Sleep-Dependent Anomalous Cortical Information Interaction in Patients With Depression

Area of Science:

• Neuroscience
• Psychiatry
• Computational Neuroscience

Background:

• Depression is a leading cause of global disability, significantly impacting mental health.
• Altered brain activity during sleep is a known consequence of depression.
• Understanding cortical information flow during sleep is crucial for identifying depression-related neurological changes.

Purpose of the Study:

• To investigate alterations in cortical information flow during sleep in individuals with depression.
• To measure effective connectivity between cortical regions using electroencephalography (EEG) signals.
• To identify potential biomarkers for depression diagnosis based on sleep-related brain activity.

Main Methods:

• Utilized delay symbolic phase transfer entropy (dsPTE) analysis on scalp EEG signals.
• Examined effective connectivity across different frequency bands and sleep stages.
• Compared information flow patterns between a patient group and a healthy control group.

Main Results:

• Both groups exhibited similar overall information flow patterns during sleep, with a tendency towards the left hemisphere and anterior cortex.
• The occiput acted as an information source, while frontal regions served as receivers, and the right hemisphere showed stronger information drive than the left.
• Depressed patients displayed weakened directional information flow and less distinct regional roles compared to controls, except in the beta band during N1 sleep stage.

Conclusions:

• Sleep-dependent cortical interaction patterns are altered in depression.
• Quantifiable changes in effective connectivity during sleep may serve as indicators of cortical abnormalities in depression.
• These findings suggest potential for EEG-based biomarkers in diagnosing depression.