Simultaneous EEG–fMRI in Major Depressive Disorder: A Systematic Review of Brain Networks, Neurovascular Coupling, and Clinical Correlates

Background: Simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) offers unique potential to characterize brain network dysfunction, neurovascular coupling alterations, and clinical associations in major depressive disorder (MDD). However, the field lacks a rigorous synthesis of evidence restricted to rigorously defined MDD populations with true multimodal integration.Objectives: To systematically review simultaneous EEG-fMRI studies in MDD, narratively synthesize clinical correlations between EEG-fMRI metrics and anhedonia severity, and characterize the heterogeneity of methodological approaches across clinical outcomes.Methods: We conducted a systematic review (PROSPERO: CRD420261292902) following PRISMA 2020 guidelines[32]. We searched PubMed, Google Scholar, Scopus, and CENTRAL (inception to March 2026) for studies using simultaneous EEG-fMRI in adults (≥18 years) with MDD. To ensure diagnostic specificity, we excluded studies on healthy populations, subclinical samples (without confirmed MDD), sequential acquisition studies, and those without formal EEG-fMRI integration. Primary outcomes included brain network dysfunction markers, neurovascular coupling differences, and clinical associations. Due to the paucity of studies (<3) for most outcomes, narrative synthesis was performed. Risk of bias was assessed using modified ROB2, ROBINS-I, and JBI tools.Results: Nine studies (reporting data from eight distinct cohorts; N=377 participants) met strict inclusion criteria. The analysis identified two reports from a single cohort investigating anhedonia using neurofeedback (Zotev et al., 2016 & 2020), reporting moderate-to-strong positive correlations (r = 0.47 and r = 0.69) between EEG-fMRI metrics and anhedonia severity[49,48]. Narrative synthesis of other outcomes revealed effect sizes for anxiety (r = 0.74), depression change (r = -0.38 to 0.90), and rumination (r = 0.20)[48,43,15,44]. Heterogeneity in analytical approaches was substantial. Evidence certainty was rated low for most outcomes due to risk of bias and imprecision.Conclusion: While simultaneous EEG-fMRI can identify strong neurophysiological correlates of symptoms like anhedonia and treatment response in active experimental contexts (e.g., neurofeedback, ketamine), the evidence for generalizable resting-state biomarkers in MDD remains insufficient. The field is currently hindered by methodological fragmentation and small sample sizes. Future efforts must prioritize standardized analytical pipelines and large-scale, multi-center cohorts to transition simultaneous EEG-fMRI from a mechanistic research tool to a viable clinical biomarker.