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Related Concept Videos

Sleep Apnea01:21

Sleep Apnea

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Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea.

Lifeng Li1,2, Qimeng Shi3, Bowen Fang4

  • 1Jiangxi Provincial Key Laboratory for Precision Pathology and Intelligent Diagnosis, Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Brain and Behavior
|July 27, 2025
PubMed
Summary

Obstructive sleep apnea (OSA) alters brain connectivity in motor regions, impacting cognition and increasing accident risks. Machine learning models, particularly support vector machine (SVM), show promise in diagnosing OSA using these brain patterns.

Keywords:
functional connectivityobstructive sleep apneaprimary motor cortexsubregionsupport vector machine

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Sleep Medicine

Background:

  • Obstructive sleep apnea (OSA) is associated with cognitive deficits and changes in motor-related brain networks.
  • Understanding functional connectivity (FC) alterations in the primary motor cortex (M1) is crucial for comprehending OSA's neurological impact.

Purpose of the Study:

  • To investigate functional connectivity (FC) changes in primary motor cortex (M1) subregions in patients with obstructive sleep apnea (OSA).
  • To explore the association of these FC changes with sleep structure, cognitive function, and clinical features.
  • To evaluate the potential of FC patterns in distinguishing OSA patients from healthy controls (HC) using machine learning.

Main Methods:

  • Resting-state functional MRI (fMRI) data were collected from 65 OSA patients and 65 matched HC participants.
  • Functional connectivity (FC) of 12 M1 subregions was analyzed using the Human Brainnetome Atlas.
  • Statistical analyses included t-tests, partial correlations, and machine learning algorithms (SVM, RF, LR) for classification.

Main Results:

  • Significant FC enhancements were observed in specific M1 subregions (e.g., A6cdl, A4tl, A6cvl) in OSA patients compared to HC.
  • A negative correlation was found between FC in the left A4tl-IPL region and N2 scores.
  • Support vector machine (SVM) demonstrated the highest accuracy in discriminating OSA patients from HC based on FC features.

Conclusions:

  • Obstructive sleep apnea (OSA) significantly alters functional connectivity (FC) in M1 subregions, impacting motor control and cognitive function.
  • These FC alterations correlate with clinical features and may increase accident risks.
  • FC patterns identified via SVM show potential as a diagnostic biomarker for OSA.