Left-right information flow in the brain during EEG arousals

Area of Science:

• Neuroscience
• Sleep Medicine
• Biomedical Engineering

Background:

• Sleep fragmentation, characterized by frequent electroencephalogram arousals (EEGA), is common in sleep disorders like sleep apnea.
• Electroencephalogram arousal (EEGA) is a complex phenomenon crucial for understanding sleep mechanisms.
• Inter-hemispheric asynchrony (IHA) reflects information flow between brain hemispheres, but its role during EEGA is not well understood.

Purpose of the Study:

• To investigate the information flow between brain hemispheres during electroencephalogram arousal (EEGA) events.
• To analyze inter-hemispheric asynchrony (IHA) in different frequency bands during EEGA.
• To determine the relationship between EEGA duration and the onset of IHA.

Main Methods:

• Collected electroencephalogram (EEG) data from 5 subjects during polysomnography (PSG) using the international 10-20 system electrodes (A1/C4 and A2/C3).
• Computed the spectral correlation coefficient (R) between EEG signals from both hemispheres in delta, theta, alpha, and beta frequency bands during EEGA events.
• Classified EEGA events into micro (3-6s), short (6.1-10s), and long (10.1-15s) arousals.

Main Results:

• Inter-hemispheric asynchrony (IHA) in the beta band increased post-EEGA onset and returned to baseline post-event.
• A direct correlation was observed between the duration of EEGA events and the onset of IHA.
• Latency (L) between arousal onset and IHA onset varied with arousal duration: L=2±0.5s (micro), 4±2.2s (short), and 6.5±3.6s (long).

Conclusions:

• Beta band IHA is a sensitive indicator of brain activity changes during EEGA.
• The duration of sleep arousals significantly influences the timing of inter-hemispheric communication changes.
• Findings provide novel insights into the neurophysiological mechanisms underlying sleep fragmentation and arousal processes.