{
  "abstract": "Neuronal classification from extracellular electrophysiological recordings is challenging due to intrinsic waveform variability, noise, and technical differences across experiments, technologies, and species. We introduce HIPPIE (High-dimensional Interpretation of Physiological Patterns In Intercellular Electrophysiology), a deep learning framework that combines self-supervised pretraining on unlabeled datasets with supervised fine-tuning to classify neurons from extracellular recordings. Using conditional convolutional joint autoencoders, HIPPIE learns technology-adjusted representations of waveforms and spiking dynamics. Here we show, across mouse, rat, and macaque recordings, that HIPPIE classifies cell types competitively with existing methods while additionally supporting generative analyses that discriminative models cannot perform, including counterfactual decoding of electrophysiological signals under changed experimental conditioning, cross-species latent interpolation, and a cross-modal analysis revealing that spike-timing modalities and waveform morphology encode largely independent dimensions of neuronal identity. HIPPIE is available as both a Python package and a coding-free web application, providing a unified framework for multimodal neuronal classification across technologies, experimental conditions, and species.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA",
    "Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA",
    "Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, USA",
    "Department of Molecular, Cellular and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA, USA",
    "Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA",
    "Biotechnology Program, Berkeley City College, Berkeley, CA, USA",
    "Department of Statistics & Data Science, Yale University, New Haven, CT, USA",
    "Wu Tsai Institute, Yale University, New Haven, CT, USA",
    "Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA. mmostajo@ucsc.edu",
    "Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, USA. mmostajo@ucsc.edu"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 15,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Jesus Gonzalez-Ferrer",
      "orcid": "0000-0002-5588-921X"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Julian Lehrer",
      "orcid": "0000-0003-3434-1025"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Bruno Alvarez-Esteban"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Avelina Moreno-Ochando",
      "orcid": "0009-0007-7346-3072"
    },
    {
      "affs": [
        3,
        1,
        2
      ],
      "name": "H. Schweiger",
      "orcid": "0000-0003-0399-9481"
    },
    {
      "affs": [
        4,
        1,
        2
      ],
      "name": "Jinghui Geng",
      "orcid": "0000-0002-3431-9568"
    },
    {
      "affs": [
        4,
        1,
        2
      ],
      "name": "Luiz F. S. Eugênio dos Santos"
    },
    {
      "affs": [
        4,
        1,
        2
      ],
      "name": "Sebastian Hernandez",
      "orcid": "0009-0000-8811-8596"
    },
    {
      "affs": [
        5,
        1,
        2
      ],
      "name": "Francisco Reyes",
      "orcid": "0000-0002-2827-7437"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Jessica L. Sevetson",
      "orcid": "0000-0001-7434-1447"
    },
    {
      "affs": [
        6,
        7
      ],
      "name": "Aidan Schneider"
    },
    {
      "affs": [
        3,
        1
      ],
      "name": "Sofie R. Salama",
      "orcid": "0000-0001-6999-7193"
    },
    {
      "affs": [
        0,
        4,
        1,
        2
      ],
      "name": "Mircea Teodorescu",
      "orcid": "0000-0001-7085-5248"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "David H. Haussler",
      "orcid": "0000-0003-1533-4575"
    },
    {
      "affs": [
        8,
        9
      ],
      "name": "Mohammed A. Mostajo-Radji",
      "orcid": "0000-0002-1634-7514"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2eq8g7bpzqpys.bib",
  "cited_by": 6,
  "doi": "10.1038/s41467-026-76939-w",
  "fulltext_url": null,
  "id": "2eq8g7bpzqpys",
  "issns": [
    "2041-1723"
  ],
  "landing_url": "https://doi.org/10.1038/s41467-026-76939-w",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "2805|Neural dynamics and brain function"
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  "pdf_url": "https://www.nature.com/articles/s41467-026-76939-w_reference.pdf",
  "pmcid": "PMC11952528",
  "pmid": "40161713",
  "published": "2026-08-21",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/2eq8g7bpzqpys.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T13:21:11Z",
      "native_id": "W7171767096",
      "source": "openalex",
      "url": "https://doi.org/10.1038/s41467-026-76939-w"
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Neural dynamics and brain function",
      "subfield": "neuroscience"
    }
  ],
  "title": "HIPPIE: a generative model for electrophysiological analysis across species, technologies, and modalities",
  "title_text": "HIPPIE: a generative model for electrophysiological analysis across species, technologies, and modalities",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T13:21:14Z",
  "url": "https://research.draconitic.com/paper/2eq8g7bpzqpys",
  "venue": "Nature Communications",
  "versions": []
}