Neuroimaging Insights into the Public Health Burden of Neuropsychiatric Disorders: A Systematic Review of Electroencephalography-Based Cognitive Biomarkers
<i>Background and Objectives</i>: Neuropsychiatric disorders, including schizophrenia, bipolar disorder, and major depression, constitute a leading global public health challenge due to their high prevalence, chronicity, and profound cognitive and functional impact. This systematic revie...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Medicina |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1648-9144/61/6/1003 |
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| Summary: | <i>Background and Objectives</i>: Neuropsychiatric disorders, including schizophrenia, bipolar disorder, and major depression, constitute a leading global public health challenge due to their high prevalence, chronicity, and profound cognitive and functional impact. This systematic review explores the role of electroencephalography (EEG)-based cognitive biomarkers in improving the understanding, diagnosis, monitoring, and treatment of these conditions. It evaluates how EEG-derived markers can reflect neuro-cognitive dysfunction and inform personalized and scalable mental health interventions. <i>Materials and Methods</i>: A systematic review was conducted following PRISMA guidelines. The databases searched included PubMed, Scopus, PsycINFO, and Web of Science for peer-reviewed empirical studies published between 2014 and 2025. Inclusion criteria focused on EEG-based investigations in clinical populations with neuropsychiatric diagnoses, emphasizing studies that assessed associations with cognitive function, symptom severity, treatment response, or functional outcomes. Of the 447 initially identified records, 132 studies were included in the final synthesis. <i>Results:</i> This review identifies several EEG markers—such as mismatch negativity (MMN), P300, frontal alpha asymmetry, and theta/beta ratios—as reliable indicators of cognitive impairments across psychiatric populations. These biomarkers are associated with deficits in attention, memory, and executive functioning, and show predictive utility for treatment outcomes and disease progression. Methodological trends indicate an increasing use of machine learning and multimodal neuroimaging integration to enhance diagnostic specificity. While many studies exhibit moderate risk of bias, the overall findings support EEG biomarkers’ reproducibility and translational relevance. <i>Conclusions</i>: EEG-based cognitive biomarkers offer a valuable, non-invasive means of capturing the neurobiological underpinnings of psychiatric disorders. Their diagnostic and prognostic potential, as well as high temporal resolution and portability, supports their use in clinical and public health contexts. The field, however, requires further standardization, cross-validation, and investment in scalable applications. Advancing EEG biomarker research holds promise for precision psychiatry and proactive mental health strategies at the population level. |
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| ISSN: | 1010-660X 1648-9144 |