Exploring the changes in brain network SC-FC coupling patterns of partial sleep deprivation based on DTI-fMRI fusion analysis

TL;DR

This study uses DTI and fMRI fusion to analyze brain network changes in partial sleep deprivation, revealing significant disruptions in connectivity and their links to emotional dysfunction, providing new biomarkers for sleep-related neural damage.

Contribution

It introduces an integrated SC-FC coupling method combining DTI and rs-fMRI to comprehensively detect brain network abnormalities in partial sleep deprivation.

Findings

Severe FC disruptions in limbic, DMN, sensorimotor, and visual networks.

Altered structural connectivity in multiple brain networks.

Significant SC-FC decoupling correlating with clinical scores.

Abstract

Sleep disorder is a serious global public health issue, with cognitive-emotional dysfunction being a core symptom. The analysis of multimodal MRI data provides an effective method for detecting sleep deprivation-induced neural network abnormalities. The structure-function coupling (SC-FC) integrates functional connectivity with white matter structural information, which can enable comprehensive detection of brain network abnormalities and offer quantitative measures of sleep deprivation-induced neural damage. This study integrates diffusion tensor imaging (DTI) and resting-state fMRI (rs-fMRI) to systematically investigate brain network reorganization and their relationship with emotional functions in partial sleep deprivation (PSD). Our methodology employed DTI to construct structural connectivity (SC) networks and rs-fMRI to establish functional connectivity (FC) networks, then construct SC-FC coupling model . The experiment included 16 healthy controls (HC) and 20 PSD patients, with comprehensive whole-brain and nodal-level SC-FC analyses performed. The results show that (1) severe FC disruptions in PSD patients involving the limbic system, default mode network, sensorimotor network, and visual networks; (2) altered SC in default mode, sensorimotor, visual, language, and auditory networks; (3) significant SC-FC decoupling in these networks; and (4) strong correlations between these neural changes and clinical measures (KSQ and HADS scores). The SC-FC coupling approach achieved comprehensive detection of PSD-related network abnormalities. Compared to single-modal approaches, this integrated SC-FC analysis provides more comprehensive biomarkers for sleep-related emotional dysregulation. This innovative multimodal neuroimaging approach elucidates the neural mechanisms of SC-FC imbalance induced by PSD, establishing novel biomarkers for sleep-mediated emotional dysregulation.