Unveiling Neural Signatures: A Comprehensive Review of EEG Biomarkers in Stress, Anxiety, and Depression

Unveiling Neural Signatures: A Comprehensive Review of EEG Biomarkers in Stress, Anxiety, and Depression

Článek WoS

Electroencephalography (EEG) is a widely used noninvasive technique that helps to explore brain activity related to various mental health disorders. It also provides valuable information on the local neural processes that underlie these conditions. This review summarizes recent studies on EEG-based biomarkers associated with stress, generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), major depressive disorder (MDD), bipolar disorder (BDD), and psychotic depressive disorder (PDD). It includes key EEG measures such as event-related potentials (ERPs), frequency domain oscillations, hemispheric asymmetry, neural connectivity, time domain complexity, and microstate dynamics. Using these, it becomes possible to identify brain patterns that are shared between disorders or specific to individual disorder. These findings provide a better understanding of how emotional and cognitive regulation is altered in mental health conditions. The review also emphasizes the growing need for EEG biomarkers to track changes in brain function over time and evaluate treatment-related effects, ultimately deepening our understanding of mental health disorders.

Electroencephalography (EEG) is a widely used noninvasive technique that helps to explore brain activity related to various mental health disorders. It also provides valuable information on the local neural processes that underlie these conditions. This review summarizes recent studies on EEG-based biomarkers associated with stress, generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), major depressive disorder (MDD), bipolar disorder (BDD), and psychotic depressive disorder (PDD). It includes key EEG measures such as event-related potentials (ERPs), frequency domain oscillations, hemispheric asymmetry, neural connectivity, time domain complexity, and microstate dynamics. Using these, it becomes possible to identify brain patterns that are shared between disorders or specific to individual disorder. These findings provide a better understanding of how emotional and cognitive regulation is altered in mental health conditions. The review also emphasizes the growing need for EEG biomarkers to track changes in brain function over time and evaluate treatment-related effects, ultimately deepening our understanding of mental health disorders.

BDD | EEG | GAD | MDD | PD | PDD | SAD | Stress

BDD | EEG | GAD | MDD | PD | PDD | SAD | Stress

Muhammad Asad Zaheer Aamir Saeed Malik

22.01.2026

Institute of Electrical and Electronics Engineers Inc.

IEEE Transactions on Affective Computing

17

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Spojené státy americké

61

76

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https://www.computer.org/csdl/journal/ta/2026/01/11361139/2dum9mZNImQ