is related to the brain capacity to process information dynamically and flexibly, often involving regions such as the prefrontal cortex and salience network.
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis 2
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 1
Keywords:
Sleep
1|2Indicates the priority used for review
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Provide references using APA citation style.
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