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Cortical Source Analysis of High-Density EEG Recordings in Children
Published on: June 30, 2014
Topological Data Analysis Based Characteristics of Electroencephalogram Signals in Children With Sleep Apnea
Aarti Sathyanarayana1,2, Shashank Manjunath2, Jose A Perea2,3
1Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts, USA.
Insights
Pediatric obstructive sleep apnea (OSA) significantly alters brain neural connectivity, even during awake periods. Topological data analysis of EEG signals reveals these differences compared to healthy children, offering new diagnostic insights.
Area of Science:
- Neuroscience
- Sleep Medicine
- Data Science
Background:
- Obstructive sleep apnea (OSA) is prevalent in children and linked to neurological consequences.
- Understanding the impact of OSA on brain functional connectivity is crucial for early diagnosis and intervention.
Purpose of the Study:
- To investigate differences in brain functional neural connectivity in pediatric patients with OSA compared to controls.
- To explore the utility of topological data analysis (TDA) in identifying OSA-related neural alterations.
Main Methods:
- Utilized electroencephalogram (EEG) signals from 3673 pediatric patients.
- Grouped subjects into OSA and control groups based on sleep oxygen desaturation and apnea-hypopnea index (AHI).
- Applied TDA techniques to analyze EEG features and assess functional neural connectivity.
Main Results:
- Statistically significant differences were found in EEG signals during apnea/hypopnea events compared to controls.
- Significant differences emerged in EEG signals during oxygen desaturation events versus controls.
- TDA identified distinct neural connectivity patterns in OSA patients, including during non-desaturation and awake periods, compared to healthy controls.
Conclusions:
- TDA effectively detects statistically significant differences in brain functional connectivity in pediatric OSA patients.
- Findings highlight the pervasive effects of OSA on the central nervous system, extending to awake states.
- This approach offers potential for novel methods in identifying and understanding pediatric sleep apnea.
Abstract:
This study aims to identify differences in the functional neural connectivity of the brain of paediatric patients with obstructive sleep apnea. Using EEG signals from 3673 paediatric patients, we grouped subjects into OSA or control groups based on sleep oxygen desaturation levels and apnea-hypopnea index (AHI), and applied topological data analysis (TDA) techniques. We evaluated our approach through statistical testing of TDA-based EEG features, which indicate fundamental differences in the functional neural connectivity of subjects with sleep apnea as compared to controls. There were statistically significant differences ( ) between EEG signals taken during apnea and hypopnea events as compared to those taken from healthy controls. No significance was found between the latent EEG signals within the same groups. We observed significant differences between EEG signals collected during oxygen desaturation as compared to the EEG signals of the controls. We additionally identified significant differences between the latent EEG signals (i.e., no oxygen desaturation event occurring) of subjects as compared with the EEGs from controls. Lastly, significant differences were additionally found in the awake before sleep portion of the polysomnograms when grouping subjects based on minimum oxygen saturation experienced during sleep. TDA techniques allow us to identify statistically significant differences between the EEG signals of subjects with OSA and healthy controls, including during awake periods. Our results provide novel insights on the effects of OSA on the central nervous system, and insights into potential novel methods for identification of sleep apnea.
