{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T04:56:06Z","timestamp":1789448166397,"version":"build-2803163510"},"reference-count":205,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Introduction: Schizophrenia is characterised by distributed abnormalities in electrophysiological dynamics and large-scale brain networks, yet unimodal EEG or MRI alone cannot fully explain how fast neural computations relate to spatially organised circuit dysfunction. Multimodal EEG\u2013MRI approaches offer a bridge across temporal and anatomical scales by explicitly modelling cross-modal coupling. Methods: Following PRISMA 2020 guidance, we conducted a systematic, mechanistic review of human studies (adults \u2265 18 years) comparing schizophrenia-spectrum groups with healthy controls using EEG combined with at least one MRI modality (fMRI, structural MRI, and\/or diffusion MRI) and explicit EEG\u2013MRI integration (e.g., EEG-informed fMRI, joint ICA, mCCA\/MCCA, coupled matrix\u2013tensor factorisation, DCM-based fusion). Searches were performed in PubMed\/MEDLINE, Embase, Web of Science, Scopus, PsycINFO, IEEE Xplore, ResearchGate, and Google Scholar for January 2000\u2013December 2025, supplemented by citation tracking. Risk of bias was assessed with ROBINS-I, and due to heterogeneity, results were synthesised narratively by integration of families. Results: From 148 records, 23 studies met the inclusion criteria. Studies used mainly simultaneous EEG\u2013fMRI at 3T and spanned resting-state designs and task paradigms dominated by auditory processing (oddball, MMN\/N100\u2013P200, ASSR\/aeGBR), with additional work in affective context, working memory, semantic processing (N400), sensory gating, and pharmacologic challenge. Across tasks, the most reproducible multimodal signature was disrupted coupling between electrophysiological markers and the recruitment of large-scale networks, rather than isolated changes in EEG or fMRI metrics. Target detection\/oddball paradigms converged on reduced late ERP responses (especially P300, sometimes N2) alongside reduced expression or loss of coupling to salience\/ventral attention and control circuitry (including ACC\/anterior insula\/TPJ). Resting-state studies most consistently indicated altered \u201ccoupling rules\u201d (frequency specificity, timing\/lag structure, and directionality), including abnormalities detectable even when unimodal summaries were weak. Extended multimodal studies (adding sMRI\/DTI and\/or classification) suggested that combining modalities can improve discrimination, though performance was sensitive to sample size, demographic imbalance, and feature-selection\/validation choices. Conclusions: Multimodal EEG\u2013MRI studies support schizophrenia as a disorder involving persistent structural and circuit-level abnormalities whose functional expression varies dynamically across cognitive states and task demands. Future progress will depend on harmonised acquisition\/artefact-control practices for simultaneous EEG\u2013fMRI, larger and more diverse samples (including early\/CHR and longitudinal designs), and cross-site replication of mechanistically interpretable coupling biomarkers.<\/jats:p>","DOI":"10.3390\/jcm15114306","type":"journal-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T11:25:31Z","timestamp":1780399531000},"page":"4306","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multimodal EEG\u2013MRI Neuroimaging in Schizophrenia\u2014A Systematic and Mechanistic Review"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5320-3658","authenticated-orcid":false,"given":"James","family":"Chmiel","sequence":"first","affiliation":[{"name":"Institute of Physical Culture Sciences, Faculty of Physical Culture and Health, University of Szczecin, Al. Piast\u00f3w 40B Block 6, 71-065 Szczecin, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3936-0698","authenticated-orcid":false,"given":"Marta","family":"Kopa\u0144ska","sequence":"additional","affiliation":[{"name":"Department of Medical Communication and Professional Competency Development, Faculty of Medicine, Collegium Medicum, University of Rzesz\u00f3w, 35-310 Rzesz\u00f3w, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1016\/j.biopsych.2015.08.025","article-title":"A Meta-Analysis of Mismatch Negativity in Schizophrenia: From Clinical Risk to Disease Specificity and Progression","volume":"79","author":"Erickson","year":"2016","journal-title":"Biol. 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