{
  "abstract": "Sensory neurons are traditionally viewed as feature detectors that respond with an increase in firing rate to preferred stimuli while remaining unresponsive to others. Here, we identify a dual-feature encoding strategy in macaque visual cortex, wherein many neurons in areas V1 and V4 are selectively tuned to two distinct visual features—one that enhances and one that suppresses activity—around an elevated baseline firing rate. By combining neuronal recordings with functional digital twin models—deep learning-based predictive models of biological neurons—we were able to systematically identify each neuron’s preferred and non-preferred features. These feature pairs served as anchors for a continuous, low-dimensional axis in natural image similarity space, along which neuronal activity varied approximately linearly. Within a single visual area, visual features that strongly or weakly activated individual neurons also had a high probability of modulating the activity of other neurons, suggesting a shared feature selectivity across the population that structures stimulus encoding. We show that this encoding strategy is conserved across species, present in both primary and lateral visual areas of mouse cortex. Dual-feature selectivity is consistent with recent anatomical evidence for feature-specific inhibitory connectivity, complementing the feature-detector principle through circuit mechanisms in which selective excitation and inhibition may together enhance the representational capacity of the neuronal population.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, United States",
    "Stanford Bio-X, Stanford University, Stanford, United States",
    "Wu Tsai Neurosciences Institute, Stanford University, Stanford, United States",
    "Institute for Ophthalmic Research, Tübingen University, Tübingen, Germany",
    "Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology- Hellas, Heraklion, Greece",
    "Department of Basic Sciences, Faculty of Medicine, University of Crete, Heraklion, Greece",
    "Department of Neuroscience and Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, United States",
    "Institute of Computer Science and Campus Institute Data Science, University of Göttingen, Göttingen, Germany",
    "Department of Pediatrics; Allergy and Immunology, Baylor College of Medicine, Houston, United States",
    "Lower Saxony Center for AI and Causal Methods in Medicine, Hannover, Germany",
    "Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany",
    "Department of Neurobiology and Biophysics, University of Washington School of Medicine, Seattle, United States",
    "Computational Neuroscience Center, University of Washington, Seattle, United States"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 19,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Nikos Karantzas",
      "orcid": "0000-0003-0369-8769"
    },
    {
      "affs": [
        0,
        1,
        2,
        3
      ],
      "name": "Katrin Franke",
      "orcid": "0000-0002-8649-4835"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Konstantin Friedrich Willeke"
    },
    {
      "affs": [
        4,
        5
      ],
      "name": "Maria Diamantaki",
      "orcid": "0000-0002-8455-7628"
    },
    {
      "affs": [
        6
      ],
      "name": "Kandan Ramakrishnan"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Hasan Atakan Bedel"
    },
    {
      "affs": [
        7
      ],
      "name": "Pavithra Elumalai"
    },
    {
      "affs": [
        6
      ],
      "name": "Kelli Restivo"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Paul Fahey"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Cate Nealley"
    },
    {
      "affs": [
        8
      ],
      "name": "Tori Shinn"
    },
    {
      "affs": [
        0,
        1,
        2
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      "name": "Gabby Garcia"
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    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Saumil Patel"
    },
    {
      "affs": [
        7,
        9,
        10
      ],
      "name": "Alexander Ecker",
      "orcid": "0000-0003-2392-5105"
    },
    {
      "affs": [
        11,
        12
      ],
      "name": "Edgar Walker"
    },
    {
      "affs": [
        4,
        5
      ],
      "name": "Emmanouil Froudarakis",
      "orcid": "0000-0002-3249-3845"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Sophia Sanborn"
    },
    {
      "affs": [
        6,
        7,
        9
      ],
      "name": "Fabian H Sinz",
      "orcid": "0000-0002-1348-9736"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Andreas Savas Tolias",
      "orcid": "0000-0002-4305-6376"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a2vxrjdrqnn2j.bib",
  "cited_by": 0,
  "doi": "10.7554/elife.109861",
  "fulltext_url": "https://elifesciences.org/articles/109861",
  "id": "a2vxrjdrqnn2j",
  "issns": [
    "2050-084X"
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  "landing_url": "https://elifesciences.org/articles/109861",
  "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": [
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      "neuroscience"
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    [
      "heading",
      "Neuroscience"
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    [
      "heading",
      "Research Article"
    ],
    [
      "openalex",
      "2805|Visual perception and processing mechanisms"
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  "openalex": "W7124417511",
  "pdf_url": "https://cdn.elifesciences.org/articles/109861/elife-109861-v1.pdf",
  "pmcid": "PMC13747320",
  "pmid": "43001849",
  "published": "2026-11-09",
  "publisher": "eLife Sciences Publications",
  "ris": "https://research.draconitic.com/paper/a2vxrjdrqnn2j.ris",
  "sources": [
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  "subjects": [
    {
      "field": "biology",
      "origin": "elife:neuroscience",
      "subfield": "neuroscience"
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  ],
  "title": "Dual-feature selectivity enables bidirectional coding in visual cortical neurons",
  "title_text": "Dual-feature selectivity enables bidirectional coding in visual cortical neurons",
  "type": "peer-reviewed",
  "updated_at": "2026-11-13T12:24:13Z",
  "url": "https://research.draconitic.com/paper/a2vxrjdrqnn2j",
  "venue": "eLife",
  "versions": []
}