Cortical integration of tactile inputs distributed across timescales.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches · all tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted

[1] § Methods › EEG recordings and preprocessing ↔ private/getreadyforanalysis.m, the whole file · a weak match · score 0.89 · pop_eegfiltnew, pop_interp, baseline corrected, spherical, EEGLAB, Eye
[2] § Methods › EEG recordings and preprocessing ↔ private/rejecteyeblink.m, the whole file · a weak match · score 0.75 · pop subcomp, Eye blink, EEGLAB, ICA, filtered, channels

Paper

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The authors' code

MATLAB · 79 lines · 2.2 KB · no license · 1 match

function INEEG = getreadyforanalysis(INEEG,bandpassrange,eyeE,epochevent,epochwindow,baselinewindow,rejepoch)
% To generate clean eeg data
% --------------------------Usage-------------------------------------
% fomula: INEEG = getreadyforanalysis(INEEG,bandpassrange,eyeE,epochevent,epochwindow,baselinewindow,rejepoch)
% Input(s):
% -INEEG: EEG struct from one participant;
% -bandpassrange:like [1 45]Hz;
% -eyeE: eye electrode, {'E5' 'E64'};
% -epochevent: {'S 1' 'S 1' 'S 4'}
% -epochwindow: [-0.2 0.3]S
% -baselinewindow: [-200 -150]ms
% -rejepoch: 0=no rejection; 1= reject trials >80 or <-80 uV
% Output(s):
% -INEEG struct
% Requires:
% -runICA
% Will do:
% -rejeact eyeblinks
% -refiltering
% -intepolate
% -epoch
% -re-reference
% -remove baseline
% -reject epoch
% Author: Wenyu Wan(万文雨), Leiden Univeristy
% Date: 08/03/2023
% edited at 24/08/2023; 27/11/2023
% remove blinks and modify EEG.event with only those events which are in 'passive movie condition'
if ~isempty(eyeE)
INEEG = rejecteyeblink(INEEG,eyeE);
end
%filtering
if ~isempty(bandpassrange)
INEEG = pop_eegfiltnew(INEEG, bandpassrange(1),bandpassrange(2));
end
% interpolate
if ~isfield(INEEG,'Orignalchanlocs')
load('Orignalchanlocs.mat');
INEEG.Orignalchanlocs = Orignalchanlocs;
end
INEEG = pop_interp(INEEG,INEEG.Orignalchanlocs,'spherical');
% remove unrelated channels
if ~isempty(eyeE)
INEEG = pop_select(INEEG,'nochannel',eyeE); %eyeE
end
% epoch, select epoch, and reject epoch according to the intervals
if ~isempty(epochevent)
INEEG = pop_epoch(INEEG,epochevent,epochwindow,'epochinfo','no');
end
%re-refernce
INEEG = pop_reref (INEEG, [1:62], 'keepref', 'on');
%baseline correction
if ~isempty(baselinewindow)
INEEG = pop_rmbase(INEEG, baselinewindow); %
end
% reject trails?
if rejepoch==1
[INEEG Indexes] = pop_eegthresh(INEEG, 1, [1:62], -80, 80, -0.2, 1, 0, 1);
end
% create INEEG.modepoch to store the epoch after running selectepoch
if ~isempty(epochevent)
INEEG = selectepoch (INEEG);
end
% check dataset
INEEG = eeg_checkset(INEEG);
end

getreadyforanalysis.m at commit cfa24ad, no license · at the source

Overview

Authors: Wenyu Wan^1,2, K Richard Ridderinkhof², Arko Ghosh¹

ORCID iDs: Wenyu Wan, Arko Ghosh

Institutions: Leiden University (Netherlands); University of Amsterdam (Netherlands)

Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1146

Dates: received 21 August 2024; accepted 30 January 2026; published online 3 March 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1162/imag.a.1146 · PMID 41799681 · PMCID PMC12961305 · OpenAlex W7128443751

Open access: diamond, a free copy (OpenAlex)

Status: code verified

Categories: EEG (modality)

Methods: Spectral & time-frequency, Statistics, Machine learning, Smoothing, state filtering, decompositions, Preprocessing, Evoked potentials, Connectivity, fMRI & imaging, Physiology & signal measures

Keywords: temporal integration, somatosensory, timescales, touch, ERP

Topic: Tactile and Sensory Interactions (Cognitive Neuroscience, Neuroscience), according to OpenAlex

Funding: Velux Stiftung; China Scholarship Council

Citations: cited by 1 paper (Europe PMC); 62 references in the paper

Abstract

Sensory experiences in the real world cut across timescales from milliseconds to seconds. Emerging evidence suggests that somatosensory processing is sensitive to the temporal structure of the stimuli in the sub-second scale, yet only a few select ranges within this scale have been studied. To process real-world information, the integration of tactile inputs must occur over a much broader temporal range. To address temporal integration across timescales, we studied scalp EEG signals from somatosensory cortex in response to a train of tactile stimuli presented to the fingertips with varying inter-stimulus intervals (ISIs) spanning hundreds of milliseconds to several seconds. We captured the variations in cortical signals as a function of the subsequent ISIs (next interval structure). We tracked cortical tactile processing through its early (<75 ms), intermediate (75 to 150 ms), and late stages (150 to 300 ms). We find that the early and late stages of cortical activity were sensitive to the previous ISI; EEG signals were suppressed with ISIs <500 ms and enhanced with longer ISIs, with this effect persisting even when ISIs were approximately 8 s. The intermediate stage of cortical activity was sensitive to both the previous and the penultimate ISIs. Our findings suggest that the specific somatosensory cortical processing stages integrate temporal structure across timescales to enable complex sensory experiences.

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 2 matches between paragraphs and lines of code.

CODELABCODELIB/JID_ERP_Tactile_2024

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: cfa24adc342ef4f0f5f6d4967216437b05e5c4b8, 18 June 2025

Languages: MATLAB (32)

Size: 34 files, 32 scripts

Software Heritage: not archived

Found in: “Data and Code Availability”

Holds: README

Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation

Tools: Statistics and Machine Learning Toolbox (12 files), EEGLAB (6 files)

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

30 September 2026: the link answers

33 files

ANLJIDERPfigure1.m, MATLAB, 146 lines
ANLJIDERPfigure2.m, MATLAB, 117 lines
ANLkmeans.m, MATLAB, 110 lines
ANLonesamplettest.m, MATLAB, 141 lines
getANLbinerp.m, MATLAB, 84 lines
getANLbinerpavg.m, MATLAB, 87 lines
getANLbinerpavg_all.m, MATLAB, 60 lines
getANLcleandata.m, MATLAB, 60 lines
getANLerpavg.m, MATLAB, 77 lines
getANLerpavg_all.m, MATLAB, 37 lines
getANLerpmax_all.m, MATLAB, 23 lines
getcorrplot_population.m, MATLAB, 151 lines
main_nnmf.m, MATLAB, 78 lines
main_nnmf_individual.m, MATLAB, 129 lines
private/NMFfigure_population.m, MATLAB, 85 lines
private/choose_best_k.m, MATLAB, 33 lines
private/constrainelectrode.m, MATLAB, 47 lines
private/excludeparticipant.m, MATLAB, 28 lines
private/getbinerp.m, MATLAB, 74 lines
private/getbinerpavg.m, MATLAB, 54 lines
private/getbinerpvideo.m, MATLAB, 109 lines
private/getbinidx.m, MATLAB, 63 lines
private/getintervaldynamics.m, MATLAB, 59 lines
private/getmaxchan.m, MATLAB, 14 lines
private/getpopolationvideo.m, MATLAB, 76 lines
private/getreadyforanalysis.m, MATLAB, 79 lines, 1 match
private/imagesc2.m, MATLAB, 17 lines
private/nanzscore.m, MATLAB, 49 lines
private/readme.m, MATLAB, 1 line
private/rejecteyeblink.m, MATLAB, 34 lines, 1 match
private/selectelectrode.m, MATLAB, 20 lines
private/selectepoch.m, MATLAB, 51 lines
README.md, Text, 21 lines

At the source: github.com/CODELABCODELIB/JID_ERP_Tactile_2024

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;
32 scripts, each with its path and the digest of its content;
2 matches 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 and Code Availability

Pseudo-anonymized MATLAB.mat file containing processed JIERP data is made available on dataverse.nl upon publication; The custom-written scripts used towards this report are shared on: https://github.com/CODELABCODELIB/JID_ERP_Tactile_2024

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, pages, dates, 3 authors, 5 keywords, 2 funders, 62 references.

Cite

This paper

Wan, W., Ridderinkhof, K. R., & Ghosh, A. (2026). Cortical integration of tactile inputs distributed across timescales. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1146. https://doi.org/10.1162/imag.a.1146

BibTeX

@article{wan2026cortical, author = {Wan, Wenyu and Ridderinkhof, K Richard and Ghosh, Arko}, title = {{Cortical integration of tactile inputs distributed across timescales}}, journal = {Imaging neuroscience (Cambridge, Mass.)}, year = {2026}, month = mar, volume = {4}, pages = {IMAG.a.1146}, publisher = {MIT Press}, issn = {2837-6056}, doi = {10.1162/imag.a.1146}, url = {https://doi.org/10.1162/imag.a.1146}, pmid = {41799681}, pmcid = {PMC12961305} }

RIS

TY - JOUR AU - Wan, Wenyu AU - Ridderinkhof, K Richard AU - Ghosh, Arko TI - Cortical integration of tactile inputs distributed across timescales T2 - Imaging neuroscience (Cambridge, Mass.) J2 - Imaging Neurosci (Camb) PY - 2026 DA - 2026/03/03 VL - 4 SP - IMAG.a.1146 SN - 2837-6056 PB - MIT Press DO - 10.1162/imag.a.1146 UR - https://doi.org/10.1162/imag.a.1146 LA - en ER -

CSL-JSON

{ "id": "10.1162/imag.a.1146", "type": "article-journal", "title": "Cortical integration of tactile inputs distributed across timescales", "container-title": "Imaging neuroscience (Cambridge, Mass.)", "author": [ { "family": "Wan", "given": "Wenyu" }, { "family": "Ridderinkhof", "given": "K Richard" }, { "family": "Ghosh", "given": "Arko" } ], "container-title-short": "Imaging Neurosci (Camb)", "volume": "4", "page": "IMAG.a.1146", "DOI": "10.1162/imag.a.1146", "PMID": "41799681", "PMCID": "PMC12961305", "ISSN": "2837-6056", "publisher": "MIT Press", "URL": "https://doi.org/10.1162/imag.a.1146", "language": "en", "issued": { "date-parts": [ [ 2026, 3, 3 ] ] } }

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