OSCR

Dual-feature selectivity enables bidirectional coding in visual cortical neurons.

Overview

Authors: Nikos Karantzas1,2,3, Katrin Franke1,2,3,4, Konstantin Friedrich Willeke1,2,3, Maria Diamantaki5,6, Kandan Ramakrishnan7, Hasan Atakan Bedel1,2,3, Pavithra Elumalai8, Kelli Restivo7, Paul Fahey1,2,3, Cate Nealley1,2,3, Tori Shinn9, Gabby Garcia1,2,3, Saumil Patel1,2,3, Alexander Ecker8,10,11, Edgar Walker12,13, Emmanouil Froudarakis5,6, Sophia Sanborn1,2,3, Fabian H Sinz7,8,10, Andreas Savas Tolias1,2,3
ORCID iDs: Nikos Karantzas, Katrin Franke, Maria Diamantaki, Alexander Ecker, Emmanouil Froudarakis, Fabian H Sinz, Andreas Savas Tolias
13 affiliations
  1. Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine Stanford United States
  2. Stanford Bio-X, Stanford University Stanford United States
  3. Wu Tsai Neurosciences Institute, Stanford University Stanford United States
  4. Institute for Ophthalmic Research, Tübingen University Tübingen Germany
  5. Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology- Hellas Heraklion Greece
  6. Department of Basic Sciences, Faculty of Medicine, University of Crete Heraklion Greece
  7. Department of Neuroscience and Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine Houston United States
  8. Institute of Computer Science and Campus Institute Data Science, University of Göttingen Göttingen Germany
  9. Department of Pediatrics; Allergy and Immunology, Baylor College of Medicine Houston United States
  10. Lower Saxony Center for AI and Causal Methods in Medicine Hannover Germany
  11. Max Planck Institute for Dynamics and Self-Organization Göttingen Germany
  12. Department of Neurobiology and Biophysics, University of Washington School of Medicine Seattle United States
  13. Computational Neuroscience Center, University of Washington Seattle United States
Institutions: Stanford University (United States); University of Tübingen (Germany); Foundation for Research and Technology Hellas (Greece); University of Crete (Greece); Baylor College of Medicine (United States); University of Göttingen (Germany); CAIMed - Niedersächsisches Zentrum für KI und Kausale Methoden in der Medizin (Germany); Max Planck Institute for Dynamics and Self-Organization (Germany); University of Washington (United States)
Journal: eLife, volume 15, article RP109861
Dates: published online 9 November 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.109861 · PMID 43001849 · PMCID PMC13747320 · OpenAlex W7124417511
Open access: gold, a free copy (OpenAlex)
Status: data only (how the code is found and verified)
Categories: human (organism), mouse (organism), non-human primate (organism), systems (subfield)
Methods: Connectivity, Smoothing, state filtering, decompositions, Machine learning, Single-unit activity, calcium imaging, Physiology & signal measures
Keywords: dual-feature selectivity, visual cortex, V1, V4, suppression, digital twin, Mouse, Rhesus macaque
MeSH: Neurons*, Visual Cortex*, Visual Perception*, Animals, Macaca mulatta, Mice, Models, Neurological, Photic Stimulation (* major topic)
Journal subjects: Neuroscience
Topic: Visual perception and processing mechanisms (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Deutsche Forschungsgemeinschaft (276693517); Bundesministerium für Bildung und Forschung (01GQ2107); Lower Saxony Ministry of Science and Culture (ZN4257); European Research Council (10.3030/101076710, 10.3030/101041669, 10.3030/101117156); European Commission (10.3030/101025482); Hellenic Foundation for Research and Innovation (4049, 016552); National Institutes of Health (R01EY026927); National Science Foundation (IIS-2113173); Defense Advanced Research Projects Agency (N66001-17-C-4002, N66001-19-C-4020)
Citations: not cited yet (Europe PMC); 100 references in the paper
Research resources: C57BL/6J RRID:IMSR_JAX:000664, Slc17a7-Cre RRID:IMSR_JAX:023527, Ai162 RRID:IMSR_JAX:031562, Kubric; Blender RRID:SCR_008606, Kilosort3 RRID:SCR_016422, RRID:SCR_020958, Pinpoint RRID:SCR_023840

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.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data and to no code of its authors: see the Data section.

The paper's code and data availability statement is in the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

Data availability

Code for screening images in the digital twin, optimizing images, and using the digital twin is available at https://github.com/enigma-brain/dualneuron (copy archived at Karantzas, 2026). Data, including predicted responses to ImageNet images, rendered images, as well as code to load ImageNet images, are available on Dryad at https://doi.org/10.5061/dryad.q573n5tx3. The ImageNet images themselves are not redistributed because of their license; the code to load them from the ImageNet-1K release is provided.

The following dataset was generated:

FrankeK KarantzasN WillekeK DiamantakiM RamakrishnanK BedelH ElumalaiP RestivoK Fahey PC ShinnT GarciaG PatelS EckerA WalkerE FroudarakisE SanbornS SinzF ToliasA 2025Dual-feature selectivity enables bidirectional coding in visual cortical neuronsDryad Digital Repository10.5061/dryad.q573n5tx3PMC1374732043001849

The following previously published datasets were used:

Deng et al. 2009ImageNet-1KILSVRC2012ImageNet

Cimpoi et al. 2014Describable Textures Datasetdtd-r1.0.1.tar.gzDTD

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 12 November 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 19 authors, 8 keywords, 8 MeSH terms, 9 funders, 96 references, 7 RRIDs.

Cite

This paper

Karantzas, N., Franke, K., Willeke, K. F., Diamantaki, M., Ramakrishnan, K., Bedel, H. A., Elumalai, P., Restivo, K., Fahey, P., Nealley, C., Shinn, T., Garcia, G., Patel, S., Ecker, A., Walker, E., Froudarakis, E., Sanborn, S., Sinz, F. H., & Tolias, A. S. (2026). Dual-feature selectivity enables bidirectional coding in visual cortical neurons. eLife, 15, RP109861. https://doi.org/10.7554/elife.109861

BibTeX

@article{karantzas2026dual,
author = {Karantzas, Nikos and Franke, Katrin and Willeke, Konstantin Friedrich and Diamantaki, Maria and Ramakrishnan, Kandan and Bedel, Hasan Atakan and Elumalai, Pavithra and Restivo, Kelli and Fahey, Paul and Nealley, Cate and Shinn, Tori and Garcia, Gabby and Patel, Saumil and Ecker, Alexander and Walker, Edgar and Froudarakis, Emmanouil and Sanborn, Sophia and Sinz, Fabian H and Tolias, Andreas Savas},
title = {{Dual-feature selectivity enables bidirectional coding in visual cortical neurons}},
journal = {eLife},
year = {2026},
month = nov,
volume = {15},
pages = {RP109861},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.109861},
url = {https://doi.org/10.7554/elife.109861},
pmid = {43001849},
pmcid = {PMC13747320}
}

RIS

TY - JOUR
AU - Karantzas, Nikos
AU - Franke, Katrin
AU - Willeke, Konstantin Friedrich
AU - Diamantaki, Maria
AU - Ramakrishnan, Kandan
AU - Bedel, Hasan Atakan
AU - Elumalai, Pavithra
AU - Restivo, Kelli
AU - Fahey, Paul
AU - Nealley, Cate
AU - Shinn, Tori
AU - Garcia, Gabby
AU - Patel, Saumil
AU - Ecker, Alexander
AU - Walker, Edgar
AU - Froudarakis, Emmanouil
AU - Sanborn, Sophia
AU - Sinz, Fabian H
AU - Tolias, Andreas Savas
TI - Dual-feature selectivity enables bidirectional coding in visual cortical neurons
T2 - eLife
J2 - eLife
PY - 2026
DA - 2026/11/09
VL - 15
SP - RP109861
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.109861
UR - https://doi.org/10.7554/elife.109861
LA - en
ER -

CSL-JSON

{
"id": "10.7554/elife.109861",
"type": "article-journal",
"title": "Dual-feature selectivity enables bidirectional coding in visual cortical neurons",
"container-title": "eLife",
"author": [
{
"family": "Karantzas",
"given": "Nikos"
},
{
"family": "Franke",
"given": "Katrin"
},
{
"family": "Willeke",
"given": "Konstantin Friedrich"
},
{
"family": "Diamantaki",
"given": "Maria"
},
{
"family": "Ramakrishnan",
"given": "Kandan"
},
{
"family": "Bedel",
"given": "Hasan Atakan"
},
{
"family": "Elumalai",
"given": "Pavithra"
},
{
"family": "Restivo",
"given": "Kelli"
},
{
"family": "Fahey",
"given": "Paul"
},
{
"family": "Nealley",
"given": "Cate"
},
{
"family": "Shinn",
"given": "Tori"
},
{
"family": "Garcia",
"given": "Gabby"
},
{
"family": "Patel",
"given": "Saumil"
},
{
"family": "Ecker",
"given": "Alexander"
},
{
"family": "Walker",
"given": "Edgar"
},
{
"family": "Froudarakis",
"given": "Emmanouil"
},
{
"family": "Sanborn",
"given": "Sophia"
},
{
"family": "Sinz",
"given": "Fabian H"
},
{
"family": "Tolias",
"given": "Andreas Savas"
}
],
"container-title-short": "eLife",
"volume": "15",
"page": "RP109861",
"DOI": "10.7554/elife.109861",
"PMID": "43001849",
"PMCID": "PMC13747320",
"ISSN": "2050-084X",
"publisher": "eLife Sciences Publications, Ltd",
"URL": "https://doi.org/10.7554/elife.109861",
"language": "en",
"issued": {
"date-parts": [
[
2026,
11,
9
]
]
}
}

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:
Dual-feature selectivity enables bidirectional coding in visual cortical neurons
Journal: eLife
In common: Dryad 10.5061/dryad.q573n5tx3, non-human primate, systems, mouse, 94 references, 7 authors
[2] doi:10.1101/2025.07.16.665209 [code]
Dual-feature selectivity enables bidirectional coding in visual cortical neurons
Journal: bioRxiv (preprint)
In common: systems, 34 references, 3 authors
[3] doi:10.1038/s41593-026-02213-3 [code]
Functional bipartite invariance in mouse primary visual cortex receptive fields.
Journal: Nature neuroscience
In common: systems, mouse, 10 references, 5 authors
[4] doi:10.1038/s41586-025-08829-y [code]
Foundation model of neural activity predicts response to new stimulus types.
Journal: Nature
In common: systems, mouse, 6 references, 4 authors
[5] doi:10.1101/2023.03.15.532836 [code]
Bipartite invariance in mouse primary visual cortex
Journal: bioRxiv (preprint)
In common: systems, mouse, 4 authors
[6] doi:10.1371/journal.pcbi.1012056 [code]
Diverse task-driven modeling of macaque V4 reveals functional specialization towards semantic tasks.
Journal: PLoS computational biology
In common: non-human primate, 6 references, 2 authors
[7] doi:10.1038/s41586-025-08840-3 [code]
Functional connectomics reveals general wiring rule in mouse visual cortex.
Journal: Nature
In common: systems, mouse, 5 references, 2 authors
[8] doi:10.7554/elife.86860 [code]
A chromatic feature detector in the retina signals visual context changes.
Journal: eLife
In common: mouse, 4 references, 2 authors
[9] doi:10.1038/s41467-025-58763-w [code]
An unsupervised map of excitatory neuron dendritic morphology in the mouse visual cortex.
Journal: Nature communications
In common: systems, mouse, 4 references, 2 authors
[10] doi:10.1016/j.crmeth.2026.101421 [code]
EthoPy provides an accessible platform for reproducible behavioral neuroscience.
Journal: Cell reports methods
In common: mouse, 3 references, 2 authors

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: code errors and mismatches between the code and the paper about this paper and its code, from readers and its authors, beside the paper and its tracing map.

Reproductions: reports from readers who ran the authors' code and did not get the paper's result, what they ran, with which environment, commit and data.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.