{
  "abstract": "Sleep deprivation is a potent, rapid-acting therapeutic intervention for major depressive disorder, yet its underlying neural mechanisms remain poorly understood, hindering the development of predictive biomarkers. Here, we systematically characterize the electro-physiological signatures of prolonged wakefulness using a multi-methodological approach across three independent datasets in humans and mice. By integrating standard power spectral density analysis with aperiodic component fitting (SpecParam) and highly compar-ative time-series analysis (HCTSA), we identified robust cross-species biomarkers of sleep pressure. Machine learning models revealed that theta power is the most consistent feature for differentiating control and sleep deprivation states, achieving up to 90% classification accuracy. Sleep deprivation significantly increased the spectral offset - suggesting global cortical hyperexcitation - while simultaneously steepening the spectral slope. We interpret this simultaneous shift as a state uncoordinated state of hyperexcited and inefficient neu-ral processing. These findings establish reproducible EEG markers of sleep deprivation that transcend species. Given the clinical utility of wake therapy, we propose that prefrontal the-ta power and spectral offset/slope may serve as mechanism-based predictors of therapeu-tic response. Our results provide a framework for the clinical validation of these biomarkers, potentially enabling personalized chronotherapeutic interventions for psychiatric disorders.",
  "abstract_shown": true,
  "affiliations": [
    "University of Muenster"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "T. Kroker"
    },
    {
      "name": "L. Puder"
    },
    {
      "name": "O. Abbasi"
    },
    {
      "name": "S. Ghiasi"
    },
    {
      "name": "C. Krug"
    },
    {
      "name": "I. Wessing"
    },
    {
      "name": "M. A. Salehinejad"
    },
    {
      "name": "T. Ruland"
    },
    {
      "name": "J. Alferink"
    },
    {
      "name": "U. Dannlowski"
    },
    {
      "name": "P. Ritter"
    },
    {
      "name": "J. Gross"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/62yvn38x5sgd3.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.08.750125",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.750125v1.full",
  "id": "62yvn38x5sgd3",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.750125v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "2805|Sleep and Wakefulness Research"
    ]
  ],
  "openalex": "W7159856203",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.08.750125v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-08",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/62yvn38x5sgd3.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:21Z",
      "native_id": "10.64898/2026.09.08.750125",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.08.750125v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Multi-Methodological Characterization of Sleep Deprivation: From Standard EEG Power Spectra to Aperiodic Dynamics in Humans and Mice.",
  "title_text": "Multi-Methodological Characterization of Sleep Deprivation: From Standard EEG Power Spectra to Aperiodic Dynamics in Humans and Mice.",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:21Z",
  "url": "https://research.draconitic.com/paper/62yvn38x5sgd3",
  "venue": "bioRxiv",
  "versions": []
}