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A unifying principle of chromatic coding across biological and artificial systems.

Overview

  1. School of Psychology, Shanghai University of Sport, Shanghai, China
  2. Abteilung Allgemeine Psychologie and Center for Mind, Brain, and Behavior, Justus-Liebig-Universität Gießen, Gießen, Germany
  3. Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Brain Cognition and Brain-Inspired Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
  4. University of Chinese Academy of Sciences, Beijing, China
  5. SANS Institute for Neuroscience and Vision Research, Shanghai Jiao Tong University, School of Medicine, Shanghai, China
Journal: Science advances, volume 12, issue 37, article eaec6658
Dates: received 28 September 2025; accepted 3 August 2026; published online 11 September 2026; in print September 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1126/sciadv.aec6658 · PMID 42726864 · PMCID PMC13564838 · OpenAlex W7212306968
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), systems (subfield)
Methods: Spectral & time-frequency, Statistics, Preprocessing, Evoked potentials, Machine learning, Physiology & signal measures
MeSH: Color Perception*, Animals, Evoked Potentials, Visual, Humans, Neural Networks, Computer, Photic Stimulation, Visual Cortex (* major topic)
Journal subjects: Neuroscience, Psychological Science
Topic: Visual perception and processing mechanisms (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: European Research Council (884116); Deutsche Forschungsgemeinschaft (German Research Foundation) (222641018); National Natural Science Foundation of China (T2541081); National Science and Technology Innovation 2030 (2022ZD0204600); DFG Excellence Cluster (533717223)
Citations: not cited yet (Europe PMC); 107 references in the paper

Abstract

Color is a defining feature of human vision, yet its integration with spatial structure across stages of the visual system is still not fully understood. Classical accounts assumed that color provides little spatial information, being represented coarsely and separately from luminance. Here, we show that the spatial selectivity of color is not fixed, but dynamically transforms with temporal frequency. In human observers, steady-state visual evoked potentials reveal a clear shift from low-pass tuning at higher temporal frequencies to band-pass tuning at lower frequencies. Local field potentials recorded from macaque V1 exhibit the same transition, and color-deficient observers show a selective loss of the low-pass component, pointing to distinct underlying mechanisms. Analyses of deep neural networks trained for object recognition reveal an analogous transformation, demonstrating that this principle also emerges in artificial vision systems. Together, these findings establish that the spatial tuning of color evolves systematically with temporal scale, providing a unifying principle of chromatic coding across biological and artificial systems.

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

Code

No file of the authors' code could be read here: it is described below, and read at its source.

Zenodo 20954249

License: CC-BY-4.0
State: the link answers, verified on 26 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data, code, and materials availability:”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
  • 26 September 2026: the link answers (HTTP 200)

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

Tracing map

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  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
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Data

No dataset and no data link were found in the paper.

Data, code, and materials availability

All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. This study did not generate new materials. Data and code are also available at https://doi.org/10.5281/zenodo.20954249.

Reproduced under the paper's license (CC BY-NC), 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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 7 MeSH terms, 5 funders, 96 references.

Cite

This paper

Songlin, Q., Gegenfurtner, K. R., Liu, Y., Cao, H., Liu, Y., Wang, W., & Chen, J. (2026). A unifying principle of chromatic coding across biological and artificial systems. Science advances, 12(37), eaec6658. https://doi.org/10.1126/sciadv.aec6658

BibTeX

@article{songlin2026unifying,
author = {Songlin, Qiao and Gegenfurtner, Karl R. and Liu, Yingfan and Cao, Hetian and Liu, Ye and Wang, Wei and Chen, Jing},
title = {{A unifying principle of chromatic coding across biological and artificial systems}},
journal = {Science advances},
year = {2026},
month = sep,
volume = {12},
number = {37},
pages = {eaec6658},
publisher = {American Association for the Advancement of Science},
issn = {2375-2548},
doi = {10.1126/sciadv.aec6658},
url = {https://doi.org/10.1126/sciadv.aec6658},
pmid = {42726864},
pmcid = {PMC13564838}
}

RIS

TY - JOUR
AU - Songlin, Qiao
AU - Gegenfurtner, Karl R.
AU - Liu, Yingfan
AU - Cao, Hetian
AU - Liu, Ye
AU - Wang, Wei
AU - Chen, Jing
TI - A unifying principle of chromatic coding across biological and artificial systems
T2 - Science advances
J2 - Sci Adv
PY - 2026
DA - 2026/09/11
VL - 12
IS - 37
SP - eaec6658
SN - 2375-2548
PB - American Association for the Advancement of Science
DO - 10.1126/sciadv.aec6658
UR - https://doi.org/10.1126/sciadv.aec6658
LA - en
ER -

CSL-JSON

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The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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