Multimodal evidence for hippocampal engagement and modulation by functional connectivity-guided parietal TMS.

Code ↔ Paper

3 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 3 matches · all tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted

[1] § Methods › Concurrent spTMS-iEEG experiment › iEEG preprocessing ↔ toolbox/jw_import_neuralynx.m, the whole file · a weak match · score 0.81 · notch filter, bandpass filter, FieldTrip, cutoff, noise, 57 Hz
[2] § Methods › Concurrent spTMS-iEEG experiment › iEEG preprocessing ↔ toolbox/dh_cleanartifact_interp.m, the whole file · a weak match · score 0.69 · TMS artifact, FieldTrip, rejected, cutoff, Algorithm, segments
[3] § Methods › Concurrent spTMS-iEEG experiment › Time-frequency analysis of iTEPs ↔ toolbox/dh_cleanartifact_interp.m, the whole file · a weak match · score 0.55 · TMS artifacts, 110 Hz, cutoff, baseline, window, 50 ms

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The paper is loaded by your browser, with JavaScript: read it at doi.org or on Europe PMC.

The authors' code

MATLAB · 60 lines · 2.7 KB · no license · 2 matches

function clean = dh_cleanartifact_interp(data,trigTimes,prebuffer,postbuffer,useSIGNI)
% DH_CLEANARTIFACT_INTERP removes large artifacts by using z-value artifact
% detection followed by SIGNIS interpolation
%
% Author: Danny Huang, adapted into function by Jeffrey B. Wang
%
% Inputs:
% data: Original EEG, in the Fieldtrip "raw" format
% trigTimes: Time (in seconds) for when the artifacts occur
% buffer: how long (in seconds) to scrub beyond each trigger time
% Output:
% clean: Fieldtrip structure of the cleaned data
%
% cfgir = [];
% cfgir.continuous = 'yes';
%
% % channel selection, cutoff and padding
% cfgir.artfctdef.zvalue.channel = 'all'; % YOU CAN SPECIFY CHANNEL USED FOR ARTIFACT DETECTION, HERE I USE ALL CHANNELS
% cfgir.artfctdef.zvalue.cutoff = cutoff; % THE CUT OFF THRESHOLD TO PICKING ARTIFACT. 50 SEEMS TO PICK UP ONLY THE STIM ARTIFACTS
% %cfgir.artfctdef.zvalue.trlpadding = -0.1; % to prevent edge artifact recognition
% %cfgir.artfctdef.zvalue.artpadding = 0.01;
% %cfgir.artfctdef.zvalue.fltpadding = 0.1;
%
% % algorithmic parameters to detect artifacts, TMS artifact should be
% % high-frequency?
% cfgir.artfctdef.zvalue.bpfilter = 'yes';
% cfgir.artfctdef.zvalue.bpfilttype = 'but';
% cfgir.artfctdef.zvalue.bpfreq = [150 200]; %[1 200];
% cfgir.artfctdef.zvalue.bpfiltord = 4;
% cfgir.artfctdef.zvalue.baselinewindow = [80 110];
% cfgir.artfctdef.zvalue.hilbert = 'yes';
% %cfgir.artfctdef.zvalue.rectify = 'yes';
%
% % make the process interactive
% cfgir.artfctdef.zvalue.interactive = 'no';
%
% [~, artifact_stim] = ft_artifact_zvalue(cfgir, data);
%% reject artfact
cfgi = [];
cfgi.artfctdef.reject = 'nan';
cfgi.artfctdef.feedback = 'no';
cfgi.artfctdef.xxx.artifact = zeros(length(trigTimes),2);
cfgi.artfctdef.xxx.artifact(:,1) = round((trigTimes - prebuffer) * data.fsample);
cfgi.artfctdef.xxx.artifact(:,2) = round((trigTimes + postbuffer) * data.fsample);
spikeTrain_ft_nan = ft_rejectartifact(cfgi, data);
%% Interpolate nans using cubic interpolation
cfgi = [];
cfgi.method = 'pchip'; % Here you can specify any method that is supported by interp1: 'nearest','linear','spline','pchip','cubic','v5cubic'
%cfgi.method = 'cubic'; % Here you can specify any method that is supported by interp1: 'nearest','linear','spline','pchip','cubic','v5cubic'
cfgi.prewindow = 0.01; % Window prior to segment to use data points for interpolation
cfgi.postwindow = 0.01; % Window after segment to use data points for interpolation
cfgi.useSIGNI = useSIGNI;
if sum(isnan(spikeTrain_ft_nan.trial{1}),'All')
clean = dh_interpolatenan(cfgi, spikeTrain_ft_nan); % Clean data
else
clean = data;
end

dh_cleanartifact_interp.m at commit c78359e, no license · at the source

Overview

Authors: Zhuoran Li^1,2,3, Nicholas T. Trapp^2,3,4, Joel Bruss¹, Xianqing Liu¹, Kang Wu¹, Ziyan Chen¹, Amit Etkin⁵, Matthew A. Howard^4,6, Aaron D. Boes^1,2,3,4, Jing Jiang^1,2,3

ORCID iDs: Joel Bruss, Kang Wu, Amit Etkin, Aaron D. Boes, Jing Jiang

Stead Family Department of Pediatrics, University of Iowa,Iowa City, IA USA
Department of Psychiatry, University of Iowa,Iowa City, IA USA
Iowa Neuroscience Institute, University of Iowa,Iowa City, IA USA
Department of Neurology, University of Iowa,Iowa City, IA USA
Alto Neuroscience,Mountain View, CA USA
Department of Neurosurgery, University of Iowa,Iowa City, IA USA

Institutions: University of Iowa (United States); Alto Neuroscience (United States) (United States)

Journal: Nature communications, volume 17, issue 1, article 3650

Dates: received 24 June 2025; accepted 24 February 2026; published online 8 March 2026

Type: Research article · Language: English

License: CC BY-NC-ND

Identifiers: DOI 10.1038/s41467-026-70346-x · PMID 41794924 · PMCID PMC13096217 · OpenAlex W7134183494

Open access: gold, a free copy (OpenAlex)

Status: code verified

Categories: EEG (modality), other (modality), human (organism), systems (subfield)

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

Keywords: Hippocampus, Neural circuits

MeSH: Hippocampus*, Parietal Lobe*, Transcranial Magnetic Stimulation*, Adult, Brain Mapping, Electroencephalography, Female, Humans, Magnetic Resonance Imaging, Male, Memory, Middle Aged, Theta Rhythm, Young Adult (* major topic)

Topic: Transcranial Magnetic Stimulation Studies (Neurology, Neuroscience), according to OpenAlex

Funding: NIH (R01MH136197, R01MH103324, R21MH120441, R01NS114405); Brain and Behavior Research Foundation (29441, 31275); National Institute of Mental Health (1K23MH125145, R01MH125160, R01MH132074); Magnus Medical, Inc; Roy J. Carver Trust

Citations: cited by 3 papers (Europe PMC); 57 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

JingjiangLab/Parietal-Hippocampus

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: c78359e0556e554971d4d58dcc713a872b922023, 8 November 2025

Languages: C++ (24), MATLAB (22), C/C++ (17), Shell (1)

Size: 89 files, 64 scripts

Software Heritage: not archived

Found in: “Data availability”

Holds: README

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

Tools: FieldTrip (8 files), Image Processing Toolbox (1 file), Parallel Computing Toolbox (1 file), 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

65 files

P1_TMS_iEEG_preprocessing.m, MATLAB, 449 lines
P2_Detrend.m, MATLAB, 234 lines
demo_preprocess.m, MATLAB, 128 lines
numSubplots.m, MATLAB, 61 lines
toolbox/dh_cleanartifact_interp.m, MATLAB, 60 lines, 2 matches
toolbox/dh_interpolatenan.m, MATLAB, 185 lines
toolbox/generate_reref_matrix.m, MATLAB, 63 lines
toolbox/jw_extract_trig_times.m, MATLAB, 44 lines
toolbox/jw_import_neuralynx.m, MATLAB, 53 lines, 1 match
toolbox/nlx2Mat/Mat2NlxCSC.m, MATLAB, 137 lines
toolbox/nlx2Mat/Mat2NlxSE.m, MATLAB, 137 lines
toolbox/nlx2Mat/Mat2NlxTT.m, MATLAB, 137 lines
toolbox/nlx2Mat/compile.sh, Shell, 79 lines
toolbox/nlx2Mat/getRawCSCData.m, MATLAB, 25 lines
toolbox/nlx2Mat/getRawCSCTimestamps.m, MATLAB, 29 lines
toolbox/nlx2Mat/getRawSE.m, MATLAB, 40 lines
toolbox/nlx2Mat/getRawTTLs.m, MATLAB, 22 lines
toolbox/nlx2Mat/putRawCSC.m, MATLAB, 53 lines
toolbox/nlx2Mat/putRawEV.m, MATLAB, 45 lines
toolbox/nlx2Mat/putRawEV_verify.m, MATLAB, 39 lines
toolbox/nlx2Mat/putRawTT.m, MATLAB, 40 lines
toolbox/nlx2Mat/source/FileDataBucket.cpp, C++, 470 lines
toolbox/nlx2Mat/source/FileDataBucket.h, C/C++, 54 lines
toolbox/nlx2Mat/source/GeneralOperations.cpp, C++, 451 lines
toolbox/nlx2Mat/source/GeneralOperations.h, C/C++, 57 lines
toolbox/nlx2Mat/source/Mat2NlxCSC.cpp, C++, 150 lines
toolbox/nlx2Mat/source/Mat2NlxEV.cpp, C++, 151 lines
toolbox/nlx2Mat/source/Mat2NlxSE.cpp, C++, 162 lines
toolbox/nlx2Mat/source/Mat2NlxTT.cpp, C++, 161 lines
toolbox/nlx2Mat/source/Nlx2MatCSC.cpp, C++, 25 lines
toolbox/nlx2Mat/source/Nlx2MatEV.cpp, C++, 25 lines
toolbox/nlx2Mat/source/Nlx2MatEVInclude.h, C/C++, 58 lines
toolbox/nlx2Mat/source/Nlx2MatSpike.cpp, C++, 24 lines
toolbox/nlx2Mat/source/Nlx2MatVTInclude.h, C/C++, 57 lines
toolbox/nlx2Mat/source/Nlx2MatVt.cpp, C++, 29 lines
toolbox/nlx2Mat/source/Nlx_Code.cpp, C++, 636 lines
toolbox/nlx2Mat/source/Nlx_Code.h, C/C++, 300 lines
toolbox/nlx2Mat/source/Nlx_DataTypes.h, C/C++, 218 lines
toolbox/nlx2Mat/source/Nlx_Error.h, C/C++, 254 lines
toolbox/nlx2Mat/source/Nlx_ObjNames.h, C/C++, 59 lines
toolbox/nlx2Mat/source/ProcessorCSC.cpp, C++, 255 lines
toolbox/nlx2Mat/source/ProcessorCSC.h, C/C++, 48 lines
toolbox/nlx2Mat/source/ProcessorEV.cpp, C++, 260 lines
toolbox/nlx2Mat/source/ProcessorEV.h, C/C++, 47 lines
toolbox/nlx2Mat/source/ProcessorSpike.cpp, C++, 655 lines
toolbox/nlx2Mat/source/ProcessorSpike.h, C/C++, 65 lines
toolbox/nlx2Mat/source/ProcessorVT.cpp, C++, 262 lines
toolbox/nlx2Mat/source/ProcessorVT.h, C/C++, 43 lines
toolbox/nlx2Mat/source/StdString.h, C/C++, 3,017 lines
toolbox/nlx2Mat/source/TimeBuf.cpp, C++, 371 lines
toolbox/nlx2Mat/source/TimeBuf.h, C/C++, 200 lines
toolbox/nlx2Mat/source/TimeCSCBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeEventBuf.cpp, C++, 49 lines
toolbox/nlx2Mat/source/TimeMClustTSBuf.cpp, C++, 39 lines
toolbox/nlx2Mat/source/TimeSEBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeSTBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeTSBuf.cpp, C++, 40 lines
toolbox/nlx2Mat/source/TimeTTBuf.cpp, C++, 47 lines
toolbox/nlx2Mat/source/TimeVideoBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/compatibility.h, C/C++, 45 lines
toolbox/nlx2Mat/source/compatibility32.h, C/C++, 46 lines
toolbox/nlx2Mat/source/compatibility64.h, C/C++, 45 lines
toolbox/prefilter_data.m, MATLAB, 61 lines
toolbox/reselect_channels.m, MATLAB, 12 lines
README.md, Text, 35 lines

At the source: github.com/JingjiangLab/Parietal-Hippocampus.git

Zenodo 18355225

License: CC-BY-4.0

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Size: 1 file

Software Heritage: not checked

Found in: “Code availability”

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

Tools: FieldTrip (8 files), Image Processing Toolbox (1 file), Parallel Computing Toolbox (1 file), Statistics and Machine Learning Toolbox (1 file)

Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

65 files

P1_TMS_iEEG_preprocessing.m, MATLAB, 449 lines
P2_Detrend.m, MATLAB, 234 lines
demo_preprocess.m, MATLAB, 128 lines
numSubplots.m, MATLAB, 61 lines
toolbox/dh_cleanartifact_interp.m, MATLAB, 60 lines
toolbox/dh_interpolatenan.m, MATLAB, 185 lines
toolbox/generate_reref_matrix.m, MATLAB, 63 lines
toolbox/jw_extract_trig_times.m, MATLAB, 44 lines
toolbox/jw_import_neuralynx.m, MATLAB, 53 lines
toolbox/nlx2Mat/Mat2NlxCSC.m, MATLAB, 137 lines
toolbox/nlx2Mat/Mat2NlxSE.m, MATLAB, 137 lines
toolbox/nlx2Mat/Mat2NlxTT.m, MATLAB, 137 lines
toolbox/nlx2Mat/compile.sh, Shell, 79 lines
toolbox/nlx2Mat/getRawCSCData.m, MATLAB, 25 lines
toolbox/nlx2Mat/getRawCSCTimestamps.m, MATLAB, 29 lines
toolbox/nlx2Mat/getRawSE.m, MATLAB, 40 lines
toolbox/nlx2Mat/getRawTTLs.m, MATLAB, 22 lines
toolbox/nlx2Mat/putRawCSC.m, MATLAB, 53 lines
toolbox/nlx2Mat/putRawEV.m, MATLAB, 45 lines
toolbox/nlx2Mat/putRawEV_verify.m, MATLAB, 39 lines
toolbox/nlx2Mat/putRawTT.m, MATLAB, 40 lines
toolbox/nlx2Mat/source/FileDataBucket.cpp, C++, 470 lines
toolbox/nlx2Mat/source/FileDataBucket.h, C/C++, 54 lines
toolbox/nlx2Mat/source/GeneralOperations.cpp, C++, 451 lines
toolbox/nlx2Mat/source/GeneralOperations.h, C/C++, 57 lines
toolbox/nlx2Mat/source/Mat2NlxCSC.cpp, C++, 150 lines
toolbox/nlx2Mat/source/Mat2NlxEV.cpp, C++, 151 lines
toolbox/nlx2Mat/source/Mat2NlxSE.cpp, C++, 162 lines
toolbox/nlx2Mat/source/Mat2NlxTT.cpp, C++, 161 lines
toolbox/nlx2Mat/source/Nlx2MatCSC.cpp, C++, 25 lines
toolbox/nlx2Mat/source/Nlx2MatEV.cpp, C++, 25 lines
toolbox/nlx2Mat/source/Nlx2MatEVInclude.h, C/C++, 58 lines
toolbox/nlx2Mat/source/Nlx2MatSpike.cpp, C++, 24 lines
toolbox/nlx2Mat/source/Nlx2MatVTInclude.h, C/C++, 57 lines
toolbox/nlx2Mat/source/Nlx2MatVt.cpp, C++, 29 lines
toolbox/nlx2Mat/source/Nlx_Code.cpp, C++, 636 lines
toolbox/nlx2Mat/source/Nlx_Code.h, C/C++, 300 lines
toolbox/nlx2Mat/source/Nlx_DataTypes.h, C/C++, 218 lines
toolbox/nlx2Mat/source/Nlx_Error.h, C/C++, 254 lines
toolbox/nlx2Mat/source/Nlx_ObjNames.h, C/C++, 59 lines
toolbox/nlx2Mat/source/ProcessorCSC.cpp, C++, 255 lines
toolbox/nlx2Mat/source/ProcessorCSC.h, C/C++, 48 lines
toolbox/nlx2Mat/source/ProcessorEV.cpp, C++, 260 lines
toolbox/nlx2Mat/source/ProcessorEV.h, C/C++, 47 lines
toolbox/nlx2Mat/source/ProcessorSpike.cpp, C++, 655 lines
toolbox/nlx2Mat/source/ProcessorSpike.h, C/C++, 65 lines
toolbox/nlx2Mat/source/ProcessorVT.cpp, C++, 262 lines
toolbox/nlx2Mat/source/ProcessorVT.h, C/C++, 43 lines
toolbox/nlx2Mat/source/StdString.h, C/C++, 3,017 lines
toolbox/nlx2Mat/source/TimeBuf.cpp, C++, 371 lines
toolbox/nlx2Mat/source/TimeBuf.h, C/C++, 200 lines
toolbox/nlx2Mat/source/TimeCSCBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeEventBuf.cpp, C++, 49 lines
toolbox/nlx2Mat/source/TimeMClustTSBuf.cpp, C++, 39 lines
toolbox/nlx2Mat/source/TimeSEBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeSTBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/TimeTSBuf.cpp, C++, 40 lines
toolbox/nlx2Mat/source/TimeTTBuf.cpp, C++, 47 lines
toolbox/nlx2Mat/source/TimeVideoBuf.cpp, C++, 45 lines
toolbox/nlx2Mat/source/compatibility.h, C/C++, 45 lines
toolbox/nlx2Mat/source/compatibility32.h, C/C++, 46 lines
toolbox/nlx2Mat/source/compatibility64.h, C/C++, 45 lines
toolbox/prefilter_data.m, MATLAB, 61 lines
toolbox/reselect_channels.m, MATLAB, 12 lines
README.md, Text, 35 lines

At the source:

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

it points to the authors' code: JingjiangLab/Parietal-Hippocampus, Zenodo 18355225

Read it in the paper: doi.org/10.1038/s41467-026-70346-x.

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.

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2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
128 scripts, each with its path and the digest of its content;
3 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.

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

it points to the authors' code: JingjiangLab/Parietal-Hippocampus, Zenodo 18355225
it says that the data are available on request

Read it in the paper: doi.org/10.1038/s41467-026-70346-x.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 2 keywords, 14 MeSH terms, 5 funders, 57 references.

Cite

This paper

Li, Z., Trapp, N. T., Bruss, J., Liu, X., Wu, K., Chen, Z., Etkin, A., Howard, M. A., Boes, A. D., & Jiang, J. (2026). Multimodal evidence for hippocampal engagement and modulation by functional connectivity-guided parietal TMS. Nature communications, 17(1), 3650. https://doi.org/10.1038/s41467-026-70346-x

BibTeX

@article{li2026multimodal, author = {Li, Zhuoran and Trapp, Nicholas T. and Bruss, Joel and Liu, Xianqing and Wu, Kang and Chen, Ziyan and Etkin, Amit and Howard, Matthew A. and Boes, Aaron D. and Jiang, Jing}, title = {{Multimodal evidence for hippocampal engagement and modulation by functional connectivity-guided parietal TMS}}, journal = {Nature communications}, year = {2026}, month = mar, volume = {17}, number = {1}, pages = {3650}, publisher = {Nature Publishing Group}, issn = {2041-1723}, doi = {10.1038/s41467-026-70346-x}, url = {https://doi.org/10.1038/s41467-026-70346-x}, pmid = {41794924}, pmcid = {PMC13096217} }

RIS

TY - JOUR AU - Li, Zhuoran AU - Trapp, Nicholas T. AU - Bruss, Joel AU - Liu, Xianqing AU - Wu, Kang AU - Chen, Ziyan AU - Etkin, Amit AU - Howard, Matthew A. AU - Boes, Aaron D. AU - Jiang, Jing TI - Multimodal evidence for hippocampal engagement and modulation by functional connectivity-guided parietal TMS T2 - Nature communications J2 - Nat Commun PY - 2026 DA - 2026/03/08 VL - 17 IS - 1 SP - 3650 SN - 2041-1723 PB - Nature Publishing Group DO - 10.1038/s41467-026-70346-x UR - https://doi.org/10.1038/s41467-026-70346-x LA - en ER -

CSL-JSON

{ "id": "10.1038/s41467-026-70346-x", "type": "article-journal", "title": "Multimodal evidence for hippocampal engagement and modulation by functional connectivity-guided parietal TMS", "container-title": "Nature communications", "author": [ { "family": "Li", "given": "Zhuoran" }, { "family": "Trapp", "given": "Nicholas T." }, { "family": "Bruss", "given": "Joel" }, { "family": "Liu", "given": "Xianqing" }, { "family": "Wu", "given": "Kang" }, { "family": "Chen", "given": "Ziyan" }, { "family": "Etkin", "given": "Amit" }, { "family": "Howard", "given": "Matthew A." }, { "family": "Boes", "given": "Aaron D." }, { "family": "Jiang", "given": "Jing" } ], "container-title-short": "Nat Commun", "volume": "17", "issue": "1", "page": "3650", "DOI": "10.1038/s41467-026-70346-x", "PMID": "41794924", "PMCID": "PMC13096217", "ISSN": "2041-1723", "publisher": "Nature Publishing Group", "URL": "https://doi.org/10.1038/s41467-026-70346-x", "language": "en", "issued": { "date-parts": [ [ 2026, 3, 8 ] ] } }

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