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Insomnia is a prevalent sleep disorder characterized by difficulty falling asleep, frequent awakenings during the night, and waking up too early without being able to return to sleep. People with insomnia often experience these disruptions at least three nights a week for at least one month. Chronic insomnia, which lasts for at least three months, can lead to increased anxiety, which in turn can worsen sleep difficulties, creating a cycle of sleeplessness and stress.
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Personalized functional network connectivity abnormalities in chronic insomnia disorder.

Xiaoxuan Li1, Yiran Zhai1, Tianwei Qin1

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Summary

Personalized brain network analysis reveals unique functional connectivity alterations in chronic insomnia disorder (CID). This approach offers new insights into the neurobiology of CID and highlights the value of individualized methods for sleep disorder treatment.

Keywords:
chronic insomnia disorderfunctional network connectivitynon-negative matrix factorizationresting-state functional magnetic mesonance imagingsmall world

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Sleep Medicine

Background:

  • Chronic insomnia disorder (CID) is linked to disrupted brain functional networks.
  • Previous research predominantly used group-level analyses, overlooking individual variations.

Purpose of the Study:

  • To identify specific connectivity abnormalities in CID using personalized functional network mapping.
  • To uncover subject-specific alterations in brain networks associated with chronic insomnia.

Main Methods:

  • Resting-state functional magnetic resonance imaging (rs-fMRI) data from 86 CID patients and 38 good sleeper controls (GSCs).
  • Non-negative matrix factorization (NMF) for deriving individualized brain networks.
  • Functional network connectivity (FNC) matrices and graph-theory metrics for comparing groups.

Main Results:

  • Significant FNC differences between CID patients and GSCs in default mode network (DMN), ventral attention, and visual networks.
  • CID exhibited altered global network topology (higher small-worldness and normalized clustering coefficient).
  • CID showed altered local network properties, including increased efficiency and clustering in the DMN.

Conclusions:

  • Individualized functional connectivity mapping reveals unique neurobiological "fingerprints" in CID.
  • Findings enhance understanding of CID's underlying mechanisms.
  • Personalized network approaches are valuable for diagnosing and treating sleep disorders.