Brain Oscillations in Bipolar Disorder: Insights from Quantitative EEG Studies
Amir Reza Bahadori1, Erfan Naghavi2, Pantea Allami2,3
1Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
Clinical EEG and Neuroscience
|July 29, 2025
Summary
Quantitative electroencephalography (QEEG) shows promise for diagnosing bipolar disorder (BD). This neurophysiological tool reveals distinct brainwave patterns, aiding in differentiating BD from other conditions and guiding treatment.
Area of Science:
- Neuroscience
- Psychiatry
- Biomarker Research
Background:
- Bipolar disorder (BD) presents diagnostic and therapeutic challenges due to mood fluctuations.
- Reliable biomarkers are crucial for effective management of BD.
- Quantitative electroencephalography (QEEG) analyzes brain oscillations, offering potential insights into neurological conditions.
Purpose of the Study:
- To systematically review QEEG alterations in bipolar disorder (BD) patients.
- To assess the diagnostic and therapeutic utility of QEEG in BD.
- To differentiate BD from major depressive disorder (MDD) and schizophrenia using QEEG.
Main Methods:
- A systematic review adhering to PRISMA 2020 guidelines.
- Comprehensive literature search across PubMed, Scopus, Web of Science, and Embase.
- Inclusion of studies assessing BD patients with QEEG, focusing on frequency band analysis, treatment response, and diagnostic differentiation.
Main Results:
- Twenty studies involving 475 BD patients were analyzed.
- Consistent increases in gamma and beta activity observed in BD.
- Variable alpha and theta band changes noted; delta band alterations more prominent in BD I.
- QEEG differentiated BD from MDD and schizophrenia based on distinct frequency band characteristics.
Conclusions:
- QEEG shows significant potential as a diagnostic and therapeutic tool for bipolar disorder.
- Integration with machine learning may enhance diagnostic accuracy and personalize treatments.
- Further research is needed to standardize QEEG methodologies and validate findings for clinical application.
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