OSCR

Visual processing of manipulable objects in the ventral stream is modulated by parietal action systems.

Code ↔ Paper

4 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 4 matches
  1. [1] § Results › Connectome-based lesion-activity mapping of manipulable object and place preferences in ventral occipitotemporal cortex ↔ 004_ExtractVoxelStats/GarceaLab_ExtractVoxelStats.m, lines 365–394 · score 0.63 · left arcuate fasciculus, left IFOF, left ILF, overlaps, tract, volume
  2. [2] § Materials and methods › Functional MRI pre-processing ↔ 001_fMRIPrep2BV/fMRIPrep_PreProcess_CreateVTC.m, lines 235–349 · score 0.62 · spatial smoothing, pre processing, FWHM, kernel, filtering, MRI
  3. [3] § Materials and methods › Functional MRI pre-processing ↔ 001_fMRIPrep2BV/importvtcfromanalyze.m, lines 1–57 · score 0.61 · BrainVoyager, motion parameters, events, linear, resolution
  4. [4] § Materials and methods › Functional MRI pre-processing ↔ 001_fMRIPrep2BV/fMRIPrep_PreProcess_CreateVTC.m, lines 151–234 · score 0.55 · native space, pre processed, filtering, mri

Paper

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The authors' code

MATLAB · 349 lines · 20 KB · no license · 2 matches

  1. function [Params] = fMRIPrep_PreProcess_CreateVTC(Params)
  2. %try
  3. %% Create VTC folder within the Processed Data Folder.
  4. if Params.CreateVTC
  5. Params.BBox = [54 44 55; 236 181 201];
  6. %% If we are working on VTC creation without prior moving of func data, we need user input.
  7. if Params.MoveFunc == 0
  8. % Let's get the func folder in the instance in which the user does
  9. % not indicate they want to move func data.
  10. promptVTCgoal = {'Do you want to create VTCs from files in an already-created functional folder?'};
  11. dlgtitle = 'VTC Creation - User Input Required';
  12. dims = [1 100];
  13. definputexpnames = {'Yes (1) or No (0)'};
  14. vtclocationinfo = inputdlg(promptVTCgoal,dlgtitle,dims,definputexpnames);
  15. % this would indicate the user wants to create VTCs within an
  16. % already-created functional folder. We need to ask them for folder
  17. % names and locations.
  18. if str2double(vtclocationinfo(1)) == 1
  19. % ask the user to provide experiment names.
  20. promptexpnames = {'Provide the number of fMRI experiment names in your derivatives folder.'};
  21. dlgtitle = 'List fMRI Experiment Names';
  22. dims = [1 100];
  23. definputexpnames = {'e.g., 1, 2, 3, 7'};
  24. Params.NrOfExps = inputdlg(promptexpnames,dlgtitle,dims,definputexpnames);
  25. end
  26. % Now that we have established the number of fMRI experiments, ask
  27. % the user for input regarding the names and if/where the folders
  28. % live.
  29. for expi = 1:str2double(Params.NrOfExps{1})
  30. % let's ask the user to provide info about the exp name and if a
  31. % BV processed data folder already exists.
  32. promptexpnames = {['Provide the name of fMRI experiment ' num2str(expi) '.']};
  33. dlgtitle = 'List the fMRI Experiment Name';
  34. dims = [1 100];
  35. definputexpnames = {'e.g., TAFP'};
  36. fmriexppromp = inputdlg(promptexpnames,dlgtitle,dims,definputexpnames);
  37. Params.ExpNames(expi).Name = cell2mat(fmriexppromp(1));
  38. % if the BV processed folder already exists, find the folder.
  39. uiwait(msgbox({['Please select the previously created folder where the ' Params.ExpNames(expi).Name ' processed data live.']}));
  40. Params.ExpNames(expi).FolderPath = uigetdir;
  41. end
  42. end
  43. %% Main loop doing VTC creation.
  44. for expi = 1:str2double(Params.NrOfExps{1})
  45. tmpexpname = []; tmpexpname = Params.ExpNames(expi).Name;
  46. % if the experiment does not have 'Rest' in the name, we proceed.
  48. if contains(lower(tmpexpname),'rest') == 0
  49. % let's get user input regarding VTC smoothing.
  50. % if move func was not selected it means we need to ask for
  51. % user-defined inputs. if not, it already exists in the Params structure.
  52. if Params.MoveFunc == 0
  53. promptVTCsmooth = {['If you are smoothing ' tmpexpname ' VTCs, enter the smoothing kernel size (FWHM)'],'What size functional voxels do you want (in mm)?','Temporal High Pass Filter the VTCs (YES!)?'};
  54. dlgtitle = ['VTC Smoothing - User Input Required for ' tmpexpname ' VTC creation.'];
  55. dims = [1 100];
  56. definputexpnames = {'Enter smoothing kernel value in mm (6 is suggested); put 0 if not smoothing','Enter voxel size in mm (3 is the suggested mm size).','How many cycles (sines per cosine) do you want (2 is suggested)?'};
  57. vtcsmoothinfo = inputdlg(promptVTCsmooth,dlgtitle,dims,definputexpnames);
  58. Params.VTC.SmoothKernel = str2double(vtcsmoothinfo(1));
  59. Params.VTC.VoxelSize = str2double(vtcsmoothinfo(2));
  60. Params.VTC.THPF = str2double(vtcsmoothinfo(3));
  61. end
  63. % Let's create the VTC folder in the processed data folder.
  64. if Params.VTC.SmoothKernel == 0
  65. % in this case, we do not smooth
  66. unsmoothedfoldername = 'ProcessedData_Unsmoothed';
  67. %Params.VTC(expi).FolderName = unsmoothedfoldername;
  68. VTCLoc = fullfile(Params.ExpNames(expi).FolderPath,unsmoothedfoldername);
  69. if isfolder(VTCLoc) == 0
  70. mkdir(VTCLoc);
  71. end
  72. elseif Params.VTC.SmoothKernel > 0
  73. % in this case, we smooth
  74. smoothedfoldername = ['ProcessedData_Smoothed_' num2str(Params.VTC.SmoothKernel) 'FWHM'];
  75. %Params.VTC(expi).FolderName = smoothedfoldername;
  76. VTCLoc = fullfile(Params.ExpNames(expi).FolderPath,smoothedfoldername);
  77. if isfolder(VTCLoc) == 0
  78. mkdir(VTCLoc);
  79. end
  80. end
  82. %% Now let's CD to the funcdicoms folder to make VTCs
  83. tmpfuncdicomsfolder = []; tmpfuncdicomsfolder = fullfile(Params.ExpNames(expi).FolderPath,'/FuncDicoms');
  84. cd(tmpfuncdicomsfolder);
  85. for subi = 1:length(Params.Subs2process)
  86. subID = [];
  87. % let's get the subject ID.
  88. if Params.Subs2process(subi) < 10
  89. subID = ['sub-00' num2str(Params.Subs2process(subi))];
  90. elseif Params.Subs2process(subi) > 9 && Params.Subs2process(subi) < 100
  91. subID = ['sub-0' num2str(Params.Subs2process(subi))];
  92. elseif Params.Subs2process(subi) > 99
  93. subID = ['sub-' num2str(Params.Subs2process(subi))];
  94. end
  95. % now let's set a temporary subject folder variable and cd there.
  96. tmpsubfolder = []; tmpsubfolder = fullfile(tmpfuncdicomsfolder,subID);
  97. cd(tmpsubfolder);
  99. % get session information.
  100. sessiondir = dir('*ses*');
  102. % let's loop through session information to get the anatomical files.
  103. % we'll then use this to copy the data to the process data folder.
  104. for sessioni = 1:size(sessiondir,1)
  105. % create a new variable
  106. sessionID = [];
  107. sessionID = sessiondir(sessioni).name;
  108. %
  109. rundirectory = [];
  110. rundirectory= filterdir('run',sessionID);
  111. %if length(rundirectory) ~= 1
  112. % error('Expected exactly one run file.');
  113. %end
  114. % if the session folder has an 'run' folder we move forward.
  115. if contains(rundirectory(1).name,'run') == 1
  116. for runi = 1:size(rundirectory,1)
  117. tmprunfolder = []; tmprunfolder = fullfile(tmpsubfolder,sessionID,rundirectory(runi).name);
  118. cd(tmprunfolder);
  119. niftidir = dir('*desc-preproc_bold.nii.gz*');
  120. if length(niftidir) ~= 1
  121. error('Expected exactly one nifti file.');
  122. end
  123. tsvdir = dir('*tsv*');
  124. if length(tsvdir) ~= 1
  125. error('Expected exactly one TSV file.');
  126. end
  127. %if runi == 1
  128. Params.fMRParams = [];
  129. V = spm_vol(fullfile(tmprunfolder,niftidir(1).name));
  130. [image,~] = spm_read_vols(V);
  131. Params.fMRIParams.nvol = size(image,4);
  132. % throw out first condition (0 = no).
  133. Params.fMRIParams.rcond = 0;
  134. % TR length in ms.
  135. Params.fMRIParams.prtr = floor(V(1).private.timing.tspace*1000);
  136. clear V image
  137. %end
  139. % let's copy this vtc file to the VTC folder in the
  140. % ProcessedData folder.
  141. tmpVTCrunloc = fullfile(VTCLoc,subID,sessionID,rundirectory(runi).name);
  142. if isfolder(tmpVTCrunloc) == 0
  143. mkdir(tmpVTCrunloc);
  144. end
  145. copyfile(niftidir(1).name,tmpVTCrunloc,'f');
  146. copyfile(tsvdir(1).name,tmpVTCrunloc,'f');
  148. %% VTC creation, THPF-ing, and smoothing (blurring).
  149. % if we're not smoothing, use these parameters.
  150. if Params.VTC.SmoothKernel == 0
  151. %% now that we've copied the files we can work in the BV VTC folder.
  152. cd(tmpVTCrunloc)
  153. % remove VTCs that may already live here.
  154. vtcdir = dir('THPFGLM2');
  155. if isempty(vtcdir) ~= 1
  156. delete('*THPFGLM2*');
  157. %! rm *THPFGLM2*
  158. end
  159. tmpniftifolder = tmpVTCrunloc;
  160. fMRIPrep_PreProcess_ConvertNiftiToVTC(tmpniftifolder,Params.fMRIParams,Params.VTC.VoxelSize);
  161. delete('*.nii*');
  162. %! rm *.nii*
  163. % now let's find the VTC file and THP filter the data.
  164. vtcfile = dir('*.vtc');
  166. % parameters for THPF
  167. %opts = []; opts.temp = 1; opts.temphp = 2; %opts.tempsc = 2;
  168. % parameters from j weber.
  169. opts = struct('temp', true, 'tempsc', Params.VTC.THPF);
  171. % load in native VTC
  172. nativeVTC = BVQXfile(fullfile(tmpVTCrunloc,vtcfile(1).name));
  174. % create a filtered VTC
  175. filteredVTC = nativeVTC.Filter(opts);
  177. % file names for VTC and nifti file.
  178. tmpunsmoothedtimecourse = [subID '_' sessionID '_task-' Params.ExpNames(expi).Name '_run-' num2str(runi) '_Unsmoothed_LTR_THPFGLM' num2str(opts.tempsc) 'c.vtc'];
  180. % don't save out nifti version so we don't
  181. % need filename but keep it here if we need
  182. % it down the road.
  183. %tmpunsmoothedtimecoursenifti = ['Sub-' subID '_task-' taskID '_run-' num2str(runi) '_Unsmoothed_LTR_THPFGLM' num2str(opts.tempsc) 'c.nii'];
  185. % now we'll erase the original VTC and then
  186. % save out the THPF-ed VTC,
  187. delete('*.vtc*'); delete('*rtv*');
  188. %! rm *.vtc* *rtv*
  190. % if this dataset is in native space, change reference space
  191. % index.
  192. if Params.Anatomyspace == 2
  193. filteredVTC.ReferenceSpace = 1;
  194. end
  196. % If the user provides the BBox size, this
  197. % will check to see if the VTC to save out
  198. % is the same size as the user provided
  199. % BBox. If the user does not provide a
  200. % BBox, the script will just save the VTC
  201. % as is.
  202. if isfield(Params,'BBox') == 1
  203. bbox = Params.BBox;
  204. %bbox = tmpvtc.BoundingBox;
  205. origVTCBbox = filteredVTC.BoundingBox;
  206. if sum(sum(bbox ~= origVTCBbox.BBox)) ~= 0
  207. filteredVTCReframe = filteredVTC.Reframe(bbox);
  208. % Save out reframed, blurred, and filtered VTC.
  209. filteredVTCReframe.SaveAs(tmpunsmoothedtimecourse);
  210. clear blurredVTCReframe
  211. end
  212. elseif isfield(Params,'BBox') ~= 1
  213. filteredVTC.SaveAs(tmpsmoothedtimecourse);
  214. end
  216. % if reframing the VTC, do it here.
  217. %tmpvtc = BVQXfile('new:vtc');
  218. %bbox = tmpvtc.BoundingBox;
  220. %filteredVTCReframe = filteredVTC.Reframe(bbox.BBox);
  222. %filteredVTCReframe.SaveAs(tmpunsmoothedtimecourse);
  224. %save also a nifti formatted file (this is for connectivity analyses in Conn).
  225. %NrOfVols = size(filteredVTC.VTCData,1);
  226. %filteredVTC.ExportNifti(tmpunsmoothedtimecoursenifti,1,1:NrOfVols);
  228. % clear VTCs from workspace
  229. clear nativeVTC filteredVTC filteredVTCReframe tmpvtc
  231. % cd to subject folder to go to next run.
  232. cd(tmpsubfolder);
  233. % if we're smoothing, we use these parameters.
  234. elseif Params.VTC.SmoothKernel > 0
  235. %% now that we've copied the files we can work in the BV VTC folder.
  236. cd(tmpVTCrunloc)
  237. % remove VTCs that may already live here.
  238. vtcdir = dir('THPFGLM2');
  239. if isempty(vtcdir) ~= 1
  240. delete('*THPFGLM2*');%! rm *THPFGLM2*
  241. end
  242. tmpniftifolder = tmpVTCrunloc;
  243. %Params.BBox = [54 44 55; 236 181 201];
  244. fMRIPrep_PreProcess_ConvertNiftiToVTC(tmpniftifolder,Params.fMRIParams,Params.VTC.VoxelSize);
  245. delete('*.nii*');%! rm *.nii*
  247. % now let's find the VTC file and THP filter the data.
  248. vtcfile = dir('*.vtc');
  249. if isempty(vtcfile)
  250. error('No VTC found.');
  251. elseif length(vtcfile) > 1
  252. warning('Multiple VTCs found. Using first.');
  253. end
  254. % load in native VTC
  255. %nativeVTC = BVQXfile(fullfile(tmpVTCrunloc,vtcfile(1).name));
  257. % parameters for THPF
  258. %opts = []; opts.temp = 1; opts.temphp = 2; %opts.tempsc = 2;
  259. % parameters from j weber.
  260. opts = struct('temp', true, 'tempsc', Params.VTC.THPF);
  262. % load in native VTC
  263. nativeVTC = BVQXfile(fullfile(tmpVTCrunloc,vtcfile(1).name));
  265. % create a filtered VTC
  266. filteredVTC = nativeVTC.Filter(opts);
  267. tempsc2save = opts.tempsc;
  269. % now we'll erase the original VTC and then save out the THP
  270. % filtered VTC
  271. delete('*.vtc*');
  272. delete('*rtv*');
  273. %! rm *.vtc* *rtv*
  275. % parameters for spatial smoothing
  276. opts = []; opts.spat = 1; opts.spkern = [Params.VTC.SmoothKernel,Params.VTC.SmoothKernel,Params.VTC.SmoothKernel];
  278. % run spatial smoothing with the blurkernel input.
  279. blurredVTC = filteredVTC.Filter(opts);
  281. tmpsmoothedtimecourse = [subID '_' sessionID '_task-' Params.ExpNames(expi).Name '_run-' num2str(runi) '_Smoothed_' num2str(Params.VTC.SmoothKernel) 'MM_FWHM_THPFGLM' num2str(tempsc2save) 'c.vtc'];
  282. % don't save out nifti version so we don't
  283. % need filename but keep it here if we need
  284. % it down the road.
  285. %tmpsmoothedtimecoursenifti = ['Sub-' subID '_task-' taskID '_run-' num2str(runi) '_Smoothed_' num2str(blurkernel) 'MM_FWHM_THPFGLM' num2str(tempsc2save) 'c.nii'];
  288. % if this dataset is in native space,
  289. % change reference space index.
  290. if Params.Anatomyspace == 2
  291. blurredVTC.ReferenceSpace = 1;
  292. end
  294. % If the user provides the BBox size, this
  295. % will check to see if the VTC to save out
  296. % is the same size as the user provided
  297. % BBox. If the user does not provide a
  298. % BBox, the script will just save the VTC
  299. % as is.
  300. if isfield(Params,'BBox') == 1
  301. bbox = Params.BBox;
  302. %bbox = tmpvtc.BoundingBox;
  303. origVTCBbox = blurredVTC.BoundingBox;
  304. if sum(sum(bbox ~= origVTCBbox.BBox)) ~= 0
  305. blurredVTCReframe = blurredVTC.Reframe(bbox);
  306. % Save out reframed, blurred, and filtered VTC.
  307. blurredVTCReframe.SaveAs(tmpsmoothedtimecourse);
  308. clear blurredVTCReframe
  309. end
  310. %if this isn't a field then we don't care.
  311. %in this case, just ssve it.
  312. elseif isfield(Params,'BBox') ~= 1
  313. blurredVTC.SaveAs(tmpsmoothedtimecourse);
  314. end
  315. %elseif exist('Params.BBox') == 0
  316. % tmpvtc = BVQXfile('new:vtc');
  317. % bbox = tmpvtc.BoundingBox;
  318. % origVTCBbox = blurredVTC.BoundingBox;
  319. % if sum(sum(bbox.BBox ~= origVTCBbox.BBox)) ~= 0
  320. % blurredVTCReframe = blurredVTC.Reframe(bbox.BBox);
  321. % % Save out reframed, blurred, and filtered VTC.
  322. % blurredVTCReframe.SaveAs(tmpsmoothedtimecourse);
  323. % clear blurredVTCReframe
  324. % else
  325. % blurredVTC.SaveAs(tmpsmoothedtimecourse);
  326. % end
  327. %blurredVTC.SaveAs(tmpsmoothedtimecourse);
  329. % if we want to save out a nii version.
  330. % NrOfVols = size(filteredVTC.VTCData,1);
  331. % blurredVTC.ExportNifti(tmpsmoothedtimecoursenifti,1,1:NrOfVols);
  333. % clear VTCs from workspace
  334. clear blurredVTC filteredVTC nativeVTC tmpvtc
  336. % cd to subject folder to go to next run.
  337. cd(tmpsubfolder);
  338. end
  339. end
  340. end
  341. end
  342. end
  343. end
  344. end
  345. end
  346. %catch
  347. %uiwait(msgbox({'There was an error in the CreateVTC code.'}));
  348. %cd(Params.HomeDirectory);
  349. %end

fMRIPrep_PreProcess_CreateVTC.m at commit 482fd51, no license · at the source

Overview

Authors: Frank E Garcea1,2,3, Emma Strawderman1,2, William Burns2, Matthew Cotroneo2, Steven P Meyers2,3,4, Tyler Schmidt2, Kevin A Walter2, Webster H Pilcher2, Bradford Z Mahon2,5,6
ORCID iDs: Frank E Garcea, Emma Strawderman, Bradford Z Mahon
  1. Department of Neuroscience, University of Rochester Medical Center, Rochester, NY 14642, USA
  2. Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY 14642, USA
  3. Department of Brain & Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA
  4. Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY 14642, USA
  5. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  6. Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Institutions: University of Rochester Medicine (United States); University of Rochester (United States); Carnegie Mellon University (United States)
Journal: Brain communications, volume 8, issue 4, article fcag293
Dates: received 7 April 2026; accepted 29 June 2026; published online 27 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/braincomms/fcag293 · PMID 42626050 · PMCID PMC13490872 · OpenAlex W7171379904
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism)
Methods: Connectivity, Statistics, Machine learning, Preprocessing, fMRI & imaging
Keywords: voxel-based lesion-activity mapping, manipulable objects, dorsal stream, connectome-based lesion-activity mapping, ventral stream
Topic: Motor Control and Adaptation (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: National Center for Advancing Translational Sciences; NIH; University of Rochester Medical Center; NIH (R21NS076176, R01NS089069); National Science Foundation (BCS1349042, P30 EY001319)
Citations: not cited yet (Europe PMC); 115 references in the paper

Abstract

Functional object use requires the integration of visuomotor representations processed in the dorsal stream with representations of the visual form, surface texture and the material composition of objects, processed in the ventral stream. How do regions across the ventral and dorsal stream interact in support of functional object grasping and use? Here we show that the left inferior parietal lobe exerts a direct effect on neural responses in ventral occipitotemporal cortex (OTC) during visual processing of manipulable objects. We studied a series of consecutively enrolled participants in the pre-operative phase of their neurosurgical care (N = 109) with lesions distributed throughout the left hemisphere. Participants completed a category localizer functional MRI experiment in which they viewed images of manipulable objects, animals, faces and places. Using voxel-based lesion-activity mapping (VLAM), category preferences in neural responses in left ventral OTC were used to predict variance in voxelwise lesion incidence throughout the brain. This approach provides direct causal evidence about which regions outside of OTC, when lesioned, cause changes in neural responses within OTC. We found that lesions to the left anterior intraparietal sulcus and left supramarginal gyrus, two inferior parietal regions known to support object-directed grasping and manipulation, respectively, are associated with reduced neural responses for manipulable objects (compared to faces, places and animals) in the left ventral OTC. Parietal lesions do not modulate neural responses during visual processing of places in the same region of the left ventral OTC, even though places elicit stronger responses in the left ventral OTC than manipulable objects. To explore the structural pathways that may mediate these effects of diaschisis, we repeated the analysis using diffusion MRI-measured white matter fibre integrity as the dependent variable (instead of lesion location). That analysis identified the descending portion of the left arcuate fasciculus as the most likely pathway mediating the parietal-to-temporal lobe diaschisis identified in the VLAM analysis. These integrated VLAM and connectometry analyses demonstrate that inputs from parietal regions supporting skilled object-directed action shape neural responses in the ventral stream when viewing manipulable objects.

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 4 matches between paragraphs and lines of code.

frankgarcea/GarceaColleagues_BrainComms

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 482fd516d8cdac0c5941945ec446190deb17c852, 26 August 2026
Languages: MATLAB (46)
Size: 67 files, 46 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: SPM (11 files), Statistics and Machine Learning Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
47 files
At the source: github.com/frankgarcea/GarceaColleagues_BrainComms.git

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;
  • 46 scripts, each with its path and the digest of its content;
  • 4 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

The whole-brain maps of contrast-weighted t-values, lesions in MNI space, ROIs localized and analysis code are available via GitHub (https://github.com/frankgarcea/GarceaColleagues_BrainComms.git). Individuals interested in raw MRI data should contact the corresponding author to complete a data use agreement, as per the IRB office at the University of Rochester.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 5 keywords, 5 funders, 113 references.

Cite

This paper

Garcea, F. E., Strawderman, E., Burns, W., Cotroneo, M., Meyers, S. P., Schmidt, T., Walter, K. A., Pilcher, W. H., & Mahon, B. Z. (2026). Visual processing of manipulable objects in the ventral stream is modulated by parietal action systems. Brain communications, 8(4), fcag293. https://doi.org/10.1093/braincomms/fcag293

BibTeX

@article{garcea2026visual,
author = {Garcea, Frank E and Strawderman, Emma and Burns, William and Cotroneo, Matthew and Meyers, Steven P and Schmidt, Tyler and Walter, Kevin A and Pilcher, Webster H and Mahon, Bradford Z},
title = {{Visual processing of manipulable objects in the ventral stream is modulated by parietal action systems}},
journal = {Brain communications},
year = {2026},
month = jul,
volume = {8},
number = {4},
pages = {fcag293},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/braincomms/fcag293},
url = {https://doi.org/10.1093/braincomms/fcag293},
pmid = {42626050},
pmcid = {PMC13490872}
}

RIS

TY - JOUR
AU - Garcea, Frank E
AU - Strawderman, Emma
AU - Burns, William
AU - Cotroneo, Matthew
AU - Meyers, Steven P
AU - Schmidt, Tyler
AU - Walter, Kevin A
AU - Pilcher, Webster H
AU - Mahon, Bradford Z
TI - Visual processing of manipulable objects in the ventral stream is modulated by parietal action systems
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/07/27
VL - 8
IS - 4
SP - fcag293
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/braincomms/fcag293
UR - https://doi.org/10.1093/braincomms/fcag293
LA - en
ER -

CSL-JSON

{
"id": "10.1093/braincomms/fcag293",
"type": "article-journal",
"title": "Visual processing of manipulable objects in the ventral stream is modulated by parietal action systems",
"container-title": "Brain communications",
"author": [
{
"family": "Garcea",
"given": "Frank E"
},
{
"family": "Strawderman",
"given": "Emma"
},
{
"family": "Burns",
"given": "William"
},
{
"family": "Cotroneo",
"given": "Matthew"
},
{
"family": "Meyers",
"given": "Steven P"
},
{
"family": "Schmidt",
"given": "Tyler"
},
{
"family": "Walter",
"given": "Kevin A"
},
{
"family": "Pilcher",
"given": "Webster H"
},
{
"family": "Mahon",
"given": "Bradford Z"
}
],
"container-title-short": "Brain Commun",
"volume": "8",
"issue": "4",
"page": "fcag293",
"DOI": "10.1093/braincomms/fcag293",
"PMID": "42626050",
"PMCID": "PMC13490872",
"ISSN": "2632-1297",
"publisher": "Oxford University Press",
"URL": "https://doi.org/10.1093/braincomms/fcag293",
"language": "en",
"issued": {
"date-parts": [
[
2026,
7,
27
]
]
}
}

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