Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ISSN 2694-0604
2 papers in the library · 6 citations · publishing 2019-2024
Cortical networks show differences in functional integration and segregation across states of consciousness, but not in overall connectivity. In the beta frequency band, functional integration during wakefulness exceeded that during NREM sleep. In the theta band, functional segregation (transitivity and clustering coefficient) was stronger in NREM sleep without conscious experience than in wakefulness or REM sleep, while the opposite pattern appeared in the beta band. No significant differences in the weighted phase lag index were found among wakefulness, REM sleep with conscious experience, NREM sleep with conscious experience, and NREM sleep without conscious experience. These findings may relate to cortical bistability and contribute to understanding neural correlates of consciousness.
Meditation's benefits are increasingly recognized, but the brain's electrical activity during meditative states is not fully understood. Existing markers have limited predictive accuracy, suggesting important information is missing. This work converts EEG time series into scale-free networks using horizontal visibility graphs, which distinguish deterministic from random systems and model new aspects of brain oscillations. The authors introduce a class of network-based predictors that outperform popular spectral and nonlinear features like complexity or entropy. These predictors show statistical significance for several meditation types, using data from highly skilled meditators, and are suitable for real-time analysis and applications such as neurofeedback.