OSCR

Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex.

Code ↔ Paper

9 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 9 matches
  1. [1] § 2. Materials and methods › 2.6. iEEG data preprocessing ↔ analysisBBFIR1.m, lines 126–252 · score 0.92 · Hilbert transform, linear interpolation, fold increase, 130 Hz, 4 ms, 110 Hz
  2. [2] § 2. Materials and methods › 2.6. iEEG data preprocessing ↔ fig1_FP_broadband_examples.m, lines 30–105 · score 0.82 · linear interpolation, adjacent, 130 Hz, 110 Hz, 170 Hz, Hilbert
  3. [3] § 2. Materials and methods › 2.5. Selection of measurement and stimulation electrodes ↔ tractography/ccepVisual_RenderTracks01.m, lines 39–95 · score 0.71 · forceps major, tractography, ILF, SLF, VOF, fiber
  4. [4] § 2. Materials and methods › 2.3. Task and stimuli ↔ functions/picturePrep/generatepermutedphase.m, lines 1–102 · score 0.70 · phase matrix, uniform distribution, Fourier, ratios, mixed, pi
  5. [5] § 2. Materials and methods › 2.3. Task and stimuli ↔ functions/picturePrep/generaterandomphaseFromInput.m, lines 1–89 · score 0.69 · phase matrix, original phase, Fourier, FFT, mixed, pi
  6. [6] § 3. Results ↔ functions/picturePrep/generatepermutedphase.m, lines 1–102 · score 0.62 · single pulse electrical, iEEG, early visual cortex, human, signal, modulates
  7. [7] § 3. Results ↔ functions/picturePrep/generaterandomphaseFromInput.m, lines 1–89 · score 0.60 · single pulse electrical, iEEG, early visual cortex, human, modulates
  8. [8] § 2. Materials and methods › 2.7. Finite impulse response analysis of stimulation and visual responses ↔ globalAnalysis2.m, lines 97–227 · score 0.58 · full model best, training trials, tailed, baseline, error, predictor
  9. [9] § 2. Materials and methods › 2.7. Finite impulse response analysis of stimulation and visual responses ↔ analysisBBFIR2.m, lines 247–368 · score 0.58 · full model best, training trials, tailed, baseline, error, predictor

Paper

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

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The authors' code

MATLAB · 116 lines · 5.2 KB · GPL-3.0 · 2 matches

  1. function f = generatepermutedphase(ph)
  3. % function f = generatepermutedphase(ph)
  4. %
  5. % Variant on knkutils/generaterandomphase -- phases are permuted from input rather than randomly generated from uniform distribution
  6. % ph must be 2D so one image is processed at a time
  7. %
  8. % DC component is kept the same so that the image mean doesn't change
  9. % All other real values in the signal (Nyquists) are also kept the same... this is so that if the output of this function, f, is mixed with the input
  10. % ph at some ratio (e.g., 50/50), the real values don't accidentally become imaginary (i.e. halfway between 0 and pi phase)
  11. %
  12. % return a <res> x <res> matrix with elements that are unit-length complex
  13. % numbers. this matrix is ready for multiplication with the output of fft2.
  14. % the result is to randomly perturb the phase of each Fourier component of each image.
  15. % note that some of the Fourier components (e.g. the DC component) are special in that
  16. % the complex numbers corresponding to these components are restricted to be either 1 or -1,
  17. % since these components have no imaginary part.
  18. %
  19. % If this code is used in a publication, please cite the manuscript:
  20. % "H Huang, KN Kay, NM Gregg, G Ojeda Valencia, M In, C Kapeller, Y Shu, GA Worrell, KJ Miller, and D Hermes.
  21. % Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex. (Under Review)"
  22. %
  23. % A preprint is available currently at doi: https://doi.org/10.1101/2025.05.05.652264.
  24. %
  25. % The dataset corresponding to this code and manuscript is in BIDS format (version 1.10.0) on OpenNeuro (ds006485),
  26. % and it will be made publicly available upon manuscript acceptance.
  27. %
  28. % Copyright (C) 2025 Harvey Huang
  29. %
  30. % This program is free software: you can redistribute it and/or modify
  31. % it under the terms of the GNU General Public License as published by
  32. % the Free Software Foundation, either version 3 of the License, or
  33. % (at your option) any later version.
  34. %
  35. % This program is distributed in the hope that it will be useful,
  36. % but WITHOUT ANY WARRANTY; without even the implied warranty of
  37. % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  38. % GNU General Public License for more details.
  39. %
  40. % You should have received a copy of the GNU General Public License
  41. % along with this program. If not, see <https://www.gnu.org/licenses/>.
  42. %
  43. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  44. %
  45. %
  46. % example:
  47. % a = randn(5,5);
  48. % b = fft2(a) .* generaterandomphase(5);
  49. % c = ifft2(b);
  50. % allzero(imag(c))
  52. res = size(ph, 1); assert(size(ph, 1) == size(ph, 2), 'Input phase matrix is not square');
  53. dc = ph(1); % dc component -- keep the same so image mean doesn't invert
  55. % Get one half of the mirror symmetrical phase distribution and real (nyquist) center phases along both legs and in matrix center
  56. if ~mod(res, 2)
  57. subM = ph(2:end, 2:end); % phase matrix excluding legs
  58. centers = [ph(res/2+1, 1), ph(1, res/2+1), subM((numel(subM)+1)/2)]; % in order: centers of vertical, horizontal legs, then center of submatrix
  59. distr = [ph(2:res/2, 1); ph(1, 2:res/2)'; subM(1:(numel(subM)-1)/2)'];
  60. else
  61. error('Not equipped to handle odd resolution inputs');
  62. % nn = (res*res-1)/2; % e.g., if 1079 x 1079, index up to 540col, 539row (just before center)
  63. % centers = ph(nn + 1); % preserve the same center (nyquist) value (0 or pi)
  64. % distr = ph(2:nn);
  65. end
  67. % randomly permute phase distribution
  68. distr = distr(randperm(length(distr)));
  70. % do it
  71. if mod(res,2)==0
  73. f = zeros(size(ph));
  75. f(1) = dc; % replace dc
  77. % fill in vertical leg
  78. f(2:res/2, 1) = distr(1:(res/2-1));
  79. f(res/2+1, 1) = centers(1);
  80. f((res/2+2):end, 1) = -flip(f(2:res/2, 1)); % mirror-symmetric from first half
  81. distr(1:(res/2-1)) = []; % remove used values from distribution
  83. % fill in horizontal leg as with vertical leg
  84. f(1, 2:res/2) = distr(1:(res/2-1));
  85. f(1, res/2+1) = centers(2);
  86. f(1, (res/2+2):end) = -flip(f(1, 2:res/2));
  87. distr(1:(res/2-1)) = [];
  89. % fill in the rest of the matrix
  90. subf = f(2:end, 2:end);
  91. subf(1:(numel(subf)-1)/2) = distr; % if this isn't the right size something is wrong with assigning distribution
  92. subf((numel(subf)+1)/2) = centers(3);
  93. subf((numel(subf)+1)/2 + 1:end) = -flip(distr);
  94. f(2:end, 2:end) = subf; % insert back into full matrix
  95. else
  96. f = helper(res,num); % need to figure out under what setting this actually works correctly. Doesn't work if fft2 image is odd sized
  97. end
  99. % convert to imaginary numbers
  100. f = exp(1i*f);
  102. %%%%%
  104. function f = helper(res,num)
  106. % return a matrix of dimensions <res> x <res> x <num> with appropriate
  107. % random phase values in [0,2*pi]. note that the center (DC component)
  108. % has phase values that are either 0 or pi. the returned matrix is
  109. % as if fftshift has been called.
  111. f = zeros(res*res,num); % initialize in convenient form
  112. nn = (res*res-1)/2; % how many in first half?
  113. f(1:nn,:) = rand(nn,num)*(2*pi); % fill in the first half with random phase in [0,2*pi]
  114. f = reshape(f,[res res num]); % reshape
  115. f = f + -flipdim(flipdim(f,1),2); % symmetrize (the mirror gets the negative phase)
  116. f((res+1)/2,(res+1)/2,:) = (rand(1,1,num)>.5)*pi; % fill in the center (either 0 or pi)

generatepermutedphase.m at commit 3eb20d8, under GPL-3.0 · at the source

Overview

Authors: Harvey Huang1, Kendrick N Kay2, Nicholas M Gregg3, Gabriela Ojeda Valencia4, Myung-Ho In5, Christoph Kapeller6, Yunhong Shu5, Gregory A Worrell3,4, Kai J Miller4,7, Dora Hermes3,4,5
ORCID iDs: Harvey Huang, Kendrick N Kay, Nicholas M Gregg, Gabriela Ojeda Valencia, Myung-Ho In, Christoph Kapeller, Yunhong Shu, Gregory A Worrell, Kai J Miller, Dora Hermes
  1. Medical Scientist Training Program, Mayo Clinic, Rochester, Minnesota, United States of America
  2. Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, United States of America
  3. Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
  4. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America
  5. Department of Radiology, Mayo Clinic, Rochester, Minnesota, United States of America
  6. Invasive Technologies, g.tec medical engineering GmbH, Schiedlberg, Austria
  7. Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota, United States of America
Institutions: Mayo Clinic (United States); University of Minnesota (United States); Guger Technologies (Austria) (Austria)
Journal: PLoS computational biology, volume 22, issue 7, article e1014563
Dates: received 21 July 2025; accepted 9 July 2026; published online 24 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1371/journal.pcbi.1014563 · PMID 42497215 · PMCID PMC13426923 · OpenAlex W4410252750
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.05.05.652264
Status: code verified
Categories: EEG (modality), intracranial EEG (iEEG / ECoG / SEEG) (modality), human (organism), systems (subfield)
Methods: Spectral & time-frequency, Connectivity, Statistics, Preprocessing, fMRI & imaging
MeSH: Electric Stimulation*, Evoked Potentials, Visual*, Visual Cortex*, White Matter*, Adult, Computational Biology, Electroencephalography, Female, Humans, Male, Photic Stimulation (* major topic)
Topic: Neuroscience and Neural Engineering (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex
Funding: NEI NIH HHS (R01 EY035533); NIMH NIH HHS (R01 MH122258); NIGMS NIH HHS (T32 GM145408); NINDS NIH HHS (U01 NS128612)
Citations: not cited yet (Europe PMC); 52 references in the paper

Abstract

Introduction: Electrical stimulation is increasingly used to modulate brain networks for clinical purposes. The basic unit of neurostimulation, a single electrical pulse, can travel through white matter to influence connected neuronal populations. However, the mechanisms by which it influences connected populations is not well understood: stimulation may excite, inhibit, or add noise to neuronal population activity.

Materials and methods: In this study, we investigated how single pulses modulate the neuronal processing of images in a well-controlled visual paradigm. In two human subjects implanted with iEEG electrodes for clinical purposes, single pulses were delivered to electrodes in white matter tracts connected to measurement electrodes in visual cortex. Images appeared on-screen at 0, 100, or 200 ms after each pulse. Using finite impulse response modeling, we decomposed the broadband and evoked potential responses into separate components induced by electrical stimulation and by visual processing.

Results: Single pulses induced transient broadband increases followed by suppression, but they did not modulate the visual broadband responses (i.e., stimulation response was additive to visual response). In contrast, single pulses elicited prominent brain stimulation evoked potentials and they modulated the visual evoked potentials. Specifically, visual evoked potentials were larger when stimulation occurred closer to visual onset. This indicates that a single electrical pulse can increase the strength or synchrony of visual inputs.

Conclusion: Overall, these findings suggest that the effects of electrical stimulation in the visual system are two-fold: stimulation induces additive effects on broadband power, possibly by adding noise, and it interacts with synchronous visual inputs to amplify them.

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 9 matches between paragraphs and lines of code.

hharveygit/SPES_Visual

License: GPL-3.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 3eb20d84f819490ac2e94fd9b17232ffe6c05432, 9 May 2026
Languages: MATLAB (234), C (6)
Size: 533 files, 240 scripts
Software Heritage: not archived
Found in: “Data Availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (27 files), Image Processing Toolbox (4 files), SPM (4 files), Optimization Toolbox (3 files), ANTs (2 files), FreeSurfer (2 files), GIfTI library for MATLAB (2 files), Signal Processing Toolbox (2 files), fdr_bh (Benjamini-Hochberg FDR) (1 file), Curve Fitting Toolbox (1 file), Parallel Computing Toolbox (1 file), MRtrix3 (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
242 files
At the source: github.com/hharveygit/SPES_Visual

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;
  • 240 scripts, each with its path and the digest of its content;
  • 9 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

Datasets cited

Data Availability

The complete data that support these findings are freely accessible on OpenNeuro: https://openneuro.org/datasets/ds007703/versions/1.0.0. All analyses were performed in MATLAB R2023a. The comprehensive code used to generate all results and figures is publicly available on GitHub: https://github.com/hharveygit/SPES_Visual.

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 2, 28 September 2026

  • Authors: added Nicholas M Gregg (0000-0002-6151-043X); Gabriela Ojeda Valencia (0000-0002-5002-3310); Myung-Ho In (0000-0001-8001-6237); Yunhong Shu (0000-0002-7521-9088); Gregory A Worrell (0000-0003-2916-0553); Kai J Miller (0000-0002-6687-6422); removed Nicholas M Gregg; Gabriela Ojeda Valencia; Myung-Ho In; Yunhong Shu; Gregory A Worrell; Kai J Miller

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 11 MeSH terms, 4 funders, 52 references.

Cite

This paper

Huang, H., Kay, K. N., Gregg, N. M., Ojeda Valencia, G., In, M.-H., Kapeller, C., Shu, Y., Worrell, G. A., Miller, K. J., & Hermes, D. (2026). Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex. PLoS computational biology, 22(7), e1014563. https://doi.org/10.1371/journal.pcbi.1014563

BibTeX

@article{huang2026single,
author = {Huang, Harvey and Kay, Kendrick N and Gregg, Nicholas M and Ojeda Valencia, Gabriela and In, Myung-Ho and Kapeller, Christoph and Shu, Yunhong and Worrell, Gregory A and Miller, Kai J and Hermes, Dora},
title = {{Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex}},
journal = {PLoS computational biology},
year = {2026},
month = jul,
volume = {22},
number = {7},
pages = {e1014563},
publisher = {PLOS},
issn = {1553-734X},
doi = {10.1371/journal.pcbi.1014563},
url = {https://doi.org/10.1371/journal.pcbi.1014563},
pmid = {42497215},
pmcid = {PMC13426923}
}

RIS

TY - JOUR
AU - Huang, Harvey
AU - Kay, Kendrick N
AU - Gregg, Nicholas M
AU - Ojeda Valencia, Gabriela
AU - In, Myung-Ho
AU - Kapeller, Christoph
AU - Shu, Yunhong
AU - Worrell, Gregory A
AU - Miller, Kai J
AU - Hermes, Dora
TI - Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex
T2 - PLoS computational biology
J2 - PLoS Comput Biol
PY - 2026
DA - 2026/07/24
VL - 22
IS - 7
SP - e1014563
SN - 1553-734X
PB - PLOS
DO - 10.1371/journal.pcbi.1014563
UR - https://doi.org/10.1371/journal.pcbi.1014563
LA - en
ER -

CSL-JSON

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