{
  "abstract": "ObjectiveWe developed a patient-specific framework to determine which information about interictal epileptiform discharges (IEDs) can be recovered from scalp EEG, separating temporal localization (\"where\") from event-specific intracranial waveform reconstruction (\"what\").\n\nMethodsSix subjects from a public simultaneous high-density scalp EEG and intracranial EEG (iEEG) dataset were analyzed using patient-specific dual-branch convolutional-attention models integrating waveform/topographic and time-frequency representations. For the where task, a 640-ms scalp EEG segment was divided into eight 80-ms bins, and the model predicted the bin containing the intracranial IED peak. For the what task, a 250-ms peak-centered iEEG waveform was represented as a fixed patient-specific template plus an event-specific residual predicted from scalp EEG. Direct scalp-input controls and event-clustered bootstrap confidence intervals were used to distinguish scalp-dependent information from template-driven performance.\n\nResultsWhere accuracy varied markedly across subjects (0.080-0.984), with an unweighted subject-level mean of 0.333 versus a chance level of 0.125; 95% confidence intervals were above chance level in three of six subjects. Input-control analyses supported a scalp-dependent contribution in subjects with successful localization. For the what task, mean waveform correlation was 0.752 for the model and 0.754 for the fixed patient-specific template (mean difference,-0.002), while residual correlations were generally modest (-0.020 to 0.378).\n\nConclusionScalp EEG contained recoverable temporal information in some subjects, but event-specific single-contact morphology was not consistently recovered beyond the patient-specific template. Separating temporal localization from template-based waveform reconstruction provides a more stringent framework for evaluating noninvasive-to-intracranial inference and reduces conflation of prior-driven similarity with input-dependent reconstruction.",
  "abstract_shown": true,
  "affiliations": [
    "Massachusetts General Hospital"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "T. Matsubara"
    },
    {
      "name": "R. Koda"
    },
    {
      "name": "M. Richardson"
    },
    {
      "name": "S. Stufflebeam"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3xfbkswt6d2fy.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.25.26364055",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.25.26364055v1.full",
  "id": "3xfbkswt6d2fy",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.25.26364055v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "neurology"
    ],
    [
      "openalex",
      "2805|EEG and Brain-Computer Interfaces"
    ]
  ],
  "openalex": "W7214574784",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.25.26364055v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3xfbkswt6d2fy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:33Z",
      "native_id": "10.64898/2026.09.25.26364055",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.25.26364055v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:neurology",
      "subfield": "neurology"
    }
  ],
  "title": "A Patient-Specific Framework for Separating Temporal Localization from Intracranial Waveform Reconstruction of Interictal Epileptiform Discharges from Scalp EEG",
  "title_text": "A Patient-Specific Framework for Separating Temporal Localization from Intracranial Waveform Reconstruction of Interictal Epileptiform Discharges from Scalp EEG",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:33Z",
  "url": "https://research.draconitic.com/paper/3xfbkswt6d2fy",
  "venue": "medRxiv",
  "versions": []
}