{
  "abstract": "Purpose\n\nEEG functional-connectivity studies in major depressive disorder (MDD) have produced inconsistent findings, partly because different estimators capture distinct aspects of neural coupling. We implemented a multi-metric resting-state EEG approach combining linear, phase-based, nonlinear, and graph-theoretical measures to characterize frequency-dependent sensor-level connectivity alterations and identify sensor-level network patterns relevant to depression-related dysconnectivity.Method\n\nResting-state EEG from 30 DSM-IV MDD participants and 28 healthy controls was analyzed using a 19-channel 10-20 montage. After MNE-Python preprocessing, including filtering, ICA-based artifact removal, current source density (CSD) transformation, and symmetric orthogonalization, coherence, PLV, PLI, and MI were computed across theta, alpha, and beta bands. Edge-wise differences were tested using Brunner-Munzel with Holm correction, confirmed with Westfall-Young maxT correction, and summarized using Hedges' g and graph measures.Finding\n\nMDD showed frequency- and metric-dependent sensor-level connectivity alterations. Theta coherence, PLV, and PLI were dominated by lower connectivity across frontal-to-posterior, fronto-central, temporal/posterior-temporal, parieto-occipital, and central-to-occipital sensor pairs, whereas theta MI showed few increased frontal/fronto-temporal effects. Alpha findings were more selective, with mainly lower coherence and PLV across frontopolar/frontal-to-central, fronto-midline, and posterior links, while alpha MI showed a limited mixed pattern. In beta, coherence, PLV, and PLI showed sparse robust reductions, whereas beta MI showed widespread increased statistical dependence. Graph-theoretical summaries at 20% proportional density showed mainly lower mean weighted strength and global efficiency in theta- and alpha-band networks.Conclusion\n\nThese findings indicate frequency- and metric-dependent resting-state EEG sensor-level connectivity alterations in MDD. The dominant pattern was lower theta/alpha connectivity across distributed sensor pairs, alongside increased beta MI-based dependence. The results provide corrected, effect-size-informed evidence of altered inter-sensor coordination without establishing dysfunction of specific cortical regions or named networks. This framework may support future hypothesis-driven research in independent, clinically annotated, higher-density EEG or multimodal datasets.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Computer Science and Engineering, Varendra University, Rajshahi, Bangladesh.",
    "Center For Interdisciplinary Research, Varendra University, Rajshahi, Bangladesh.",
    "Professor Emeritus of Mathematical Sciences, Ball State University, Muncie, Indiana, USA."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Sushmit Jahan Rose"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "A H M Rahmatullah Imon"
    },
    {
      "affs": [
        0
      ],
      "name": "Rushdania Bushra"
    },
    {
      "affs": [
        0
      ],
      "name": "Nafis Ahmed"
    },
    {
      "affs": [
        0
      ],
      "name": "Moha Tasneem Habib Warid"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/14g8e2msy6xkf.bib",
  "cited_by": 0,
  "doi": "10.1002/brb3.71842",
  "fulltext_url": "https://europepmc.org/articles/PMC13684065",
  "id": "14g8e2msy6xkf",
  "issns": [
    "2162-3279"
  ],
  "landing_url": "https://europepmc.org/article/MED/42902871",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2805|Functional Brain Connectivity Studies"
    ]
  ],
  "openalex": "W7223131530",
  "pdf_url": "https://europepmc.org/articles/PMC13684065?pdf=render",
  "pmcid": "PMC13684065",
  "pmid": "42902871",
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/14g8e2msy6xkf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:57Z",
      "native_id": "MED:42902871",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42902871"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Functional Brain Connectivity Studies",
      "subfield": "neuroscience"
    }
  ],
  "title": "Multi-Metric EEG Connectivity and Graph Analysis Reveal Altered Resting-State Networks in Major Depressive Disorder.",
  "title_text": "Multi-Metric EEG Connectivity and Graph Analysis Reveal Altered Resting-State Networks in Major Depressive Disorder.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:57Z",
  "url": "https://research.draconitic.com/paper/14g8e2msy6xkf",
  "venue": "Brain and behavior",
  "versions": []
}