[The nonstability of the EEG: a methodological and experimental analysis]

Area of Science:

• Neuroscience
• Computational Neuroscience
• Signal Processing

Context:

• Electroencephalography (EEG) analysis often assumes stationarity, which does not reflect the dynamic nature of brain activity.
• Nonstationary EEGs, where patterns change over time, present significant analytical challenges.
• Understanding the temporal dynamics of brain activity is crucial for diagnosing neurological disorders.

Purpose:

• To review theoretical, methodological, and methodical aspects of analyzing nonstationary EEGs.
• To confirm the piecewise description of EEGs using existing data and new findings.
• To introduce the concept of "operational synchrony" for understanding cortex process cooperation.

Summary:

• The study confirms the piecewise nature of nonstationary EEGs, supported by empirical data and prior research.
• It examines statistical evaluation methods for nonstationary EEGs, focusing on quasi-stationary segments.
• The concept of "operational synchrony" is proposed to describe the discrete cooperation of cortical processes, based on segmental organization and time consistency.

Impact:

• Provides a framework for analyzing complex, time-varying brain signals.
• Enhances understanding of neural network functioning and cortical dynamics.
• Offers new theoretical explanations for the piecewise operation of neural networks.