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EEG: Current relevance and promising quantitative analyses.
M Gavaret1, A Iftimovici2, E Pruvost-Robieux1
1Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; Service de Neurophysiologie Clinique et Epileptologie, GHU Paris Psychiatrie et Neurosciences, Paris, France; FHU NeuroVasc, Paris, France.
Revue Neurologique
|March 12, 2023
Summary
Electroencephalography (EEG) provides excellent temporal resolution for studying brain activity. Recent advancements enhance both visual and quantitative EEG analyses for clinical and research applications.
Area of Science:
- Neuroscience
- Biomedical Engineering
Background:
- Electroencephalography (EEG) is a vital, low-cost tool for recording brain electrical activity.
- Its high temporal resolution offers insights into cerebral functions, crucial for clinical diagnostics and research.
- EEG is indispensable for conditions like epilepsy, sleep disorders, and disorders of consciousness, as well as cognitive neuroscience and brain-computer interfaces.
Purpose of the Study:
- To review recent advancements in visual electroencephalography (EEG) analysis.
- To highlight promising quantitative EEG analysis techniques.
- To discuss developments in surface EEG electrodes for continuous monitoring.
Main Methods:
- Overview of current visual EEG analysis techniques.
- Exploration of quantitative EEG analysis methods including event-related potentials, source localization, brain connectivity, and microstates.
- Review of emerging surface EEG electrode technologies.
Main Results:
- Visual EEG analysis is undergoing significant progress.
- Quantitative EEG analyses offer valuable complements to visual interpretation.
- New electrode developments show promise for long-term continuous EEG monitoring.
Conclusions:
- EEG remains a cornerstone in neurology and neuroscience due to its practical and temporal advantages.
- Recent progress in both visual and quantitative EEG analysis methods enhances its utility.
- Emerging technologies are poised to expand the applications of EEG, particularly for continuous monitoring.
