Unveiling Compromised Control Networks in Insomnia: Insights from Functional and Structural MRI
Poster No:
527
Submission Type:
Abstract Submission
Authors:
Yun Tian1, Haobo Zhang2, shiyan yang3, Shuo Wang1, Linman Weng1, lei xu3
Institutions:
1Southwest University, Chongqing, Chongqing, 2southwest university, Chongqing, Chongqing, 3southwest university, chongqing, China
First Author:
Co-Author(s):
Introduction:
Insomnia, a prevalent sleep disorder, not only affects sleep quality but also potentially impacts daytime functioning and brain dynamics(Van Someren, 2021). However, a comprehensive understanding of changes in brain networks, both functionally and structurally, among individuals with insomnia remains incomplete. This study aims to explore functional and structural alterations in cerebral networks among insomnia patients, utilizing functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) to provide evidence supporting the link between insomnia and cerebral networks.
Methods:
We recruited 43 diagnosed insomnia patients and 41 healthy control volunteers for resting-state fMRI and sMRI scans. Fmriprep, along with embedded FreeSurfer, was used to preprocess resting-state images and structural images (Esteban et al., 2019; Fischl, 2012). For structural metrics, differences between healthy and insomnia groups were analyzed across nine indices covering whole-brain measures, including curvature index, folding index, Gaussian curvature, grey matter volume, mean curvature, vertex count, surface area, cortical thickness standard deviation, and mean cortical thickness. Regarding functional images, differences between healthy and insomnia groups in provincial hub and connector hub of eight brain networks were investigated from a functional hub perspective (Bertolero et al., 2018). FDR correction was applied.
Results:
Insomnia participants exhibited structural abnormalities solely in the right inferior orbital frontal gyrus of the control network, showing significantly lower values in curvature index, folding index, Gaussian curvature, grey matter volume, mean curvature, vertex count, cortical surface area, and cortical thickness standard deviation compared to the healthy group, with only mean thickness showing no significant differences (Fig 1). Simultaneously, the fMRI data unveiled a notable decrease in connector hub strength (specifically in the right dorsal prefrontal cortex) within the control network among insomnia patients (Fig 2). Conversely, no substantial differences were detected in the provincial hub.
·Abnormalities in cortical structure in insomnia patients
·Abnormalities in functional network hubs in insomnia patients
Conclusions:
This study provides evidence of impaired functionality and structure in control networks among insomnia patients, supporting the association between insomnia and control networks. These findings hold promise for advancing our understanding of the pathophysiological mechanisms underlying insomnia and may offer potential neurobiological targets for future interventions and treatments.
Brain Stimulation:
Non-invasive Magnetic/TMS
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Keywords:
FUNCTIONAL MRI
Psychiatric Disorders
Sleep
STRUCTURAL MRI
1|2Indicates the priority used for review
Provide references using author date format
Esteban, O. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods, 16(1), 111-116.
Fischl, B. (2012). FreeSurfer. Neuroimage, 62(2), 774-781.
Van Someren, E. J. W. (2021). Brain mechanisms of insomnia: new perspectives on causes and consequences. Physiol Rev, 101(3), 995-1046.