OSCR

Motor cortex excitability during spine shape-judgment in adolescent idiopathic scoliosis: a TMS motor evoked potential study.

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
  1. [1] § Materials and methods › Procedure and experimental design ↔ Code/compute_threshold.m, lines 149–263 · score 0.70 · fixation cross, psychometric function, Palamedes, Psi, slope, duration
  2. [2] § Materials and methods › Procedure and experimental design ↔ Code/compute_threshold.m, lines 149–263 · score 0.52 · fixation cross, cumulative, keyboard, interval, 0.8 s, stimulus

Paper

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The authors' code

MATLAB · 428 lines · 15 KB · no license · 2 matches

  1. % procedure derived from PAL_AMPM_demo from Palamedes toolbox
  2. %
  3. % Using psi adaptive procedure (classic one) to estimate both the threshold
  4. % and the slope of the psychometric function
  5. % I have tested the cumulative normal distribution but the estimations are unstable - empirical
  6. % approximations used.
  7. % to be done:
  8. % - define sensitive ranges for alpha and beta for the weibull distribution
  9. % (I have tested the cumnorm but the estimations are unstable - empirical
  10. % approximations used)
  11. % - include psychtoolbox for presentation of stimulus
  12. %
  14. clearvars
  15. close all
  17. addpath('Palamedes')
  19. %% load stimuli
  21. % Specify the folder containing the images
  22. imageFolderPath = '../Stimoli TMS';
  23. imageFiles = dir(fullfile(imageFolderPath, '*.png')); % Ensure the extension matches your files
  24. numImages = numel(imageFiles);
  25. assert(numImages > 0)
  26. % load angles and images
  27. angles = zeros(numImages, 1);
  28. imageHandles = cell(numImages, 1);
  30. % Loop through each file and extract the number from the file name
  31. for i = 1:length(imageFiles)
  32. % extract angle
  33. parts = strsplit(imageFiles(i).name, '.');
  34. assert(length(parts) == 2)
  35. angles(i, 1) = str2double(parts{1});
  37. % load images
  38. imageHandles{i,1} = imread(fullfile(imageFolderPath, imageFiles(i).name));
  39. end
  41. % setup subject
  42. prompt = {'Enter subject id:','Enter subject age:'};
  43. dlg_title = 'Input';
  44. num_lines = 1;
  45. defaultans = {'Test','99'};
  46. answer = inputdlg(prompt,dlg_title,num_lines,defaultans);
  47. subject.name = answer{1};
  48. subject.age = num2str(answer{2});
  50. % set up trial list
  51. trialData = struct();
  53. % Initialize an array to hold trial data
  54. numTrials = 60;
  55. trials = repmat(trialData, numTrials, 1);
  57. for t = 1:numTrials
  58. trials(t).name = subject.name;
  59. trials(t).age = subject.age;
  60. end
  62. %% setup psychtoolbox
  63. PTBcode_debuging = false;
  65. % Make sure Psychtoolbox is properly installed and set it up
  66. PsychDefaultSetup(2); %Feature level 2: Normalized 0-1 color range and unified key mapping
  67. PsychImaging('PrepareConfiguration'); %Prepare setup of imaging pipeline for onscreen window. This is the first step in the sequence of configuration steps.
  68. Screen('Preference','SkipSyncTests', 1); %Skip sync tests because it often leads to errors on Windows systems (http://psychtoolbox.org/docs/SyncTrouble)
  69. Screen('Preference','VisualDebugLevel', 0); %Disable all visual alerts (this avoids the large on-screen error message for the skipping of sync tests).
  70. InitializePsychSound(1); %Load the PsychPortAudio sound driver for high-precision timing ("1")
  71. clear ans; %Not sure why 'ans' gets created by PTB, but I'll just delete it to clean up the workspace.
  74. %--------------------
  75. % Screen setup
  76. %--------------------
  78. % Seed the random number generator
  79. rng('shuffle');
  81. % see here
  82. % https://raw.githubusercontent.com/Psychtoolbox-3/Psychtoolbox-3/beta/Psychtoolbox/PsychDemos/DriftDemo2.m
  83. AssertOpenGL;
  85. % Set the screen number to the external secondary monitor if there is one
  86. % connected
  87. screenNumber = max(Screen('Screens'));
  89. % Define black, white and grey
  90. white = WhiteIndex(screenNumber);
  91. black = BlackIndex(screenNumber);
  92. gray = round((white+black) / 2);
  93. if gray==white
  94. gray=white/2;
  95. end
  97. %% Open the screen
  98. [window, windowRect] = PsychImaging('OpenWindow', screenNumber, black, [], 32, 2,...
  99. [], [], kPsychNeed32BPCFloat);
  100. %Open the screen, smaller window
  101. %[window, windowRect] = PsychImaging('OpenWindow', screenNumber, black, [0 0 640 480], 32, 2,...
  102. % [], [], kPsychNeed32BPCFloat);
  105. % set some stuff for timing optimization
  106. Priority(MaxPriority(window));
  107. ListenChar(-1); %This new function suppresses keyboard input to the Matlab console but does not prevent the use of KbQueue commands.
  108. % Enable antialiasing blending function (e.g. so we can use line smoothing in the DrawLines command)
  109. Screen('BlendFunction', window, GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA);
  111. [ifi,nrValidSamples,stddev] = Screen('GetFlipInterval',window,100,0.001,5);
  112. disp(['Inter-flip interval (ifi) was measured to be ' num2str(round(ifi*1000*100)/100) ' ms (num_samples = ' num2str(nrValidSamples) ', SD = ' num2str(round(stddev*1000*100)/100) ' ms).']);
  113. disp(['The screen''s frame rate is reported to be ' num2str(Screen('NominalFrameRate', window)) ' Hz.']);
  116. % Flip to clear
  117. Screen('Flip', window);
  119. % Query the frame duration
  120. ifi = Screen('GetFlipInterval', window);
  122. %sca; % just for testing
  124. % Query the maximum priority level
  125. topPriorityLevel = MaxPriority(window);
  127. % Get the size of the on screen window
  128. [screenXpixels, screenYpixels] = Screen('WindowSize', window);
  130. % Get the centre coordinate of the window
  131. [xCenter, yCenter] = RectCenter(windowRect);
  133. % Set the blend function for the screen
  134. Screen('BlendFunction', window, 'GL_SRC_ALPHA', 'GL_ONE_MINUS_SRC_ALPHA');
  136. %% ---------------------
  137. % Text
  138. % ----------------------
  140. % Select specific text font, size, and style:
  141. Screen('TextFont',window, 'Arial');
  142. Screen('TextSize',window, 70);
  146. % text
  147. % mytext = 'Press any key to exit.';
  149. %% ---------------------------------
  150. % Colors
  151. % ---------------------------------
  153. % NB. 0 = black, 1 = white
  154. % set color for background
  155. %grayBack = 0.8; % gray 2
  157. % base line color
  158. %lineColor = 0.6; % gray3 & line_color
  160. % Calculate dark gray index
  161. grayLevel = 0.8; % Adjust this value between 0 and 1 to change darkness
  162. darkGray = round(grayLevel * white + (1-grayLevel) * black);
  164. %-------------------------------------
  165. % Keyboard/mouse information
  166. %-------------------------------------
  168. % Define the keyboard keys.
  170. % Unify key names across platforms for consistency
  171. KbName('UnifyKeyNames');
  173. % We will be using the left and right arrow keys as response keys
  174. % for the task and the escape key as a exit/reset key
  175. escapeKey = KbName('ESCAPE');
  176. not_straight_KeyCode = KbName('L');
  177. straight_KeyCode = KbName('A');
  179. % Hide the mouse cursor
  180. HideCursor;
  181. % move cursor to console
  182. commandwindow;
  185. %-----------------------------
  186. % Fixation cross information
  187. %-----------------------------
  189. % Here we set the size of the arms of our fixation cross
  190. fixCrossDimPix = 40;
  192. % Now we set the coordinates
  193. xCoords = [-fixCrossDimPix fixCrossDimPix 0 0];
  194. yCoords = [0 0 -fixCrossDimPix fixCrossDimPix];
  195. allCoords = [xCoords; yCoords];
  197. % Set the line width for our fixation cross
  198. lineWidthPix = 4;
  200. %---------------------------------
  201. % Timing Information
  202. %---------------------------------
  204. % Interstimulus interval time in seconds and frames
  205. % An ISI is a period of time between stimuli presentations
  206. isiTimeSecs = 1;
  207. isiTimeFrames = round(isiTimeSecs / ifi);
  209. % Numer of frames to wait before re-drawing
  210. waitframes = 1;
  212. % Cleanup
  213. % Screen('CloseAll');
  214. % ShowCursor;
  216. % ---------------------------
  217. % Trial structure
  218. % ---------------------------
  219. blackScreenDuration = 1; % Duration in seconds
  220. fixationCrossDuration = 1; % Duration in seconds
  221. imagePresentationDuration = 2; % Duration in seconds
  224. % set up palamedes
  226. S = warning('QUERY', 'PALAMEDES:AMPM_setupPM:priorTranspose');
  227. warning('off','PALAMEDES:AMPM_setupPM:priorTranspose');
  229. %Set up psi
  231. PF = @PAL_Weibull; %assumed psychometric function
  232. % PF = @PAL_CumulativeNormal;
  234. xMin = 0;
  235. xMax = 37;
  236. spatial_grid = xMin:1:xMax;
  237. totals = zeros(size(spatial_grid));
  239. paramsGen = [10, 5, .5, .02]; %parameter values [alpha, beta, gamma, lambda] (or [threshold, slope, guess, lapse]) used to simulate observer
  241. %Stimulus values the method can select from
  242. stimRange = spatial_grid; %(linspace(PF(trueParams,.1,'inverse'),PF(trueParams,.9999,'inverse'),xMax+1));
  244. %Define parameter ranges to be included in posterior
  247. grain = 201; %grain of posterior, high numbers make method more precise at the cost of RAM and time to compute.
  248. %Always check posterior after method completes [using e.g., :
  249. %surf(priorAlphaRange,priorBetaRange,PM.pdf) to check whether appropriate
  250. %grain and parameter ranges were used.
  251. priorAlphaRange = linspace(0,50,grain);
  252. priorBetaRange = linspace(log10(.0625),log10(4),grain); %Use log10 transformed values of beta (slope) parameter in PF
  253. gamma = 0.5; %fixed value (using vector here would make it a free parameter)
  254. lambda = .01; %ditto
  256. %Initialize PM structure
  257. PM = PAL_AMPM_setupPM('priorAlphaRange',priorAlphaRange,...
  258. 'priorBetaRange',priorBetaRange,...
  259. 'priorGammaRange',gamma,...
  260. 'priorLambdaRange',lambda,...
  261. 'numtrials',numTrials,...
  262. 'PF' , PF,...
  263. 'stimRange',stimRange);
  266. %% loop for the number of instruction pages
  267. % ask type of task
  268. instruction{1} = ['Benvenut*', ...
  269. '\n Durante questo esperimento ' ...
  270. '\n ti verranno mostrate immagini' ...
  271. '\n del corpo visto da dietro.'...
  272. '\n ' ...
  273. '\n Ti verra` chiesto di decidere' ...
  274. '\n se la colonna vertebrale sia normale o no.'];
  276. instruction{2} = ['Prima apparira` una croce' ...
  277. '\n centrale che dovrai fissare,' ...
  278. '\n dopodiche` un` immagine verra` ' ...
  279. '\n mostrata al centro dello schermo.' ...
  280. '\n ' ...
  281. '\n Il tuo compito sara` di rispondere' ...
  282. '\n piu` veloce possibile' ...
  283. '\n premendo lettera A per si' ...
  284. '\n o lettera L per no.'];
  286. for i = 1:length(instruction)
  288. % draw text
  289. DrawFormattedText(window, instruction{i}, 'center','center', white);
  291. % Flip to the screen
  292. Screen('Flip', window);
  294. WaitSecs(1)
  295. KbStrokeWait;
  297. end
  299. DrawFormattedText(window, 'Premere un tasto qualsiasi per proseguire', 'center', ...
  300. 'center', white);
  301. Screen('Flip', window);
  302. KbStrokeWait;
  304. %% START EXPERIMENT
  305. t = 1;
  306. try
  307. % Experimental loop: we loop for the total number of trials
  309. %trial loop
  310. while PM.stop ~= 1
  311. trials(t).trialIndex = t;
  313. % fixation phase
  314. Screen('DrawLines', window, allCoords,...
  315. lineWidthPix, white, [xCenter yCenter], 2);
  316. Screen('Flip', window);
  317. fixation_time = 1 + sign(randn(1,1))*.2*rand(1,1);
  318. trials(t).fixation_time = fixation_time;
  319. WaitSecs(fixation_time);
  321. % show image
  322. current_angle = find(angles == round(PM.xCurrent, 0));
  323. trials(t).image_angle = angles(current_angle);
  324. mytexture_fix = Screen('MakeTexture',window, imageHandles{current_angle,1});
  325. Screen('DrawTexture',window,mytexture_fix, [], [], 0);
  326. vbl = Screen('Flip', window);
  328. % collect response
  329. % Now we wait for a keyboard button signaling the observers response
  330. % Reaction times
  331. response = NaN;
  332. reaction_time = 0;
  333. start_time = GetSecs;
  334. invalid = false;
  336. while true
  337. [keyIsDown, secs, keyCode] = KbCheck;
  339. if keyIsDown
  340. reaction_time = secs - start_time;
  342. % check if response is too quick (<.1s)
  343. if (reaction_time < .1)
  344. invalid = true;
  345. end
  347. if keyCode(not_straight_KeyCode)
  348. response = 1; % not straight
  349. elseif keyCode(straight_KeyCode)
  350. response = 0; % straight
  351. elseif keyCode(escapeKey) % exit
  352. error('Experiment manually interrupted!')
  353. else
  354. invalid = true;
  355. end
  357. % if invalid concatenate trial at the end of trial list
  358. if invalid
  359. trials(end+1) = trials(t);
  360. trials(t).invalid_response = true;
  361. trials(t).reaction_time = reaction_time;
  363. numTrials = numTrials + 1;
  364. break;
  365. end
  367. % save response if trial is valid
  368. %update PM based on response
  369. PM = PAL_AMPM_updatePM(PM,response);
  371. trials(t).threshold = PM.threshold(end);
  372. trials(t).se_threshold = PM.seThreshold(end);
  373. trials(t).slope = 10.^PM.slope(end);
  374. trials(t).se_slope = 10.^PM.seSlope(end);
  377. if response==1; trials(t).response = 'not_straight';
  378. elseif response==0; trials(t).response = 'straight';
  379. else; trials(t).response = 'invalid';
  380. end
  382. break;
  383. end
  384. end
  386. % black screen
  387. % Clear the screen and continue to next trial
  388. Screen('FillRect', window, black);
  389. vbl = Screen('Flip', window);
  391. % wait for tms
  392. wait_time = 2 + sign(randn(1,1))*1*rand(1,1);
  393. trials(t).wait_time = wait_time;
  394. WaitSecs(wait_time);
  396. t = t + 1;
  397. end
  398. catch
  399. Screen('CloseAll');
  400. %display the last error message
  401. psychrethrow(psychlasterror);
  402. ShowCursor;
  403. return
  404. end
  406. ShowCursor;
  407. Screen('CloseAll');
  409. fprintf('th: %.2f\n', PM.threshold(end))
  410. results.threshold = PM.threshold(end);
  411. fprintf('slope: %.2f\n', 10.^PM.slope(end))
  412. results.slope = 10.^PM.slope(end); %PM.slope is in log10 units of beta parameter
  415. % ---------------------------
  416. % Save results
  417. % ---------------------------
  419. clear imageHandles
  420. fld = sprintf('./threshold_results/%s', subject.name);
  421. mkdir(fld);
  422. save(sprintf('%s/%s', fld, 'workspace_final.mat')); %final workspace
  423. writetable(struct2table(trials), sprintf('%s/tabular_results_%s.xlsx', fld, subject.name))
  424. disp('---End---');
  426. %reset warning to original state
  427. warning(S);

compute_threshold.m, no license · at the source

Overview

Authors: Mateja Virovec1, Roberto Barumerli1,2, Paola Cesari1
ORCID iDs: Mateja Virovec
  1. Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Via Casorati 43, Verona, 37131 Italy
  2. Dyson School of Design Engineering, Imperial College London, London, UK
Institutions: University of Verona (Italy); Imperial College London (United Kingdom)
Journal: Experimental brain research, volume 244, issue 8, article 147
Dates: received 7 April 2026; accepted 13 June 2026; published online 30 June 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1007/s00221-026-07343-5 · PMID 42377508 · PMCID PMC13319178 · OpenAlex W7166674883
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: other (modality), human (organism)
Methods: Spectral & time-frequency, Statistics, Preprocessing, Connectivity, Physiology & signal measures
Keywords: Body representation, Adolescent idiopathic scoliosis, Corticospinal excitability, Transcranial magnetic stimulation, Motor evoked potentials
MeSH: Body Image*, Evoked Potentials, Motor*, Motor Cortex*, Scoliosis*, Adolescent, Electromyography, Female, Humans, Muscle, Skeletal, Pyramidal Tracts, Transcranial Magnetic Stimulation (* major topic)
Topic: Scoliosis diagnosis and treatment (Surgery, Medicine), according to OpenAlex
Funding: Università degli Studi di Verona
Citations: not cited yet (Europe PMC); 51 references in the paper

Abstract

This study investigated the neurophysiological mechanisms linking visual body perception to motor output in females with adolescent idiopathic scoliosis (AIS), specifically examining how altered body schema influences corticospinal excitability. A two-stage paradigm was employed in participants with AIS and healthy controls. First, psychophysical thresholds for detecting spinal curvature were estimated. Second, single-pulse transcranial magnetic stimulation (TMS) was applied over the primary motor cortex (100–125 ms post-stimulus) to assess motor system reactivity to body-relevant stimuli. Corticospinal excitability was recorded via motor evoked potentials (MEPs) from intrinsic hand muscles as a proxy for motor readiness during the observation of spinal distortions. Results revealed that AIS patients exhibited significantly lower perceptual thresholds than controls, indicating hypersensitivity to spinal curvature that correlated with subjective self-perception (Trunk Appearance Perception Scale; TAPS). TAPS scores did not correlate significantly with participants’ Cobb angles, indicating that subjective body schema distortion operates independently of mechanical deformity severity. In addition, TMS revealed that AIS patients reached peak corticospinal excitability at their lower perceptual threshold, whereas healthy controls demonstrated peak excitability only when spinal curvatures exceeded their detection thresholds. These findings suggest that AIS involves an increased corticospinal gain in response to body-relevant stimuli. Rather than serving purely as a detection mechanism, the motor system in AIS exhibits a heightened readiness that is tightly coupled with the perception of spinal distortions. Such sensorimotor reorganization suggests that motor excitability is adaptively recalibrated to the patient’s lived physical experience.

Supplementary Information: The online version contains supplementary material available at 10.1007/s00221-026-07343-5.

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.

OSF y5shp

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: MATLAB (2)
Size: 57 files, 2 scripts
Software Heritage: not checked
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Psychtoolbox (2 files)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
2 files
At the source: osf.io/y5shp/

Code availability

All analysis code supporting this research is publicly available: https://osf.io/y5shp/

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

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;
  • 2 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 availability

Raw data are publicly available: https://osf.io/y5shp/

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

Data Availability Statement

Raw data are publicly available: https://osf.io/y5shp/

All study materials supporting this research are publicly available: https://osf.io/y5shp/

All analysis code supporting this research is publicly available: https://osf.io/y5shp/

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

  • Publisher: n/a → Springer Science+Business Media

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 11 MeSH terms, 1 funder, 38 references.

Cite

This paper

Virovec, M., Barumerli, R., & Cesari, P. (2026). Motor cortex excitability during spine shape-judgment in adolescent idiopathic scoliosis: a TMS motor evoked potential study. Experimental brain research, 244(8), 147. https://doi.org/10.1007/s00221-026-07343-5

BibTeX

@article{virovec2026motor,
author = {Virovec, Mateja and Barumerli, Roberto and Cesari, Paola},
title = {{Motor cortex excitability during spine shape-judgment in adolescent idiopathic scoliosis: a TMS motor evoked potential study}},
journal = {Experimental brain research},
year = {2026},
month = jun,
volume = {244},
number = {8},
pages = {147},
publisher = {Springer Science+Business Media},
issn = {0014-4819},
doi = {10.1007/s00221-026-07343-5},
url = {https://doi.org/10.1007/s00221-026-07343-5},
pmid = {42377508},
pmcid = {PMC13319178}
}

RIS

TY - JOUR
AU - Virovec, Mateja
AU - Barumerli, Roberto
AU - Cesari, Paola
TI - Motor cortex excitability during spine shape-judgment in adolescent idiopathic scoliosis: a TMS motor evoked potential study
T2 - Experimental brain research
J2 - Exp Brain Res
PY - 2026
DA - 2026/06/30
VL - 244
IS - 8
SP - 147
SN - 0014-4819
PB - Springer Science+Business Media
DO - 10.1007/s00221-026-07343-5
UR - https://doi.org/10.1007/s00221-026-07343-5
LA - en
ER -

CSL-JSON

{
"id": "10.1007/s00221-026-07343-5",
"type": "article-journal",
"title": "Motor cortex excitability during spine shape-judgment in adolescent idiopathic scoliosis: a TMS motor evoked potential study",
"container-title": "Experimental brain research",
"author": [
{
"family": "Virovec",
"given": "Mateja"
},
{
"family": "Barumerli",
"given": "Roberto"
},
{
"family": "Cesari",
"given": "Paola"
}
],
"container-title-short": "Exp Brain Res",
"volume": "244",
"issue": "8",
"page": "147",
"DOI": "10.1007/s00221-026-07343-5",
"PMID": "42377508",
"PMCID": "PMC13319178",
"ISSN": "0014-4819",
"publisher": "Springer Science+Business Media",
"URL": "https://doi.org/10.1007/s00221-026-07343-5",
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
30
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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