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Thalamic transcranial electrical stimulation with temporal interference enhances sleep spindle activity during a daytime nap.

Code ↔ Paper

5 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 5 matches · 2 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Materials and methods › Sleep spindle detection ↔ ISA from YASA.m, the whole file · a weak match · score 0.71 · spindle detection, detected spindle, Integrated spindle activity, events, duration, interval
  2. [2] § Materials and methods › Statistical analysis ↔ Figure 3A-Table 2.R, lines 12–43 · score 0.70 · regression models, band power, sigma power, TIPeak, stimulation protocols, TI10Hz
  3. [3] § Materials and methods › E‌EG data acquisition and preprocessing ↔ Figure 3C.m, lines 1–67 · score 0.58 · Power spectral density, power bands, channels
  4. [4] § Materials and methods › E‌EG data acquisition and preprocessing ↔ ISA from YASA.m, the whole file · a weak match · score 0.56 · pop_eegfiltnew, EEGLAB, channels, filtered
  5. [5] § Results › Low-frequency EEG power increased and high-frequency power decreased in all protocols between PRE and STIM epochs, reflecting increasing sleep depth during N2 ↔ Figure 3A-Table 2.R, lines 12–43 · score 0.55 · sigma band power, TIPeak, stimulation protocol, TI10Hz, TES15kHz, STIM PRE

Paper

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

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The authors' code

MATLAB · 118 lines · 4.8 KB · no license · 2 matches

  1. addpath(genpath('D:/Code/EEG/eeglab2024.1'))
  2. addpath(genpath('D:/Studies/REM-REST/Code/EEG/ti_process-main_RR'))
  4. root_path = 'Z:/REM-REST/spindle_detection/spindles/data';
  5. results_folder_path = 'Z:/REM-REST/spindle_detection/spindles/results';
  6. which_protos_file = 'Z:/REM-REST/spindle_detection/spindles/Spindles_protos.xlsx';
  7. save_path = fullfile(results_folder_path, 'int_spindle_activity');
  8. if ~exist(save_path)
  9. mkdir(save_path)
  10. end
  11. spindle_range = [11 16];
  13. d = readtable(which_protos_file);
  14. protos_table = d(:, [1:6]);
  16. for iProto = 1:size(d,1)
  17. % load EEG and filter in the spindle range
  18. sub = sprintf('%03d', d.Sub(iProto));
  19. sess = d.Sess{iProto};
  20. abs_proto = d.abs_proto(iProto);
  22. EEG = pop_loadset(fullfile(root_path, sub, sess, sprintf('REMREST_%s_%s_forYasa.set', sub, sess)));
  23. EEG = pop_eegfiltnew(EEG, spindle_range(1), spindle_range(2), [], 0, [], 0);
  25. % find pre and stim intervals and define intervals duration
  26. % ramping periods excluded
  27. for iEv = 1:size(EEG.event, 2)
  28. if abs_proto == EEG.event(iEv).proto_ind
  29. if strcmp(EEG.event(iEv).type, 'pre start')
  30. pre_start = EEG.event(iEv).latency;
  31. end
  32. if strcmp(EEG.event(iEv).type, 'stim start') % ramp up start
  33. pre_end = EEG.event(iEv).latency;
  34. end
  35. if strcmp(EEG.event(iEv).type, 'max stim start') % ramp up end
  36. stim_start = EEG.event(iEv).latency;
  37. end
  38. if strcmp(EEG.event(iEv).type, 'max stim end') % ramp down start
  39. stim_end = EEG.event(iEv).latency;
  40. end
  41. end
  42. end
  44. pre_dur = pre_end - pre_start;
  45. stim_dur = stim_end - stim_start;
  48. % load list of detected spindles
  49. spindles_list = readtable(fullfile(results_folder_path, sprintf('%s_%s_spindles.csv', sub, sess)));
  51. % for each channel in ascending order
  52. chans = unique(spindles_list.Channel);
  54. q = regexp(chans, '\d+', 'match');
  55. q = cellfun(@str2double, q);
  56. [~, idx] = sort(q);
  57. chans = chans(idx);
  59. int_activity_table = table('Size', [numel(chans) 7], 'VariableTypes', {'string','double','double','double','double','double','double'}, ...
  60. 'VariableNames', {'Chan','Spin_Int_Act_PRE','Spin_Int_Act_STIM', 'N_Spin_PRE', 'N_Spin_STIM', 'Dur_PRE', 'Dur_STIM'});
  61. iChan = 1;
  63. for iChan = 1:numel(chans)
  64. chan = chans{iChan};
  65. for iChanLabel = 1:numel(EEG.chanlocs)
  66. if strcmp(EEG.chanlocs(iChanLabel).labels, chan)
  67. chan_idx = iChanLabel;
  68. end
  69. end
  71. % rectify channel
  72. data = abs(EEG.data(chan_idx, :));
  74. % find and integrate spindles in pre and stim
  75. int_activity_pre = 0; int_activity_stim = 0; spin_pre = 0; spin_stim = 0;
  76. spindles_chan = spindles_list(strcmp(spindles_list.Channel, chan), :);
  78. for iSpin = 1:size(spindles_chan, 1)
  79. if spindles_chan.Start(iSpin)*EEG.srate >= pre_start & spindles_chan.End(iSpin)*EEG.srate <= pre_end
  80. int_activity_pre = int_activity_pre + sum(data(pre_start:pre_end));
  81. spin_pre = spin_pre + 1;
  82. end
  83. if spindles_chan.Start(iSpin)*EEG.srate >= stim_start & spindles_chan.End(iSpin)*EEG.srate <= stim_end
  84. int_activity_stim = int_activity_stim + sum(data(stim_start:stim_end));
  85. spin_stim = spin_stim + 1;
  86. end
  87. end
  88. int_activity_pre = int_activity_pre/pre_dur;
  89. int_activity_stim = int_activity_stim/stim_dur;
  91. % create one Excel file for each participant with integrated
  92. % spindle activity in pre and stim by channel
  93. int_activity_table.Chan(iChan) = chan;
  94. int_activity_table.Spin_Int_Act_PRE(iChan) = int_activity_pre;
  95. int_activity_table.Spin_Int_Act_STIM(iChan) = int_activity_stim;
  96. int_activity_table.N_Spin_PRE(iChan) = spin_pre;
  97. int_activity_table.N_Spin_STIM(iChan) = spin_stim;
  98. int_activity_table.Dur_PRE(iChan) = pre_dur;
  99. int_activity_table.Dur_STIM(iChan) = stim_dur;
  100. end
  102. table_name = sprintf('%s_%s_proto%g_int_spin_act.csv', sub, sess, abs_proto)
  103. writetable(int_activity_table, fullfile(save_path, table_name))
  105. protos_table.mean_int_spin_act_PRE(iProto) = mean(int_activity_table.Spin_Int_Act_PRE);
  106. protos_table.mean_int_spin_act_STIM(iProto) = mean(int_activity_table.Spin_Int_Act_STIM);
  108. protos_table.sum_int_spin_act_PRE(iProto) = sum(int_activity_table.Spin_Int_Act_PRE);
  109. protos_table.sum_int_spin_act_STIM(iProto) = sum(int_activity_table.Spin_Int_Act_STIM);
  110. end
  112. big_table_name = 'Int_spin_act_summary.csv';
  113. writetable(protos_table, fullfile(save_path, big_table_name))

ISA from YASA.m at commit 3ba9617, no license · at the source

Overview

Authors: Simone Bruno1, Beril Mat1, Erin L Schaeffer1,2, Ido Haber1,3, Zhiwei Fan1,4, Sean P Prahl1, Mackenzie R Wilcox1, Emma P Strainis1, Madelynn D Loring1, Tariq Alauddin1, Richard F Smith1, Peter Achermann5,6, Stefan Beerli6, Myles Capstick6, Esra Neufeld6, Niels Kuster6,7, William Marshall8, Larissa Albantakis1,9, Stephanie G Jones1,9, Chiara Cirelli1,9, Melanie Boly1,9,10, Giulio Tononi1,9
ORCID iDs: Simone Bruno, Ido Haber, Larissa Albantakis, Chiara Cirelli, Giulio Tononi
  1. Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
  2. Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, United States
  3. Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States
  4. International Institute for Integrative Sleep Medicine (WPI-IIIS), Tsukuba Institute for Advanced Research (TIAR), University of Tsukuba, Tsukuba, Japan
  5. Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
  6. Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
  7. Department of Information Technology and Electrical Engineering, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
  8. Department of Mathematics and Statistics, Brock University, St. Catharines, ON, Canada
  9. Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison, Madison, WI, United States
  10. Department of Neurology, University of Wisconsin-Madison, Madison, WI, United States
Institutions: University of Wisconsin–Madison (United States); University of Tsukuba (Japan); University of Zurich (Switzerland); Foundation for Research on Information Technologies in Society (Switzerland); ETH Zurich (Switzerland); Brock University (Canada)
Journal: Sleep advances : a journal of the Sleep Research Society, volume 7, issue 3, article zpag069
Dates: received 17 March 2026; accepted 19 June 2026; published online 7 July 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1093/sleepadvances/zpag069 · PMID 42548908 · PMCID PMC13430039 · OpenAlex W7167612884
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: EEG (modality), human (organism)
Methods: Spectral & time-frequency, Statistics, Preprocessing, fMRI & imaging, Connectivity
Keywords: basic science, brain stimulation, electrophysiology, high density EEG, neurophysiology, sleep/wake physiology, sleep spindles
Topic: Sleep and Wakefulness Research (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: JSPS Fund for the Promotion of Joint International Research (22 K21351); United States Department of Defense | Defense Advanced Research Projects Agency (DARPA) (HR00112490326)
Citations: not cited yet (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.

Repository

Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.

sbruno3/TES-TI_spindles

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 3ba96172e232a0d71fb6f4c11c6152eec7655ba7, 10 February 2026
Languages: R (5), MATLAB (3)
Size: 9 files, 8 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (4 files), tidyverse (4 files), EEGLAB (2 files), lme4 (2 files), Statistics and Machine Learning Toolbox (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
9 files
At the source: github.com/sbruno3/TES-TI_spindles

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

Tracing map

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  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 8 scripts, each with its path and the digest of its content;
  • 5 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:

Read it in the paper: doi.org/10.1093/sleepadvances/zpag069.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 22 authors, 7 keywords, 2 funders, 55 references.

Cite

This paper

Bruno, S., Mat, B., Schaeffer, E. L., Haber, I., Fan, Z., Prahl, S. P., Wilcox, M. R., Strainis, E. P., Loring, M. D., Alauddin, T., Smith, R. F., Achermann, P., Beerli, S., Capstick, M., Neufeld, E., Kuster, N., Marshall, W., Albantakis, L., Jones, S. G., . . . Tononi, G. (2026). Thalamic transcranial electrical stimulation with temporal interference enhances sleep spindle activity during a daytime nap. Sleep advances : a journal of the Sleep Research Society, 7(3), zpag069. https://doi.org/10.1093/sleepadvances/zpag069

BibTeX

@article{bruno2026thalamic,
author = {Bruno, Simone and Mat, Beril and Schaeffer, Erin L and Haber, Ido and Fan, Zhiwei and Prahl, Sean P and Wilcox, Mackenzie R and Strainis, Emma P and Loring, Madelynn D and Alauddin, Tariq and Smith, Richard F and Achermann, Peter and Beerli, Stefan and Capstick, Myles and Neufeld, Esra and Kuster, Niels and Marshall, William and Albantakis, Larissa and Jones, Stephanie G and Cirelli, Chiara and Boly, Melanie and Tononi, Giulio},
title = {{Thalamic transcranial electrical stimulation with temporal interference enhances sleep spindle activity during a daytime nap}},
journal = {Sleep advances : a journal of the Sleep Research Society},
year = {2026},
month = jul,
volume = {7},
number = {3},
pages = {zpag069},
publisher = {Oxford University Press},
issn = {2632-5012},
doi = {10.1093/sleepadvances/zpag069},
url = {https://doi.org/10.1093/sleepadvances/zpag069},
pmid = {42548908},
pmcid = {PMC13430039}
}

RIS

TY - JOUR
AU - Bruno, Simone
AU - Mat, Beril
AU - Schaeffer, Erin L
AU - Haber, Ido
AU - Fan, Zhiwei
AU - Prahl, Sean P
AU - Wilcox, Mackenzie R
AU - Strainis, Emma P
AU - Loring, Madelynn D
AU - Alauddin, Tariq
AU - Smith, Richard F
AU - Achermann, Peter
AU - Beerli, Stefan
AU - Capstick, Myles
AU - Neufeld, Esra
AU - Kuster, Niels
AU - Marshall, William
AU - Albantakis, Larissa
AU - Jones, Stephanie G
AU - Cirelli, Chiara
AU - Boly, Melanie
AU - Tononi, Giulio
TI - Thalamic transcranial electrical stimulation with temporal interference enhances sleep spindle activity during a daytime nap
T2 - Sleep advances : a journal of the Sleep Research Society
J2 - Sleep Adv
PY - 2026
DA - 2026/07/07
VL - 7
IS - 3
SP - zpag069
SN - 2632-5012
PB - Oxford University Press
DO - 10.1093/sleepadvances/zpag069
UR - https://doi.org/10.1093/sleepadvances/zpag069
LA - en
ER -

CSL-JSON

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