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Addressing arbitrary choices of frequency band of interest in fNIRS hyperscanning.

Code ↔ Paper

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The 1 match
  1. [1] § Methods › fNIRS data analysis ↔ fnirs_hyper_MathHyper.m, lines 2–33 · score 0.68 · optical density, DPFs, intensity, artifacts, motion, filtering

Paper

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The authors' code

MATLAB · 39 lines · 1.5 KB · no license · 1 match

  2. function [Homer_data] = fnirs_hyper_IBC(Homer_data, age, LP, HP,NN,SCI,srt_ch,lrt_ch)
  4. Homer_data.step_re=f_de_step(Homer_data.d);
  5. % convert intensity (raw files) to optical density
  6. Homer_data.heart = hmrBandpassFilt(Homer_data.step_re, Homer_data.t, LP, HP);
  7. Homer_data.OD = hmrIntensity2OD(Homer_data.step_re);
  8. % % % Homer_data.wav = hmrMotionCorrectWavelet(Homer_data.OD,Homer_data.SD,0.7);
  9. [DPF_lam]=esti_DPF_age(Homer_data.SD.Lambda, age);
  10. Homer_data.conc = hmrOD2Conc(Homer_data.OD, Homer_data.SD, DPF_lam);
  11. % % % Homer_data.concfilt = hmrBandpassFiltConc(Homer_data.conc, Homer_data.t, 0.01, 2.5);
  12. Homer_data.PostNorm_v2 = PCA_SS_Hbdata(Homer_data,'conc',NN,SCI,srt_ch,lrt_ch);
  19. % % fs=1/(Homer_data.t(2)-Homer_data.t(1));
  20. %%%% use MARA for artifact removal (Scholkmann 2010); code from SPM12-NIRS;
  21. %%%% parameters from Nguyen 2021
  22. % % for mm=1:size(Homer_data.OD,2)
  23. % % Homer_data.MARA(:,mm) = spm_fnirs_MARA(Homer_data.OD(:,mm),fs,3,1,5);
  24. % % end
  25. % Homer_data.conc = hmrOD2Conc(Homer_data.wav, Homer_data.SD, [7.3 6.4]);
  26. % Homer_data.concMara = hmrOD2Conc(Homer_data.MARA, Homer_data.SD, [DPF_lam1 DPF_lam2]);
  27. % % Homer_data.conc = hmrOD2Conc(Homer_data.OD, Homer_data.SD, [DPF_lam1 DPF_lam2]);
  29. % band pass filter the concentration (?). Filters oxy, deoxy and then adds
  30. % % Homer_data.concMarafilt = hmrBandpassFiltConc(Homer_data.concMara, Homer_data.t, 0.01, 0.5);
  31. % % %
  32. % % % %%% apply the anticorrelation method
  33. % % % Homer_data.concfiltCBSI = hmrMotionCorrectCbsi(Homer_data.concfilt, Homer_data.SD);

fnirs_hyper_MathHyper.m, no license · at the source

Overview

Authors: Xin Zhou1, Florrie F. Y. Ng1,2, Patrick C. M. Wong1,3
  1. Brain and Mind Institute, The Chinese University of Hong Kong,Sha Tin, Hong Kong SAR China
  2. Department of Educational Psychology, The Chinese University of Hong Kong,Sha Tin, Hong Kong SAR, China
  3. Department of Linguistics and Modern Languages, The Chinese University of Hong Kong,Sha Tin, Hong Kong SAR, China
Institutions: Chinese University of Hong Kong (Hong Kong SAR China)
Journal: Scientific reports, volume 16, issue 1, article 19400
Dates: received 14 October 2025; accepted 21 April 2026; published online 27 April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41598-026-50540-z · PMID 42045603 · PMCID PMC13287691 · OpenAlex W4415208896
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.21203/rs.3.rs-7854624/v1
Status: code verified
Categories: fMRI (modality), fNIRS (modality), human (organism), methods / tools (subfield)
Methods: Statistics, Connectivity, Preprocessing
Keywords: fNIRS hyperscanning, Inter-brain connection, Frequency band of interest, Neuroscience, Psychology
MeSH: Brain*, Functional Neuroimaging*, Brain Mapping, Humans, Social Interaction, Spectroscopy, Near-Infrared (* major topic)
Topic: Optical Imaging and Spectroscopy Techniques (Radiology, Nuclear Medicine and Imaging, Medicine), according to OpenAlex
Funding: Research Grants Council of Hong Kong (C4001-22EF)
Citations: not cited yet (Europe PMC); 95 references in the paper

Abstract

Neuroimaging hyperscanning—the monitoring of brain activity of two or more persons simultaneously—has emerged as a popular tool to uncover the neural mechanisms of social interactions. The use of functional near-infrared spectroscopy (fNIRS)—a non-invasive, child-friendly technique tolerant of motion artifacts—has significantly advanced the research of social interactions. Despite its popularity, the field has yet to agree on best practices for quantifying inter-brain connections (IBC) during social interactions, including the frequency band of interest (FOI) for signal analysis. Various choices of FOIs, along with subject-level physiological differences or experimental design, may have contributed to inconsistent findings across prior studies. In this study, we reviewed various methods used and their corresponding FOI results in previous fNIRS hyperscanning research focused on the topics of cooperation. Additionally, we propose a new methodology to quantify FOI that aims to point to the origin of synchronization between brains. We tested the proposed method on three independent fNIRS hyperscanning datasets. The three datasets involved three different populations and three types of social interactions commonly studied in the literature. We examined the effect of sample sizes and data exclusion rates on the calculation of FOIs and statistical results. We offer a method for testing and adoption within the fNIRS community, aimed at eliminating arbitrary FOI selections and potentially enhancing the reproducibility of results in future fNIRS hyperscanning research.

Supplementary Information: The online version contains supplementary material available at 10.1038/s41598-026-50540-z.

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

Repository

Its files are read in the Code ↔ Paper reader above, with 1 match between paragraphs and lines of code.

OSF r4s73

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Languages: MATLAB (5)
Size: 5 files, 5 scripts
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (4 files), shadedErrorBar (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
  • 30 September 2026: the link answers (HTTP 200)
5 files
At the source: osf.io/r4s73/?view_only=6c14eb3ca218417489e939bbd45f7197

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

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;
  • 5 scripts, each with its path and the digest of its content;
  • 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
  • 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

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

Data availability

MATLAB code used for the data analyses is stored on Open Science Framework and available for peer review through the following link https://osf.io/r4s73/?view_only=6c14eb3ca218417489e939bbd45f7197. The summary (de-identified) data supporting the conclusions of this article will be made available by the authors, without undue reservation.

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

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 6 MeSH terms, 1 funder, 93 references.

Cite

This paper

Zhou, X., Ng, F. F. Y., & Wong, P. C. M. (2026). Addressing arbitrary choices of frequency band of interest in fNIRS hyperscanning. Scientific reports, 16(1), 19400. https://doi.org/10.1038/s41598-026-50540-z

BibTeX

@article{zhou2026addressing,
author = {Zhou, Xin and Ng, Florrie F. Y. and Wong, Patrick C. M.},
title = {{Addressing arbitrary choices of frequency band of interest in fNIRS hyperscanning}},
journal = {Scientific reports},
year = {2026},
month = apr,
volume = {16},
number = {1},
pages = {19400},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-50540-z},
url = {https://doi.org/10.1038/s41598-026-50540-z},
pmid = {42045603},
pmcid = {PMC13287691}
}

RIS

TY - JOUR
AU - Zhou, Xin
AU - Ng, Florrie F. Y.
AU - Wong, Patrick C. M.
TI - Addressing arbitrary choices of frequency band of interest in fNIRS hyperscanning
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/04/27
VL - 16
IS - 1
SP - 19400
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-50540-z
UR - https://doi.org/10.1038/s41598-026-50540-z
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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