{
  "abstract": "Introduction: Altered attention network activity has been consistently reported in recent neuroimaging literature of smartphone addiction and problematic smartphone use. However, many functional imaging studies have relied on traditional static functional connectivity analyses, which cannot capture time-varying or recurrent dynamics of attention networks.\n\nMethods: Given the importance of temporal and spatial dynamics for attentional processing, we applied two complementary dynamic functional connectivity approaches: functional connectivity-based attractor networks (fcANN), which characterize transitions between discrete attractor states related to internal-external context and action-perception dynamics, and cPCA-based quasi-periodic pattern (QPP) analysis, which captures phase relationships between cortical networks including the default mode network, dorsal attention network, and frontoparietal control network.\n\nResults: In a resting-state fMRI dataset comparing participants with High and Low SAS-M scores (SAS-M: Smartphone addiction scale-Malay version questionnaire), we observed context-dependent differences in DMN-attention-network relationships across attractor states. The most consistent effects emerged during transitions between internal and external attractor states, where subjects with high smartphone addiction (SPA) scores showed greater DMN dominance relative to attention-related networks. For DMN-FPN, these differences correlated with subject SAS-M scores.\n\nDiscussion: Overall, these findings provide preliminary evidence that smartphone addiction may be associated with altered large-scale attentional dynamics at rest, warranting further investigation in larger and more diverse samples.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Computer Science of the Czech Academy of Sciences",
    "Department of Psychological Science, Weber State University",
    "Center for Diagnostic Nuclear Imaging, Universiti Putra Malaysia",
    "Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
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        0,
        1
      ],
      "name": "Harrison Watters"
    },
    {
      "affs": [
        2
      ],
      "name": "Aida Abdul Rashid"
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    {
      "affs": [
        2
      ],
      "name": "Subapriya Suppiah"
    },
    {
      "affs": [
        3
      ],
      "name": "Theodore J. LaGrow"
    },
    {
      "affs": [
        0
      ],
      "name": "Jaroslav Hlinka"
    },
    {
      "affs": [
        3
      ],
      "name": "Shella Keilholz"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0vyf1vbh5116b.bib",
  "cited_by": 0,
  "doi": "10.3389/fnins.2026.1948718",
  "fulltext_url": "https://europepmc.org/articles/PMC13713798",
  "id": "0vyf1vbh5116b",
  "issns": [
    "1662-453X",
    "1662-4548"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fnins.2026.1948718/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "Original Research"
    ],
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      "openalex",
      "2805|Functional Brain Connectivity Studies"
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  "pdf_url": "https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2026.1948718/pdf",
  "pmcid": "PMC13713798",
  "pmid": "42952809",
  "published": "2026-10-14",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/0vyf1vbh5116b.ris",
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      "url": "https://www.frontiersin.org/articles/10.3389/fnins.2026.1948718/full"
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Functional Brain Connectivity Studies",
      "subfield": "neuroscience"
    }
  ],
  "title": "Altered attention network dynamics in resting-state fMRI of individuals with high smartphone addiction scores",
  "title_text": "Altered attention network dynamics in resting-state fMRI of individuals with high smartphone addiction scores",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:21:24Z",
  "url": "https://research.draconitic.com/paper/0vyf1vbh5116b",
  "venue": "Frontiers in Neuroscience",
  "versions": []
}