An analysis of sleep quality and resting state global transition energy in young adults
Poster No:
1590
Submission Type:
Abstract Submission
Authors:
Anthony Villegas1, Amy Kuceyeski2, Parker Singleton3, Keith Jamison2
Institutions:
1Weill Cornell Medicine, Maspeth, NY, 2Weill Cornell Medicine, New York City, NY, 3Weill Cornell Medicine, New York, NY
First Author:
Co-Author(s):
Introduction:
Approximately 1 in 3 adults in the United States report insufficient rest or sleep, a widespread issue with significant public health implications. Poor sleep quality extends beyond fatigue, impacting cognitive processes and contributing to mental health disorders. Inadequate sleep is linked to adverse effects on working memory, executive function, and decision-making (Zavecz 2020), and with anxiety and depression (Abdelhack 2023; Dietch 2016). The complex relationship between sleep quality and brain functionality necessitates innovative approaches for characterization and diagnosis. Heterogeneity in outcomes among those with poor sleep quality underscores the limitations of conventional measures, emphasizing the need for novel biological markers.
Methods:
We used high-resolution, preprocessed MRI data from the Human Connectome Project – Young Adult S1200 dataset (van Essen 2013). Regional time-series and structural connectomes were extracted from 958 HCP subjects using the 268-region Shen atlas and deterministic tractography. K-means clustering and network control theory-based transition energy (TE) calculations were employed to characterize brain states. TE represents the minimum energy input within the structural connectome needed for transitioning between brain activity states (Gu 2015). Average TE quantified overall energy requirements for transitions across four brain states. The Pittsburgh Sleep Quality Index (PSQI) assessed sleep quality, and ordinary least squares regression explored the relationship between average TE and sleep quality, accounting for age, sex, and mean framewise displacement as covariates.
Results:
Significant main effects of PSQI scores on average global transition energy were found, with interactions between PSQI scores and age and framewise displacement.
·OLS regression results: Significant main effects of PSQI scores on average global transition energy were found, with interactions between PSQI scores and age and framewise displacement.
Conclusions:
This study provides evidence of the influence of sleep quality, as assessed by the PSQI, on resting-state global transition energy among young adults. Our findings suggest that individuals with poorer sleep quality may exhibit alterations in brain activity, reflecting a less dynamic system characterized by reduced complexity and higher energetic barriers. In contrast, those with better sleep quality may demonstrate a more robust and intricate neural network, highlighting the potential implications of sleep quality on the overall dynamism of the brain. These insights contribute to our understanding of the neurobiological underpinnings of sleep quality and underscore the importance of considering sleep-related factors in assessing brain dynamics.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 2
Keywords:
FUNCTIONAL MRI
Sleep
1|2Indicates the priority used for review
Provide references using author date format
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Singleton, S.P (2022), ‘Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape’, Nature Communications, 13, 5812
Van Essen DC (2013), ‘The WU-Minn Human Connectome Project: an overview’, Neuroimage. 15;80:62-79.
Zavecz Z (2020), ‘The relationship between subjective sleep quality and cognitive performance in healthy young adults: Evidence from three empirical studies’, Sci Rep, 10(1):4855.