Assessment of EEG synchronization based on state-space analysis

Area of Science:

• Neuroscience
• Computational Neuroscience
• Signal Processing

Background:

• Cortical computation relies on neuronal assemblies with synchronous oscillatory activity.
• Traditional methods like coherence analysis of electroencephalography (EEG) signals are used to identify these assemblies.
• A novel approach is needed to better understand cortical synchrony.

Purpose of the Study:

• To introduce and validate a new method, the S estimator, for quantifying cortical synchrony.
• To investigate how different visual stimuli configurations affect neuronal synchrony in the human cortex.
• To explore the frequency-specific nature of stimulus-induced synchrony changes.

Main Methods:

• Developed the S estimator, defining cortical synchrony via state-space embedding dimension.
• Validated the S estimator on coupled chaotic oscillators, comparing it with existing synchronization assessment methods.
• Recorded high-density EEG from nine adult subjects viewing collinear and orthogonal moving gratings in separate visual hemifields.

Main Results:

• The S estimator showed increased synchrony over occipital electrodes for collinear gratings and decreased synchrony over temporo-parietal regions.
• Orthogonal gratings led to increased synchrony in temporo-parietal regions.
• Occipital synchrony was prominent in the beta band, while temporal synchrony was in the alpha band; the gamma band was unaffected.

Conclusions:

• The S estimator effectively quantifies cortical synchrony and its modulation by visual stimuli.
• Different visual stimulus configurations induce complex, spatially distributed rearrangements of synchronous neuronal assemblies.
• Findings highlight the frequency-specific and region-specific responses of neuronal synchrony within the visual cortex.