OSCR

Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception.

Code ↔ Paper

The paper beside its authors' code: matches between them have not been computed for this paper yet.

Paper

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

The paper is loaded when this pane is shown.

The authors' code

MATLAB · 446 lines · 14 KB · no license

  1. %% Exp. 1 Auditory modality - frequency selectivity condition
  2. clear all;
  3. close all;
  4. clc;
  5. rng shuffle
  6. % Force GetSecs and WaitSecs into memory to avoid latency later on:
  7. GetSecs;
  8. WaitSecs(0.1);
  9. %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  10. %% EXPERIMENTAL PARAMETERS - CHECK IT CAREFULLY BEFORE RUNNING!
  11. subj = 'XXXX'; % SUBJ ID
  12. experimental_condition = 1;
  13. num_blocks=5;
  14. numTrials = 112; % number of trials
  15. %% testing parameters
  16. probe_dur = [.100 .125 .160 .200 .250 .320 .400];
  17. ref_dur = [.200];
  18. ind_dur = [.100 .400];
  19. %% combine name and condition for filename
  20. IDsubj=[strcat(subj,'_', num2str(experimental_condition))];
  21. %% control variables
  22. situation=1; %ignore this variable
  23. %% Screen dimension and distance
  24. horiz_dim = 53.3; % cm
  25. distance = 57; % distance from the screen
  26. %% PATH INFO
  27. %% set path for the experiment folder
  28. % PATH TO USE ON ACTUAL SETUP
  29. main_path='XXXXX';
  30. stat_data_path='XXXX\stat';
  31. stimuli_path='XXXX\stimuli';
  32. params_path='XXXXX\params';
  33. res_fn_txt = fullfile(stat_data_path,sprintf('%s-%01g.txt',subj,experimental_condition));
  34. % Check if the path is correct
  35. try
  36. cd (main_path);
  37. catch
  38. disp('Define a position in the actual file system');
  39. return
  40. end
  41. %% Keybord parameters
  42. KbName('UnifyKeyNames');
  43. escapeKey = KbName('return');
  44. %% Switch response buttons according to the side of reference stimulus
  45. cont_key = KbName('C');
  46. abortKey=KbName('q');
  47. %% initialize
  48. commandwindow;
  49. HideCursor;
  50. %% Open window
  51. screen_num = max(Screen('Screens'));
  52. [w,rect]=Screen('OpenWindow',screen_num,128);
  53. Screen('BlendFunction', w, GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA);
  54. Screen('Preference', 'TextRenderer', 1);
  55. Screen('Preference', 'TextAlphaBlending', 1);
  56. Screen('Preference', 'TextAntiAliasing', [], 1);
  57. %% Gamma linearization
  58. lum=linspace(0,1,256)';
  59. gammatable=[lum lum lum].^(1./2.2);
  60. Screen('LoadNormalizedGammaTable', screen_num, gammatable ,0);
  61. %% Screen parameters
  62. [xc,yc]=RectCenter(rect); % screen center coordinates
  63. if ismac
  64. fps = 60; % Just for debug
  65. else
  66. fps = Screen('FrameRate',w); % frames per second
  67. end
  68. ppd = pi * (rect(3)-rect(1)) / atan(horiz_dim/distance/2) / 360; % pixels per degree
  69. %% Central Fixpoint parameters - cross
  70. fromHc1 = xc-8;
  71. fromVc1 = yc;
  72. toHc1 = xc+8;
  73. toVc1 = yc;
  74. fromHc2 = xc;
  75. fromVc2 = yc-8;
  76. toHc2 = xc;
  77. toVc2 = yc+8;
  78. %% Initial flip
  79. Screen('Flip',w);
  80. %% start drawing the fixation point
  81. Screen('DrawLine', w, [255 0 0], fromHc1, fromVc1, toHc1, toVc1 ,1);
  82. Screen('DrawLine', w, [255 0 0], fromHc2, fromVc2, toHc2, toVc2 ,1);
  83. Screen('Flip',w);
  84. pause(.1)
  85. radiusMin=1;
  86. t=0;
  87. matIndex=0;
  88. %% Welcome and instructions screen
  89. font_instr = 'Arial';
  90. size_instr = 28;
  91. instructions{1} = ['Welcome to the experiment!\n\n']; %,...
  92. instructions{2} = ['[Wait for Experimenter Trigger].\n\n']; %,...
  93. % Set font parameters
  94. Screen('TextFont', w, font_instr);
  95. Screen('TextStyle', w, 0);
  96. Screen('TextSize', w, size_instr);
  97. % Welcome and instructions screen
  98. for i = 1 : length(instructions)
  99. DrawFormattedText(w, instructions{i}, 'center', 'center', [0 0 0], 60, [], [], 1.5);
  100. vbl = Screen('Flip', w);
  101. % Check until the release of the key
  102. [secs, keyCode, deltaSecs] = KbJstWait([], Inf);
  103. if keyCode(abortKey)
  104. % Return to standard gamma
  105. lum = linspace(0,1,256)';
  106. gammatable = [lum lum lum];
  107. Screen('LoadNormalizedGammaTable', screen_num, gammatable ,0);
  108. Screen('CloseAll');
  109. ShowCursor;
  110. ListenChar(0);
  111. Priority(0);
  112. return;
  113. end
  114. end
  115. data.header = {'Block','Trial','RefConn','NAN','ProbeNum','Resp','RT'};
  116. %
  117. % % Write to File
  118. dev.foutid = fopen(res_fn_txt, 'w');
  119. fprintf(dev.foutid, '# Subject : %04g\r\n', subj);
  120. fprintf(dev.foutid, '# Session : %01g\r\n', experimental_condition);
  121. fprintf(dev.foutid, '# Date : %s\r\n', uniqueclock);
  122. fprintf(dev.foutid, '# Header :');
  123. for iheader = 1 : length(data.header)
  124. fprintf(dev.foutid, ' %s', data.header{iheader});
  125. end
  126. fprintf(dev.foutid, '\r\n');
  127. numerosity_indexes = [];
  128. %% Initialize PsychPortAudio
  129. InitializePsychSound(1)
  130. d=PsychPortAudio('GetDevices');
  131. pa = PsychPortAudio('Open',2);
  132. for iblock = 1:num_blocks
  133. % Perform one warmup trial, to get the sound hardware fully up and running,
  134. % performing whatever lazy initialization only happens at real first use.
  135. % This "useless" warmup will allow for lower latency for start of playback
  136. % during actual use of the audio driver in the real trials:
  137. mysound=PsychPortAudio('FillBuffer' ,pa, [0 0 0; 0 0 0]); %repmat(soundmatrix,nchannel,1));
  138. PsychPortAudio('Start', pa, 1, 0, 1);
  139. PsychPortAudio('Stop', pa, 1);
  140. cd (main_path)
  141. respbox=[];
  142. inducer_arrays={};
  143. probe_arrays={};
  144. ref_arrays={};
  145. stimuli_conds = ones(4,(length(probe_dur)*8)+3);
  146. %% START TRIAL LOOP
  147. for trial=1:numTrials
  148. %% STACK PROCEDURE TO RANDOMIZE REFERENCE PRESENTATION
  149. stimuli_num = ((1:(length(probe_dur))*8));
  150. ind1=ones(1,length(probe_dur)).*ind_dur(1);
  151. ind2=ones(1,length(probe_dur)).*ind_dur(2);
  152. f1 = ones(1,length(probe_dur)).*1;
  153. f2 = ones(1,length(probe_dur)).*2;
  154. stimuli_conds = [probe_dur probe_dur probe_dur probe_dur probe_dur probe_dur probe_dur probe_dur; ...
  155. ind1 ind2 ind1 ind2 ind1 ind2 ind1 ind2; ...
  156. f1 f1 f2 f2 f1 f1 f2 f2];
  157. if length(numerosity_indexes) > 1 %pop value
  158. numerosity_indexes = numerosity_indexes(2:end);
  159. else
  160. numerosity_indexes = Shuffle(stimuli_num); %push new sequence if the stack had only one value
  161. end
  162. chosen_index = numerosity_indexes(1); %look at top value
  163. chosen_dur = stimuli_conds(1,chosen_index);
  164. chosen_ind = stimuli_conds(2,chosen_index);
  165. chosen_freq = stimuli_conds(3,chosen_index);
  166. %% sound params
  167. nchannel=2; % number of channels (2 if you have two speakers)
  168. Ind_SoundDuration = chosen_ind;
  169. Ref_SoundDuration = ref_dur;
  170. Probe_SoundDuration = chosen_dur;
  171. % PauseDuration = round(0.08*fps)/fps;
  172. sampRate = 44100;
  173. if chosen_freq==1
  174. indfreq = 700;
  175. elseif chosen_freq==2
  176. indfreq = 1100;
  177. end
  178. testfreq = 700;
  179. Ind_SoundLength = sampRate * Ind_SoundDuration; % length of the sound
  180. Ref_SoundLength = sampRate * Ref_SoundDuration; % length of the sound
  181. Probe_SoundLength = sampRate * Probe_SoundDuration; % length of the sound
  182. indSoundwave = 0.5* ( sin (2*pi*indfreq * Ind_SoundDuration* [1:Ind_SoundLength]./ Ind_SoundLength));
  183. refSoundwave = 0.5* ( sin (2*pi*testfreq * Ref_SoundDuration* [1:Ref_SoundLength]./ Ref_SoundLength)) ;
  184. probeSoundwave = 0.5* ( sin (2*pi*testfreq * Probe_SoundDuration* [1:Probe_SoundLength]./ Probe_SoundLength)) ;
  185. % smooth the wave to avoid "clicks" at the start of the sound
  186. lenght_smoothing=round(.002*sampRate); % define the length of the smoothing
  187. modulation_ind=indSoundwave*0+1;
  188. modulation_ind(1:lenght_smoothing+1)=0:1/lenght_smoothing:1;
  189. modulation_ind(end:-1:end-lenght_smoothing)=0:1/lenght_smoothing:1;
  190. indSoundwave=[indSoundwave.*modulation_ind]; % apply smoothing
  191. modulation_ref=refSoundwave*0+1;
  192. modulation_ref(1:lenght_smoothing+1)=0:1/lenght_smoothing:1;
  193. modulation_ref(end:-1:end-lenght_smoothing)=0:1/lenght_smoothing:1;
  194. refSoundwave=[refSoundwave.*modulation_ref]; % apply smoothing
  195. modulation_probe=probeSoundwave*0+1;
  196. modulation_probe(1:lenght_smoothing+1)=0:1/lenght_smoothing:1;
  197. modulation_probe(end:-1:end-lenght_smoothing)=0:1/lenght_smoothing:1;
  198. probeSoundwave=[probeSoundwave.*modulation_probe];
  199. soundmatrix_ind=[indSoundwave; indSoundwave];
  200. soundmatrix_ref=[refSoundwave; refSoundwave];
  201. soundmatrix_probe=[probeSoundwave; probeSoundwave];
  202. %% random isi (to be added to a fixed value)
  203. isi1 = [0.2:0.05:0.25];
  204. isi1 = Shuffle(isi1);
  205. isi1 = isi1(1);
  206. isi2 = [0.35:0.05:0.45];
  207. isi2 = Shuffle(isi2);
  208. isi2 = isi2(1);
  209. iti = [0.4:0.05:0.5];
  210. iti = Shuffle(iti);
  211. iti = iti(1);
  212. %% display fixation point
  213. Screen('DrawLine', w, [0 0 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  214. Screen('DrawLine', w, [0 0 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  215. Screen('Flip',w);
  216. pause(0.3);
  217. %% Stime phases
  218. % Reference - 5 different timings, 25ms intervals
  219. which_ref_time = [0 0.025 0.050 0.075 0.100];
  220. which_ref_time = Shuffle(which_ref_time);
  221. which_ref_time = which_ref_time(1);
  222. %% PRESENT STIMULI
  223. PsychPortAudio('DeleteBuffer'); % delete buffer to be sure
  224. mysound=PsychPortAudio('FillBuffer' ,pa, soundmatrix_ind); %repmat(soundmatrix,nchannel,1));
  225. start_time = GetSecs;
  226. Screen('DrawLine', w, [90 90 90], fromHc1, fromVc1, toHc1, toVc1 ,3);
  227. Screen('DrawLine', w, [90 90 90], fromHc2, fromVc2, toHc2, toVc2 ,3);
  228. Screen('Flip',w);
  229. WaitSecs(0.5);
  230. ind_onset=GetSecs;
  231. PsychPortAudio('Start', pa);
  232. Screen('DrawLine', w, [90 90 90], fromHc1, fromVc1, toHc1, toVc1 ,3);
  233. Screen('DrawLine', w, [90 90 90], fromHc2, fromVc2, toHc2, toVc2 ,3);
  234. Screen('Flip',w);
  235. WaitSecs(chosen_ind);
  236. ind_offset = GetSecs;
  237. Screen('DrawLine', w, [0 0 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  238. Screen('DrawLine', w, [0 0 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  239. Screen('Flip',w);
  240. WaitSecs(0.02);
  241. PsychPortAudio('DeleteBuffer'); % delete buffer to be sure
  242. mysound=PsychPortAudio('FillBuffer' ,pa, soundmatrix_ref); %repmat(soundmatrix,nchannel,1));
  243. WaitSecs(isi1+which_ref_time);
  244. ref_onset=GetSecs;
  245. PsychPortAudio('Start', pa);
  246. WaitSecs(ref_dur);
  247. Screen('DrawLine', w, [0 0 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  248. Screen('DrawLine', w, [0 0 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  249. Screen('Flip',w);
  250. WaitSecs(0.02);
  251. PsychPortAudio('DeleteBuffer'); % delete buffer to be sure
  252. mysound=PsychPortAudio('FillBuffer' ,pa, soundmatrix_probe); %repmat(soundmatrix,nchannel,1));
  253. WaitSecs(isi2);
  254. probe_onset=GetSecs;
  255. PsychPortAudio('Start', pa);
  256. WaitSecs(chosen_dur);
  257. WaitSecs(0.05);
  258. Screen('DrawLine', w, [255 0 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  259. Screen('DrawLine', w, [255 0 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  260. Screen('Flip',w);
  261. %% RESPONSE COLLECTION
  262. resp_time = GetSecs;
  263. [pressedkey, timepress]=respkey('2','3','q','SPACE');
  264. pressedkey=pressedkey-1;
  265. % press Q to exit
  266. if pressedkey ==2
  267. situation=0;
  268. break
  269. end
  270. respbox=[respbox; iblock trial pressedkey chosen_dur chosen_ind NaN chosen_freq which_ind_time which_ref_time ref_dur ... % 1-10
  271. NaN timepress-resp_time NaN ref_onset-start_time NaN ind_onset-start_time ref_onset-ind_offset probe_onset-ind_offset ... %11-20
  272. NaN probe_onset-start_time NaN iti NaN indfreq testfreq NaN timepress-resp_time NaN];
  273. fprintf(dev.foutid,'%g\t%g\t%g\t%.f\t%g\t%.3f\t%.3f\t%g\t%.3f\r\n',...
  274. iblock, trial, chosen_ind, NaN, chosen_dur, NaN, which_ref_time, pressedkey, timepress-resp_time);
  275. fprintf('%g\t%g\t%g\t%.f\t%g\t%.3f\t%.3f\t%g\t%.3f\r\n',...
  276. iblock, trial, chosen_ind, NaN, chosen_dur, NaN, which_ref_time, pressedkey, timepress-resp_time);
  277. %% flash a green fixpoint after respnse
  278. Screen('DrawLine', w, [0 255 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  279. Screen('DrawLine', w, [0 255 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  280. Screen('Flip',w);
  281. pause(.15);
  282. Screen('DrawLine', w, [0 0 0], fromHc1, fromVc1, toHc1, toVc1 ,3);
  283. Screen('DrawLine', w, [0 0 0], fromHc2, fromVc2, toHc2, toVc2 ,3);
  284. Screen('Flip',w);
  285. pause(iti);
  286. end
  287. if situation==0
  288. break
  289. Screen('CloseAll');
  290. end
  291. exp_cond_id=num2str(experimental_condition);
  292. if situation % if you stopped the experiment don't save data
  293. cd data
  294. if size(respbox,1)>5 % save if RESPBOX contains at least 5 trials
  295. save([subj '_' exp_cond_id '_' uniqueclock ], 'respbox');
  296. end
  297. end
  298. if iblock==num_blocks
  299. DrawFormattedText(w, 'This is the end of the condition', 'center', 'center', [0 0 0], 60, [], [], 1.5);
  300. else
  301. DrawFormattedText(w, 'This is the end of one block. Press any key to continue', 'center', 'center', [0 0 0], 60, [], [], 1.5);
  302. end
  303. vbl = Screen('Flip', w);
  304. KbWait;
  305. end
  306. % Return to standard gamma
  307. lum=linspace(0,1,256)';
  308. gammatable=[lum lum lum];
  309. Screen('LoadNormalizedGammaTable', screen_num, gammatable ,0);
  310. Screen('CloseAll');

Exp_1_Aud_diffFreq.m, no license · at the source

Overview

Authors: Irene Togoli1,2, Michele Fornaciai1,2, Domenica Bueti2
  1. Life Sciences Department, University of Trieste,Trieste, Italy
  2. International School for Advanced Studies (SISSA),Trieste, Italy
Journal: BMC biology, volume 24, issue 1, article 95
Dates: received 9 July 2025; accepted 12 January 2026; published online 4 March 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1186/s12915-026-02515-9 · PMID 41776494 · PMCID PMC13067438 · OpenAlex W7133315529
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: EEG (modality), human (organism), cognitive (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Evoked potentials, Single-unit activity, calcium imaging, Machine learning
Keywords: Perceptual history, Serial dependence, EEG, Time perception
MeSH: Auditory Perception*, Visual Perception*, Acoustic Stimulation, Electroencephalography, Female, Humans, Male, Photic Stimulation, Time Perception (* major topic)
Topic: Multisensory perception and integration (Experimental and Cognitive Psychology, Psychology), according to OpenAlex
Funding: Ministero dell'Università e della Ricerca (J93C25000610006, J93C25000630006, R16X32NALR); HORIZON EUROPE Marie Sklodowska-Curie Actions (838823); European Research Council (682117)
Citations: not cited yet (Europe PMC); 61 references in the paper

Abstract

Background: Perceptual history plays an important role in sensory processing and decision making, shaping how we perceive and judge external objects and events. Indeed, past stimuli can bias what we are currently seeing in an attractive fashion, making a current stimulus appear more similar to a preceding one than it actually is. Such attractive “serial dependence” effects concern virtually every aspect of perception, suggesting that they may reflect a fundamental principle of brain processing. However, it is unclear whether the ubiquitous nature of serial dependence is due to an underlying centralised mechanism, or to the existence of separate mechanisms implemented independently in different perceptual pathways. Here we address this question by assessing the behavioural and neural signature of serial dependence in the auditory and visual sensory modality (in separate conditions), in the context of time perception.

Results: Our results first show a double dissociation between the two modalities, whereby auditory serial dependence is selective for the features of the stimuli (i.e. reduced effect when successive stimuli have different features) but not their position, and vice versa in vision. Electroencephalography results further support a difference between the visual and auditory modality, demonstrating that the signature of serial dependence unfolds according to different dynamics in the two modalities.

Conclusions: Overall, our results suggest that the serial dependence effect is mediated by different and at least partially independent modality-specific mechanisms, potentially based on the same computational principle implemented in different sensory pathways.

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

Repository

Its files are read in the Code ↔ Paper reader above.

OSF 7ex9y

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Size: 14 files
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Psychtoolbox (12 files)
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
  • 30 September 2026: the link answers (HTTP 200)
13 files
At the source: osf.io/7ex9y/

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;
  • 13 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • 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

All the data generated during the experiments described in this manuscript and the experimental code is freely available on Open Science Framework at this link: https://osf.io/7ex9y/ (DOI: 10.17605/OSF.IO/7EX9Y).

(DOI: 10.17605/OSF.IO/7EX9Y).

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, issue, pages, dates, 3 authors, 4 keywords, 9 MeSH terms, 3 funders, 60 references.

Cite

This paper

Togoli, I., Fornaciai, M., & Bueti, D. (2026). Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception. BMC biology, 24(1), 95. https://doi.org/10.1186/s12915-026-02515-9

BibTeX

@article{togoli2026different,
author = {Togoli, Irene and Fornaciai, Michele and Bueti, Domenica},
title = {{Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception}},
journal = {BMC biology},
year = {2026},
month = mar,
volume = {24},
number = {1},
pages = {95},
publisher = {BMC},
issn = {1741-7007},
doi = {10.1186/s12915-026-02515-9},
url = {https://doi.org/10.1186/s12915-026-02515-9},
pmid = {41776494},
pmcid = {PMC13067438}
}

RIS

TY - JOUR
AU - Togoli, Irene
AU - Fornaciai, Michele
AU - Bueti, Domenica
TI - Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception
T2 - BMC biology
J2 - BMC Biol
PY - 2026
DA - 2026/03/04
VL - 24
IS - 1
SP - 95
SN - 1741-7007
PB - BMC
DO - 10.1186/s12915-026-02515-9
UR - https://doi.org/10.1186/s12915-026-02515-9
LA - en
ER -

CSL-JSON

{
"id": "10.1186/s12915-026-02515-9",
"type": "article-journal",
"title": "Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception",
"container-title": "BMC biology",
"author": [
{
"family": "Togoli",
"given": "Irene"
},
{
"family": "Fornaciai",
"given": "Michele"
},
{
"family": "Bueti",
"given": "Domenica"
}
],
"container-title-short": "BMC Biol",
"volume": "24",
"issue": "1",
"page": "95",
"DOI": "10.1186/s12915-026-02515-9",
"PMID": "41776494",
"PMCID": "PMC13067438",
"ISSN": "1741-7007",
"publisher": "BMC",
"URL": "https://doi.org/10.1186/s12915-026-02515-9",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
4
]
]
}
}

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

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1371/journal.pbio.3003333
Attractive serial dependence arises during decision-making
Journal: n/a
In common: cognitive, 15 references
[2] doi:10.1038/s41467-026-75705-2 [code]
Redundant prefrontal hemispheres adapt storage strategy to working memory demands.
Journal: Nature communications
In common: cognitive, 9 references
[3] doi:10.1186/s12915-026-02609-4
Saccade-synchronized alpha rhythms predict strength of memory trace of stimulus orientation.
Journal: BMC biology
In common: EEG, cognitive, 3 references
[4] doi:10.1111/psyp.70271 [code]
Disentangling Respiratory Phase-Dependent and Phase-Independent Components of Anticipatory Cardiac Deceleration.
Journal: Psychophysiology
In common: Psychtoolbox, EEG, cognitive, 2 references
[5] doi:10.1038/s41597-026-06616-6 [code]
Sustained Attention Task (gradCPT) Dataset using simultaneous EEG-fMRI and DTI.
Journal: Scientific data
In common: Psychtoolbox, EEG, 2 references
[6] doi:10.7554/elife.108017 [code]
Visual working memory guides attention rhythmically in humans.
Journal: eLife
In common: Psychtoolbox, cognitive, 2 references
[7] doi:10.1038/s41467-026-71600-y [code]
Temporal predictions shape somatosensory perception.
Journal: Nature communications
In common: Psychtoolbox, EEG, cognitive, 1 reference
[8] doi:10.1016/j.isci.2026.117159
Ultraslow brain dynamics as neurophysiological markers of information sampling during learning.
Journal: iScience
In common: EEG, cognitive, 3 references
[9] doi:10.1111/psyp.70370 [code]
Song Familiarity Relies on Evidence Accumulation.
Journal: Psychophysiology
In common: EEG, cognitive, 3 references
[10] doi:10.1523/jneurosci.0154-26.2026 [code]
Faster but less precise: expectation enhances response speed while reducing sensory fidelity.
Journal: The Journal of neuroscience : the official journal of the Society for Neuroscience
In common: EEG, cognitive, 3 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.