{
  "abstract": "The development of large-scale artificial intelligence (AI) models is influencing neuroscience research by enabling end-to-end learning from raw brain signals and neural data. In this paper, we review applications of large-scale AI models across four major neuroscience domains: neu- roimaging and data processing, brain-computer interfaces and neural decoding, clinical decision support and translational frameworks, and disease-specific applications across neurological and psychiatric disorders. These models show potential to address major computational neuroscience challenges, including multimodal neural data integration, spatiotemporal pattern interpretation, and the development of translational frameworks for clinical research. Moreover, the interaction between neuroscience and AI has become increasingly reciprocal, as biologically informed architectural constraints are now incorporated to develop more interpretable and computationally efficient models. This review highlights both the promise of such technologies and critical implementation considerations, with particular emphasis on rigorous evaluation frameworks, effective integration of domain knowledge, prospective clinical validation, and comprehensive ethical guidelines. Finally, a systematic listing of critical neuroscience datasets used to develop and evaluate large-scale AI models across diverse research applications is provided.",
  "abstract_shown": true,
  "affiliations": [
    "Stevens Institute of Technology, Department of Systems Engineering, Hoboken, 07030, NJ, USA",
    "University of California San Francisco, Department of Neurology and Weill Institute for Neurosciences, San Francisco, 94143, CA, USA",
    "Duke University, Duke Institute for Brain Sciences, Durham, 27708, NC, USA",
    "Boston University, Division of Systems Engineering and Department of Electrical and Computer Engineering, Boston, 02215, MA, USA",
    "Monash University, Department of Neuroscience, School of Translational Medicine, Melbourne, 3800, VIC, Australia",
    "Alfred Hospital, Department of Neurology, Melbourne, 3004, VIC, Australia",
    "University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, 94143, CA, USA",
    "Stanford Institute for Human-Centered AI, Stanford University, Stanford, 94305, CA, USA",
    "Stanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, Stanford, 94305, CA, USA",
    "Wu Tsai Neurosciences Institute, Stanford University, Stanford, 94305, CA, USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Shihao Yang",
      "orcid": "0009-0006-2263-9309"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiying Huang"
    },
    {
      "affs": [
        1
      ],
      "name": "Danilo Bernardo",
      "orcid": "0000-0002-4512-3843"
    },
    {
      "affs": [
        0
      ],
      "name": "Jun-En Ding",
      "orcid": "0000-0002-1233-138X"
    },
    {
      "affs": [
        2
      ],
      "name": "Andrew Michael"
    },
    {
      "affs": [
        0
      ],
      "name": "Jingmei Yang",
      "orcid": "0009-0000-8562-7782"
    },
    {
      "affs": [
        3
      ],
      "name": "Jingmei Yang",
      "orcid": "0009-0000-8562-7782"
    },
    {
      "affs": [
        4
      ],
      "name": "Alison Anderson"
    },
    {
      "affs": [
        4
      ],
      "name": "Dinesh Giritharan",
      "orcid": "0009-0005-0620-3815"
    },
    {
      "affs": [
        5,
        4
      ],
      "name": "Patrick Kwan",
      "orcid": "0000-0001-7310-276X"
    },
    {
      "affs": [
        6
      ],
      "name": "Ashish Raj",
      "orcid": "0000-0003-2414-2444"
    },
    {
      "affs": [
        7,
        8,
        9
      ],
      "name": "Yu Zhang",
      "orcid": "0000-0003-4087-6544"
    },
    {
      "affs": [
        0
      ],
      "name": "Feng Liu",
      "orcid": "0000-0002-5225-8199"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1pzd7t940zqtf.bib",
  "cited_by": 11,
  "doi": "10.1016/j.metrad.2026.100224",
  "fulltext_url": null,
  "id": "1pzd7t940zqtf",
  "issns": [
    "2950-1628"
  ],
  "landing_url": "https://doi.org/10.1016/j.metrad.2026.100224",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2805|EEG and Brain-Computer Interfaces"
    ]
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  "openalex": "W4415955468",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-06-04",
  "publisher": "Elsevier BV",
  "ris": "https://research.draconitic.com/paper/1pzd7t940zqtf.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T13:20:36Z",
      "native_id": "W4415955468",
      "source": "openalex",
      "url": "https://doi.org/10.1016/j.metrad.2026.100224"
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|EEG and Brain-Computer Interfaces",
      "subfield": "neuroscience"
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  ],
  "title": "Large-scale AI and foundation models for neuroscience: A comprehensive review",
  "title_text": "Large-scale AI and foundation models for neuroscience: A comprehensive review",
  "type": "peer-reviewed",
  "updated_at": "2026-11-13T13:21:08Z",
  "url": "https://research.draconitic.com/paper/1pzd7t940zqtf",
  "venue": "Meta-Radiology",
  "versions": []
}