{
  "abstract": "Excitation/inhibition (E/I) balance is crucial for maintaining healthy brain function and can be disrupted in various neurological and psychiatric disorders. Despite its importance, there are few tools to study E/I balance non-invasively in humans. Here, we propose a canonical microcircuit model to estimate E/I balance from non-invasive magnetoencephalography (MEG), electroencephalography (EEG) or optically pumped magnetometers (OPM) recordings by parameterising global pyramidal and inhibitory cell excitability. We first establish that E/I parameters are identifiable and recoverable. We then explore the effects of these new parameters and their interaction with other parameters in a series of simulations. To highlight the clinical relevance of this new model, we simulate changes in E/I balance and their impact on event-related potentials (ERPs) derived from paired-click, passive and active oddball paradigms, which are among the most robust clinical biomarkers of schizophrenia. Our simulations show that a loss of pyramidal cell excitability can explain reduced ERP amplitudes across all three paradigms, mirroring empirical findings in schizophrenia. This method may serve as a computational assay for estimating synaptopathy and E/I balance from non-invasive electrophysiological recordings across various clinical conditions thereby advancing efforts to develop personalised interventions to restore E/I balance.",
  "abstract_shown": true,
  "affiliations": [
    "Hawkes Institute, Department of Computer Science, University College London, London, UK",
    "Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK",
    "Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK",
    "King’s Institute for Artificial Intelligence, King’s College London, London, UK",
    "Department of Psychology and Neuroscience, City St George’s, University of London, London, UK",
    "Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK",
    "School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK",
    "Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK",
    "Department of Psychiatry & Behavioral Sciences, University of California, San Francisco, CA USA",
    "Mental Health Service, San Francisco Veterans Affairs Health Care System, San Francisco, CA USA",
    "Institute of Cognitive Neuroscience, University College London, London, UK"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0,
        1,
        2,
        3
      ],
      "name": "Daniel J. Hauke",
      "orcid": "0000-0003-1772-9239"
    },
    {
      "affs": [
        0,
        4
      ],
      "name": "Julia Rodriguez-Sanchez",
      "orcid": "0000-0001-5839-0230"
    },
    {
      "affs": [
        0
      ],
      "name": "Hope Oloye"
    },
    {
      "affs": [
        0,
        5,
        6
      ],
      "name": "Lioba C. S. Berndt",
      "orcid": "0009-0006-2455-3031"
    },
    {
      "affs": [
        4
      ],
      "name": "Dimitris A. Pinotsis"
    },
    {
      "affs": [
        7
      ],
      "name": "Karl J. Friston",
      "orcid": "0000-0001-7984-8909"
    },
    {
      "affs": [
        8,
        9
      ],
      "name": "Daniel H. Mathalon",
      "orcid": "0000-0001-6090-4974"
    },
    {
      "affs": [
        10
      ],
      "name": "Rick A. Adams",
      "orcid": "0000-0002-7661-8881"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/15y9hr7157gtb.bib",
  "cited_by": 2,
  "doi": "10.1038/s41398-026-04312-y",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13714252/",
  "id": "15y9hr7157gtb",
  "issns": [
    "2158-3188"
  ],
  "landing_url": "https://doi.org/10.1038/s41398-026-04312-y",
  "language": "en",
  "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": [
    [
      "heading",
      "Article"
    ],
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      "openalex",
      "2805|Neural dynamics and brain function"
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  "openalex": "W4412466330",
  "pdf_url": "https://www.nature.com/articles/s41398-026-04312-y_reference.pdf",
  "pmcid": "PMC13714252",
  "pmid": "42946699",
  "published": "2026-07-31",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/15y9hr7157gtb.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:21:47Z",
      "native_id": "PMC13714252",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41398-026-04312-y"
    }
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Neural dynamics and brain function",
      "subfield": "neuroscience"
    }
  ],
  "title": "A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance",
  "title_text": "A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:21:47Z",
  "url": "https://research.draconitic.com/paper/15y9hr7157gtb",
  "venue": "Translational Psychiatry",
  "versions": []
}