Broadband synergy versus oscillatory redundancy in the visual cortex.

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Paper

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The authors' code

MATLAB · 10 lines · 333 B · GPL-3.0

function fmap = cpp_mex_default_function_map()
fmap = struct( ...
'copnorm_slice', 'copnorm_slice_cpp', ...
'info_cc_slice', 'info_cc_slice_cpp', ...
'info_cc_multi', '', ...
'info_cc_slice_indexed', '', ...
'info_c1d_slice', '', ...
'info_cd_slice', 'info_cd_slice_cpp', ...
'info_dc_slice_bc', '');
end

cpp_mex_default_function_map.m at commit cd5426b, under GPL-3.0 · at the source

Overview

Authors: Louis Roberts^1,2,3, Juho Äijälä^1,4, Florian Burger^1,5, Cem Uran^6,7, Michael A Jensen⁸, Kai J Miller⁸, Robin A A Ince⁹, Martin Vinck^6,7, Dora Hermes⁸, Andres Canales-Johnson^1,4,10,11

ORCID iDs: Florian Burger, Michael A Jensen, Kai J Miller, Martin Vinck, Dora Hermes, Andres Canales-Johnson

Institutions: University of Cambridge (United Kingdom); RIKEN (Japan); Institute of Science Tokyo (Japan); University of Helsinki (Finland); HiLIFE – Elämäntieteiden Instituutti; Western Sydney University (Australia); Radboud University Nijmegen (Netherlands); Max Planck Society (Germany); Ernst Strüngmann Institute for Neuroscience (Germany); Donders Centre for Neuroscience (Netherlands); Mayo Clinic (United States); University of Glasgow (United Kingdom); Catholic University of the Maule (Chile); Karolinska Institutet (Sweden)

Journal: Nature communications, volume 17, issue 1, article 5568

Dates: received 17 June 2025; accepted 15 April 2026; published online 28 April 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1038/s41467-026-72444-2 · PMID 42049731 · PMCID PMC13294381 · OpenAlex W4408087161

Open access: gold, a free copy (OpenAlex)

Preprint: doi:10.1101/2025.02.27.640666

Status: code verified

Categories: extracellular electrophysiology (units, LFP) (modality), intracranial EEG (iEEG / ECoG / SEEG) (modality), human (organism), non-human primate (organism), systems (subfield)

Methods: Spectral & time-frequency, Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, Physiology & signal measures

Keywords: Visual system, Sensory processing

MeSH: Visual Cortex*, Animals, Electrocorticography, Gamma Rhythm, Humans, Local Field Potential Measurement, Macaca mulatta, Male, Photic Stimulation (* major topic)

Topic: Neural dynamics and brain function (Cognitive Neuroscience, Neuroscience), according to OpenAlex

Funding: European Research Council (850861); Dutch Research Council (NWO) (14701)

Citations: cited by 9 papers (Europe PMC); 90 references in the paper

Abstract

The cortex generates diverse neural dynamics, ranging from broadband fluctuations to narrowband oscillations at specific frequencies. Here, we investigated whether broadband and oscillatory dynamics play different roles in the encoding and transmission of visual information. We used information-theoretical measures to dissociate neural signals sharing common information (i.e., redundancy) from signals encoding complementary information (i.e., synergy). We analyzed electrocorticography (ECoG) and local field potentials (LFP) in the visual cortex of human and non-human primates (macaque) to investigate the extent to which broadband signals (BB) and narrowband gamma (NBG) oscillations conveyed synergistic or redundant information about images. In both species, the information conveyed by BB signals was highly synergistic within and between visual areas. By contrast, the information carried by NBG was primarily redundant within and between the same visual areas. Finally, the information conveyed by BB signals emerged early after stimulus onset, while NBG sustained information at later time points. These results suggest a potential dual role of BB and NBG cortical dynamics in visual processing, with broadband dynamics supporting nonlinear pattern recognition and oscillations facilitating information maintenance across the cortex.

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

Repository

Its files are read in the Code ↔ Paper reader above.

robince/gcmi

License: GPL-3.0

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: cd5426bb4c6b7094858f37c3710a4ae9367f8ef1, 23 July 2026

Languages: MATLAB (45), Python (10), C++ (10), C (1)

Size: 90 files, 66 scripts

Software Heritage: archived

Found in: “Code availability”

Holds: README, license file, environment (python/pyproject.toml, python/uv.lock), tests, continuous integration

Not found: CITATION.cff, documentation

Tools: NumPy (5 files), Numba (3 files), EEGLAB (2 files), SciPy (2 files), Statistics and Machine Learning Toolbox (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

68 files

benchmarks/cpp_mex_default_function_map.m, MATLAB, 10 lines
benchmarks/run_matlab_benchmarks.m, MATLAB, 798 lines
benchmarks/run_python_benchmarks.py, Python, 392 lines
buildfile.m, MATLAB, 45 lines
matlab/Contents.m, MATLAB, 36 lines
matlab/bias_cmi_ggg_bits.m, MATLAB, 23 lines
matlab/bias_ent_g_bits.m, MATLAB, 23 lines
matlab/bias_mi_gd_bits.m, MATLAB, 42 lines
matlab/bias_mi_gg_bits.m, MATLAB, 14 lines
matlab/cmi_ggg.m, MATLAB, 93 lines
matlab/cmi_ggg_vec.m, MATLAB, 118 lines
matlab/copnorm.m, MATLAB, 10 lines
matlab/cpp_mex/mex/copnorm_slice_cpp.cpp, C++, 25 lines
matlab/cpp_mex/mex/gcmi_cpp_blas_probe.cpp, C++, 32 lines
matlab/cpp_mex/mex/gcmi_cpp_omp_probe.cpp, C++, 21 lines
matlab/cpp_mex/mex/gcmi_cpp_ping.cpp, C++, 16 lines
matlab/cpp_mex/mex/gcmi_cpp_runtime_probe.cpp, C++, 34 lines
matlab/cpp_mex/mex/info_cc_slice_cpp.cpp, C++, 33 lines
matlab/cpp_mex/mex/info_cc_slice_cpp_capi.c, C, 96 lines
matlab/cpp_mex/mex/info_cd_slice_cpp.cpp, C++, 29 lines
matlab/cpp_mex/src/copnorm_kernel.cpp, C++, 105 lines
matlab/cpp_mex/src/gcmi_kernels.cpp, C++, 371 lines
matlab/cpp_mex/src/info_cc_slice_bridge.cpp, C++, 36 lines
matlab/cpp_mex/tests/run_gcmi_cpp_mex_smoke_tests.m, MATLAB, 3 lines
matlab/cpp_mex/tooling/gcmi_cpp_mex_clean.m, MATLAB, 9 lines
matlab/cpp_mex/tooling/gcmi_cpp_mex_compile.m, MATLAB, 189 lines
matlab/cpp_mex/tooling/gcmi_cpp_mex_config.m, MATLAB, 154 lines
matlab/cpp_mex/tooling/gcmi_cpp_mex_package.m, MATLAB, 17 lines
matlab/cpp_mex/tooling/gcmi_cpp_mex_test.m, MATLAB, 156 lines
matlab/ctransform.m, MATLAB, 8 lines
matlab/ent_g.m, MATLAB, 42 lines
matlab/gccmi_ccc.m, MATLAB, 56 lines
matlab/gccmi_ccd.m, MATLAB, 73 lines
matlab/gcmi_cc.m, MATLAB, 46 lines
matlab/gcmi_mixture_cd.m, MATLAB, 66 lines
matlab/gcmi_model_cd.m, MATLAB, 46 lines
matlab/gcmi_version.m, MATLAB, 4 lines
matlab/maxstar.m, MATLAB, 42 lines
matlab/mi_gg.m, MATLAB, 71 lines
matlab/mi_gg_vec.m, MATLAB, 129 lines
matlab/mi_mixture_gd.m, MATLAB, 108 lines
matlab/mi_mixture_gd_vec.m, MATLAB, 164 lines
matlab/mi_model_gd.m, MATLAB, 82 lines
matlab/mi_model_gd_vec.m, MATLAB, 156 lines
matlab/tests/Contents.m, MATLAB, 3 lines
matlab/tests/run_gcmi_regression_tests.m, MATLAB, 255 lines
matlab/validate_discrete_labels.m, MATLAB, 35 lines
matlab/vecchol.m, MATLAB, 74 lines
matlab_examples/bias_demo.m, MATLAB, 37 lines
matlab_examples/block_delay.m, MATLAB, 12 lines
matlab_examples/block_index.m, MATLAB, 6 lines
matlab_examples/continuous_meg.m, MATLAB, 229 lines
matlab_examples/cpp_continuous_native.m, MATLAB, 150 lines
matlab_examples/cpp_discrete_native.m, MATLAB, 155 lines
matlab_examples/discrete_eeg.m, MATLAB, 122 lines
matlab_examples/eeg_temporal_interaction.m, MATLAB, 269 lines
python/gcmi.py, Python, 33 lines
python/src/gcmi/__init__.py, Python, 5 lines
python/src/gcmi/_core.py, Python, 926 lines
python/src/gcmi/_dispatch.py, Python, 95 lines
python/src/gcmi/_numba.py, Python, 557 lines
python/src/gcmi/_version.py, Python, 41 lines
python/tests/conftest.py, Python, 9 lines
python/tests/test_batch_kernels.py, Python, 192 lines
python/tests/test_gcmi.py, Python, 304 lines
setup_gcmi.m, MATLAB, 78 lines
LICENSE, License, 231 lines
README.md, Text, 272 lines

At the source: github.com/robince/gcmi

Code availability

The MATLAB/Python toolbox GCMI (Gaussian Copula Mutual Information) used in this study is publicly available at: https://github.com/robince/gcmi.

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

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
66 scripts, each with its path and the digest of its content;
no match between paragraphs and code yet;
neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

osf:q4yad, at OSF; found in “Data availability”

Data availability

The original human data used in this study are publicly available at: https://osf.io/q4yad. Source data are provided with this paper.

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, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 2 keywords, 9 MeSH terms, 2 funders, 88 references.

Cite

This paper

Roberts, L., Äijälä, J., Burger, F., Uran, C., Jensen, M. A., Miller, K. J., Ince, R. A. A., Vinck, M., Hermes, D., & Canales-Johnson, A. (2026). Broadband synergy versus oscillatory redundancy in the visual cortex. Nature communications, 17(1), 5568. https://doi.org/10.1038/s41467-026-72444-2

BibTeX

@article{roberts2026broadband, author = {Roberts, Louis and Äijälä, Juho and Burger, Florian and Uran, Cem and Jensen, Michael A and Miller, Kai J and Ince, Robin A A and Vinck, Martin and Hermes, Dora and Canales-Johnson, Andres}, title = {{Broadband synergy versus oscillatory redundancy in the visual cortex}}, journal = {Nature communications}, year = {2026}, month = apr, volume = {17}, number = {1}, pages = {5568}, publisher = {Nature Publishing Group}, issn = {2041-1723}, doi = {10.1038/s41467-026-72444-2}, url = {https://doi.org/10.1038/s41467-026-72444-2}, pmid = {42049731}, pmcid = {PMC13294381} }

RIS

TY - JOUR AU - Roberts, Louis AU - Äijälä, Juho AU - Burger, Florian AU - Uran, Cem AU - Jensen, Michael A AU - Miller, Kai J AU - Ince, Robin A A AU - Vinck, Martin AU - Hermes, Dora AU - Canales-Johnson, Andres TI - Broadband synergy versus oscillatory redundancy in the visual cortex T2 - Nature communications J2 - Nat Commun PY - 2026 DA - 2026/04/28 VL - 17 IS - 1 SP - 5568 SN - 2041-1723 PB - Nature Publishing Group DO - 10.1038/s41467-026-72444-2 UR - https://doi.org/10.1038/s41467-026-72444-2 LA - en ER -

CSL-JSON

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Broadband synergy versus oscillatory redundancy in the visual cortex.

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robince/gcmi

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