{
  "abstract": "Spectral modeling of electrophysiological recordings enables non-invasive characterization of neural excitability. However, current approaches rely on a single spectral index, limiting insight into the multiple biophysical processes underlying excitation-inhibition balance. Here, we introduce a biologically informed, multi-parametric spectral analysis that disentangles neural excitability and synaptic kinetics from recordings. As a proof of concept, we demonstrate that this approach captures signatures of hyperexcitability and glutamate reuptake dysfunction characteristic of Alzheimer's disease.",
  "abstract_shown": true,
  "affiliations": [
    "Université libre de Bruxelles (ULB)"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "V. Philippe"
    },
    {
      "name": "L. Tombroff"
    },
    {
      "name": "F. Akbarian"
    },
    {
      "name": "S. De Witte"
    },
    {
      "name": "N. Trotta"
    },
    {
      "name": "J. Van Schependom"
    },
    {
      "name": "S. Engelborghs"
    },
    {
      "name": "J.-C. Bier"
    },
    {
      "name": "M. Strauss"
    },
    {
      "name": "X. De Tiege"
    },
    {
      "name": "V. Wens"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/11bvw31kmph9d.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.15.759313",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.15.759313v1.full",
  "id": "11bvw31kmph9d",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.15.759313v1",
  "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": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "2805|Neural dynamics and brain function"
    ]
  ],
  "openalex": "W7222887930",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.15.759313v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/11bvw31kmph9d.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:24Z",
      "native_id": "10.64898/2026.10.15.759313",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.15.759313v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Multi-parametric spectral modeling disentangles synaptic kinetics and neural excitability from non-invasive electrophysiological recordings",
  "title_text": "Multi-parametric spectral modeling disentangles synaptic kinetics and neural excitability from non-invasive electrophysiological recordings",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:24Z",
  "url": "https://research.draconitic.com/paper/11bvw31kmph9d",
  "venue": "bioRxiv",
  "versions": []
}