Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review

Area of Science:

• Neuroscience
• Biophysics
• Computational Neuroscience

Background:

• Electrophysiological data requires interpretation across multiple spatial scales.
• Local field potentials, electrocorticography, and electroencephalography (EEG) arise from micro current sources at cell membrane surfaces.

Purpose of the Study:

• Develop a biophysical framework to interpret multi-scale electrophysiological data.
• Categorize multi-scale neural sources (genuine, equivalent, representative).
• Inform EEG source localization and interpretation of brain dynamics.

Main Methods:

• Categorization of multi-scale neural sources.
• Definition of macro sources (e.g., dipoles) based on micro source properties.
• Analysis of factors influencing the number of representative sources for EEG data.

Main Results:

• Introduced a framework classifying sources as genuine, equivalent, or representative.
• Demonstrated that macro sources depend on micro source magnitudes, synchrony, and cortical depth distribution.
• Highlighted strengths and limitations of EEG inverse solutions and high-resolution estimates.

Conclusions:

• The theoretical framework aids in understanding EEG source localization and characterization.
• Facilitates interpretation of brain dynamics, synchrony, and functional connectivity.
• Enhances the analysis of brain complexity using multi-scale electrophysiological data.