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Multiplicity of the alpha rhythm in normal humans
V A Feshchenko1, R A Reinsel, R A Veselis
1Department of Anesthesiology and Critical Care Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Summary
This study reveals up to three distinct alpha rhythms in the human brain, identified using electroencephalography (EEG). These rhythms, including a novel frontal alpha rhythm, show reproducible individual characteristics.
Area of Science:
- Neuroscience
- Neurophysiology
Background:
- The alpha rhythm in electroencephalography (EEG) has been understood as narrowband filtration of broadband processes.
- Previous analyses focused on single derivations, limiting a comprehensive understanding of alpha rhythm complexity.
Purpose of the Study:
- To differentiate and characterize multiple distinct alpha rhythms within each brain hemisphere.
- To investigate the spatial and dynamic properties of alpha rhythms.
- To identify reliable individual EEG characteristics for describing the 'normal' EEG.
Main Methods:
- Analysis of electroencephalography (EEG) data from 65 resting, awake subjects.
- Utilized cross-correlation measurements of rhythmic and broadband processes.
- Compared dynamic characteristics of oscillatory systems underlying alpha rhythms.
- Recorded five-minute EEG epochs for precise statistical estimates.
Main Results:
- Identified up to three distinct alpha rhythms per hemisphere based on spatial and dynamic properties.
- Discovered a frontal alpha rhythm, independent of occipital activity, present in 20% of subjects.
- This frontal rhythm is distinct from known alpha and mu rhythms and attenuates with open eyes.
- Demonstrated reproducible dynamic characteristics and intrahemispheric cross-correlation coefficients over time within individuals.
Conclusions:
- The dynamic characteristics and cross-correlation patterns of alpha rhythms are reliable individual EEG markers.
- High correlation in symmetric derivations may stem from symmetric afferent impulse flows, not just structural connections.
- Findings contribute to a more nuanced understanding of the "normal" EEG and individual brain activity patterns.