Electroencephalogram Microstate Abnormalities in Early-Course Psychosis

Area of Science:

• Neuroscience
• Psychiatry
• Computational Neuroscience

Background:

• Electroencephalography (EEG) microstates reflect brain network activity.
• Abnormal microstate parameters are observed in psychotic disorders.
• Early-course psychosis presents unique challenges for understanding brain dynamics.

Purpose of the Study:

• To investigate resting-state network dynamics in early-course psychosis using microstate and sample entropy analysis.
• To identify alterations in brain network transitions associated with psychosis.

Main Methods:

• High-density EEG data from 22 early-course psychosis patients and 22 controls were analyzed.
• Microstate analysis identified characteristic scalp topographies.
• Sample entropy quantified the complexity of microstate transition sequences.

Main Results:

• Patients and controls showed similar microstate sets (A, B, C, D).
• Patients had decreased frequency of microstate A and lacked self-similarity in microstate transitions.
• Elevated entropy in unmedicated patients decreased with medication; specific transition patterns differed between groups.

Conclusions:

• Early-course psychosis is associated with abnormally chaotic brain network transitions.
• This chaos may stem from impaired neural resource allocation and state transitions.
• Microstate and entropy analysis offer insights into psychosis pathophysiology.