Previous motor task performance impacts phase-based EEG resting-state connectivity states

Area of Science:

• Neuroscience
• Brain Imaging
• Computational Neuroscience

Background:

• The resting human brain exhibits dynamic states analyzed via electroencephalography (EEG) microstate analysis.
• Microstates, based on EEG topographic features, may serve as biomarkers for neurodegenerative diseases but lack information on active neural networks.
• Current methods do not fully capture the dynamic neural network activity during resting states.

Purpose of the Study:

• To present a novel, reproducible, and reliable method for analyzing resting-state EEG data.
• To investigate cerebral connectivity states using phase synchronization and source-reconstructed EEG.
• To compare the effects of a motor task on traditional microstates versus novel connectivity states.

Main Methods:

• Analysis of resting-state EEG data from young, healthy participants over five consecutive days.
• Application of microstate analysis to classify EEG data into topographic states.
• Measurement of cerebral connectivity states using corrected imaginary phase-locking value (ciPLV) on source-reconstructed EEG.
• Evaluation of data reproducibility and reliability across multiple sessions and conditions.

Main Results:

• The study successfully reproduced previously reported EEG microstates.
• Four stable topographic patterns in source connectivity space were identified across recording sessions.
• Unlike microstates, connectivity states were significantly altered after a preceding motor task.
• The observed alterations in connectivity states reflected suppressed frontal activity in the post-movement resting state.

Conclusions:

• The proposed method provides a complementary approach to microstate analysis for understanding resting-state brain dynamics.
• Cerebral connectivity states, measured by ciPLV, offer insights into neural network activity not captured by microstates.
• Motor tasks induce distinct changes in brain connectivity states, highlighting their sensitivity to recent neural activity.