OSCR

Brain Bases for Navigating Acoustic Features.

Code ↔ Paper

3 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 3 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted
  1. [1] § Materials and Methods › MRI Data Acquisition ↔ +gadgetron/+types/+xml/serialize.m, lines 131–189 · score 0.73 · flip angle, acceleration factor, TR, TE, double, sequence
  2. [2] § Materials and Methods › MRI Data Acquisition ↔ +gadgetron/+types/+xml/deserialize.m, lines 185–206 · score 0.66 · flip angle, TR, bandwidth, sequence, weighted, echo
  3. [3] § Materials and Methods › Multivariate fMRI Analyses ↔ +gadgetron/+FIL/+utils/morse_estimate_sensitivities.m, the whole file · a weak match · score 0.53 · diagonal, variances, smoothed, weights, matrices, voxel

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 · 314 lines · 13 KB · BSD-3-Clause · 1 match

  1. function [xml_doc] = serialize( header)
  2. %SERIALIZE Summary of this function goes here
  3. % Detailed explanation goes here
  4. docNode = com.mathworks.xml.XMLUtils.createDocument('ismrmrdHeader');
  5. docRootNode = docNode.getDocumentElement;
  6. docRootNode.setAttribute('xmlns','http://www.ismrm.org/ISMRMRD');
  7. docRootNode.setAttribute('xmlns:xsi','http://www.w3.org/2001/XMLSchema-instance');
  8. docRootNode.setAttribute('xmlns:xs','http://www.w3.org/2001/XMLSchema');
  10. docRootNode.setAttribute('xsi:schemaLocation','http://www.ismrm.org/ISMRMRD ismrmrd.xsd');
  12. append_optional(docNode,docRootNode,header,'version',@int2str)
  14. if isfield(header,'subjectInformation')
  15. subjectInformation = header.subjectInformation;
  16. subjectInformationNode = docNode.createElement('subjectInformation');
  17. append_optional(docNode,subjectInformationNode,subjectInformation,'patientName');
  18. append_optional(docNode,subjectInformationNode,subjectInformation,'patientWeight_kg',@num2str);
  19. append_optional(docNode,subjectInformationNode,subjectInformation,'patientID');
  20. append_optional(docNode,subjectInformationNode,subjectInformation,'patientBirthdate');
  21. append_optional(docNode,subjectInformationNode,subjectInformation,'patientGender');
  22. docRootNode.appendChild(subjectInformationNode);
  23. end
  25. if isfield(header,'studyInformation')
  26. studyInformation = header.studyInformation;
  27. studyInformationNode = docNode.createElement('studyInformation');
  28. append_optional(docNode,studyInformationNode,studyInformation,'studyDate');
  29. append_optional(docNode,studyInformationNode,studyInformation,'studyTime');
  30. append_optional(docNode,studyInformationNode,studyInformation,'studyID');
  31. append_optional(docNode,studyInformationNode,studyInformation,'accessionNumber',@int2str);
  32. append_optional(docNode,studyInformationNode,studyInformation,'referringPhysicianName');
  33. append_optional(docNode,studyInformationNode,studyInformation,'studyDescription');
  34. append_optional(docNode,studyInformationNode,studyInformation,'studyInstanceUID');
  35. docRootNode.appendChild(studyInformationNode);
  36. end
  38. if isfield(header,'measurementInformation')
  39. measurementInformation = header.measurementInformation;
  40. measurementInformationNode = docNode.createElement('measurementInformation');
  41. append_optional(docNode,measurementInformationNode,measurementInformation,'measurementID');
  42. append_optional(docNode,measurementInformationNode,measurementInformation,'seriesDate');
  43. append_optional(docNode,measurementInformationNode,measurementInformation,'seriesTime');
  45. append_node(docNode,measurementInformationNode,measurementInformation,'patientPosition');
  47. append_optional(docNode,measurementInformationNode,measurementInformation,'initialSeriesNumber',@int2str);
  48. append_optional(docNode,measurementInformationNode,measurementInformation,'protocolName');
  49. append_optional(docNode,measurementInformationNode,measurementInformation,'seriesDescription');
  51. if isfield(measurementInformation, 'measurementDependency')
  52. measurementDependency = measurementInformation.measurementDependency;
  53. for dep = measurementDependency(:)
  54. node = docNode.createElement('measurementDependency');
  55. append_node(docNode,node,dep,'dependencyType');
  56. append_node(docNode,node,dep,'measurementID');
  57. measurementInformationNode.appendChild(node)
  58. end
  59. end
  61. append_optional(docNode,measurementInformationNode,measurementInformation,'seriesInstanceUIDRoot');
  62. append_optional(docNode,measurementInformationNode,measurementInformation,'frameOfReferenceUID');
  64. if isfield(measurementInformation, 'referencedImageSequence')
  65. referencedImageSequence = measurementInformation.referencedImageSequence;
  66. referencedImageSequenceNode = docNode.createElement('referencedImageSequence');
  67. for ref = referencedImageSequence(:)
  68. append_node(docNode,referencedImageSequenceNode,ref,'referencedSOPInstanceUID');
  69. end
  70. end
  72. docRootNode.appendChild(measurementInformationNode);
  73. end
  75. if isfield(header,'acquisitionSystemInformation')
  76. acquisitionSystemInformation = header.acquisitionSystemInformation;
  77. acquisitionSystemInformationNode = docNode.createElement('acquisitionSystemInformation');
  78. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'systemVendor');
  79. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'systemModel');
  80. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'systemFieldStrength_T',@num2str);
  81. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'relativeReceiverNoiseBandwidth',@num2str);
  82. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'receiverChannels',@int2str);
  84. if isfield(acquisitionSystemInformation, 'coilLabel')
  85. coilLabel = acquisitionSystemInformation.coilLabel;
  86. for coil = 1:length(coilLabel)
  87. coilLabelNode = docNode.createElement('coilLabel');
  88. append_node(docNode,coilLabelNode,coilLabel(coil),'coilNumber',@num2str);
  89. append_node(docNode,coilLabelNode,coilLabel(coil),'coilName');
  90. acquisitionSystemInformationNode.appendChild(coilLabelNode);
  91. end
  92. end
  94. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'institutionName');
  95. append_optional(docNode,acquisitionSystemInformationNode,acquisitionSystemInformation,'stationName',@num2str);
  96. docRootNode.appendChild(acquisitionSystemInformationNode);
  97. end
  99. experimentalConditions = header.experimentalConditions;
  100. experimentalConditionsNode = docNode.createElement('experimentalConditions');
  101. append_node(docNode,experimentalConditionsNode,experimentalConditions,'H1resonanceFrequency_Hz',@int2str);
  102. docRootNode.appendChild(experimentalConditionsNode);
  104. if ~isfield(header,'encoding')
  105. error('Illegal header: missing encoding section');
  106. end
  108. for enc = header.encoding(:)
  109. node = docNode.createElement('encoding');
  111. append_encoding_space(docNode,node,'encodedSpace',enc.encodedSpace);
  112. append_encoding_space(docNode,node,'reconSpace',enc.reconSpace);
  114. n2 = docNode.createElement('encodingLimits');
  116. append_encoding_limits(docNode,n2,'kspace_encoding_step_0',enc.encodingLimits);
  117. append_encoding_limits(docNode,n2,'kspace_encoding_step_1',enc.encodingLimits);
  118. append_encoding_limits(docNode,n2,'kspace_encoding_step_2',enc.encodingLimits);
  119. append_encoding_limits(docNode,n2,'average',enc.encodingLimits);
  120. append_encoding_limits(docNode,n2,'slice',enc.encodingLimits);
  121. append_encoding_limits(docNode,n2,'contrast',enc.encodingLimits);
  122. append_encoding_limits(docNode,n2,'phase',enc.encodingLimits);
  123. append_encoding_limits(docNode,n2,'repetition',enc.encodingLimits);
  124. append_encoding_limits(docNode,n2,'set',enc.encodingLimits);
  125. append_encoding_limits(docNode,n2,'segment',enc.encodingLimits);
  126. node.appendChild(n2);
  128. append_node(docNode,node,enc,'trajectory');
  129. node.appendChild(n2);
  131. % sometimes the encoding has the fields, but they are empty
  132. if isfield(enc,'trajectoryDescription')
  133. if ~isempty(fieldnames(enc.trajectoryDescription))
  134. n2 = docNode.createElement('trajectoryDescription');
  135. append_node(docNode,n2,enc.trajectoryDescription,'identifier');
  136. append_user_parameter(docNode,n2,enc.trajectoryDescription,'userParameterLong',@int2str);
  137. append_user_parameter(docNode,n2,enc.trajectoryDescription,'userParameterDouble',@num2str);
  138. append_optional(docNode,n2,enc.trajectoryDescription,'comment');
  139. node.appendChild(n2);
  140. end
  141. end
  143. if isfield(enc,'parallelImaging')
  144. if ~isempty(fieldnames(enc.parallelImaging))
  145. n2 = docNode.createElement('parallelImaging');
  147. n3 = docNode.createElement('accelerationFactor');
  148. parallelImaging = enc.parallelImaging;
  149. append_node(docNode,n3,parallelImaging.accelerationFactor,'kspace_encoding_step_1',@int2str);
  150. append_node(docNode,n3,parallelImaging.accelerationFactor,'kspace_encoding_step_2',@int2str);
  151. n2.appendChild(n3);
  153. append_optional(docNode,n2,parallelImaging,'calibrationMode');
  154. append_optional(docNode,n2,parallelImaging,'interleavingDimension',@int2str);
  156. node.appendChild(n2);
  157. end
  158. end
  160. if isfield(enc,'echoTrainLength')
  161. if ~isempty(enc.echoTrainLength)
  162. append_optional(docNode,node,enc,'echoTrainLength',@int2str);
  163. end
  164. end
  166. docRootNode.appendChild(node);
  168. end
  170. if isfield(header,'sequenceParameters')
  171. n1 = docNode.createElement('sequenceParameters');
  172. sequenceParameters = header.sequenceParameters;
  174. append_optional(docNode,n1,sequenceParameters,'TR',@num2str);
  175. append_optional(docNode,n1,sequenceParameters,'TE',@num2str);
  176. append_optional(docNode,n1,sequenceParameters,'TI',@num2str);
  177. append_optional(docNode,n1,sequenceParameters,'flipAngle_deg',@num2str);
  178. append_optional(docNode,n1,sequenceParameters,'sequence_type');
  179. append_optional(docNode,n1,sequenceParameters,'echo_spacing',@num2str);
  180. docRootNode.appendChild(n1);
  181. end
  183. if isfield(header,'userParameters')
  184. n1 = docNode.createElement('userParameters');
  185. userParameters = header.userParameters;
  187. if isfield(userParameters,'userParameterLong')
  188. append_user_parameter(docNode,n1,userParameters,'userParameterLong',@int2str);
  189. end
  191. if isfield(userParameters,'userParameterDouble')
  192. append_user_parameter(docNode,n1,userParameters,'userParameterDouble',@num2str);
  193. end
  194. if isfield(userParameters,'userParameterString')
  195. append_user_parameter(docNode,n1,userParameters,'userParameterString');
  196. end
  197. if isfield(userParameters,'userParameterBase64')
  198. append_user_parameter(docNode,n1,userParameters,'userParameterBase64');
  199. end
  201. docRootNode.appendChild(n1);
  202. end
  204. if isfield(header,'waveformInformation')
  205. n1 = docNode.createElement('waveformInformation')
  206. waveformInformation = header.waveformInformation;
  208. append_node(docNode,n1,waveformInformation,'waveformName');
  209. append_node(docNode,n1,waveformInformation,'waveformType');
  211. if isfield(waveformInformation,'userParameters')
  212. n2 = n1.createElement('userParameters')
  213. userParameters = waveformInformation.userParameters;
  215. if isfield(userParameters,'userParameterLong')
  216. append_user_parameter(docNode,n2,userParameters,'userParameterLong',@int2str);
  217. end
  219. if isfield(userParameters,'userParameterDouble')
  220. append_user_parameter(docNode,n2,userParameters,'userParameterDouble',@num2str);
  221. end
  222. if isfield(userParameters,'userParameterString')
  223. append_user_parameter(docNode,n2,userParameters,'userParameterString');
  224. end
  225. if isfield(userParameters,'userParameterBase64')
  226. append_user_parameter(docNode,n2,userParameters,'userParameterBase64');
  227. end
  228. end
  229. end
  233. xml_doc = xmlwrite(docNode);
  238. end
  240. function append_user_parameter(docNode,subNode,values,name,tostr)
  242. for v = 1:length(values.(name))
  243. n2 = docNode.createElement(name);
  245. append_node(docNode,n2,values.(name)(v),'name');
  247. if nargin > 4
  248. append_node(docNode,n2,values.(name)(v),'value',tostr);
  249. else
  250. append_node(docNode,n2,values.(name)(v),'value');
  251. end
  253. subNode.appendChild(n2);
  254. end
  255. end
  258. function append_encoding_limits(docNode,subNode,name,limit)
  259. if isfield(limit,name)
  260. n2 = docNode.createElement(name);
  261. append_node(docNode,n2,limit.(name),'minimum',@int2str);
  262. append_node(docNode,n2,limit.(name),'maximum',@int2str);
  263. append_node(docNode,n2,limit.(name),'center',@int2str);
  264. subNode.appendChild(n2);
  265. end
  266. end
  268. function append_encoding_space(docNode,subnode,name,encodedSpace)
  269. n2 = docNode.createElement(name);
  271. n3 = docNode.createElement('matrixSize');
  272. append_node(docNode,n3,encodedSpace.matrixSize,'x',@int2str);
  273. append_node(docNode,n3,encodedSpace.matrixSize,'y',@int2str);
  274. append_node(docNode,n3,encodedSpace.matrixSize,'z',@int2str);
  275. n2.appendChild(n3);
  277. n3 = docNode.createElement('fieldOfView_mm');
  278. append_node(docNode,n3,encodedSpace.fieldOfView_mm,'x',@num2str);
  279. append_node(docNode,n3,encodedSpace.fieldOfView_mm,'y',@num2str);
  280. append_node(docNode,n3,encodedSpace.fieldOfView_mm,'z',@num2str);
  281. n2.appendChild(n3);
  283. subnode.appendChild(n2);
  284. end
  287. function append_optional(docNode,subnode,subheader,name,tostr)
  288. if isfield(subheader,name)
  289. if nargin > 4
  290. append_node(docNode,subnode,subheader,name,tostr);
  291. else
  292. append_node(docNode,subnode,subheader,name);
  293. end
  294. end
  295. end
  297. function append_node(docNode,subnode,subheader,name,tostr)
  299. if ischar(subheader.(name))
  300. n1 = docNode.createElement(name);
  301. n1.appendChild...
  302. (docNode.createTextNode(subheader.(name)));
  303. subnode.appendChild(n1);
  304. else
  306. val = subheader.(name)(:);
  307. for thisval = 1:length(val)
  308. n1 = docNode.createElement(name);
  309. n1.appendChild...
  310. (docNode.createTextNode(tostr(val(thisval))));
  311. subnode.appendChild(n1);
  312. end
  313. end
  314. end

serialize.m at commit 09c53ca, under BSD-3-Clause · at the source

Overview

Authors: Alexander J. Billig1, William Sedley2, Phillip E. Gander3,4, Sukhbinder Kumar4, Meher Lad2, Maria Chait1, Yousef Mohammadi5, Joel I. Berger4, Timothy D. Griffiths4,5,6
ORCID iDs: William Sedley, Maria Chait, Yousef Mohammadi, Joel I. Berger
  1. UCL Ear Institute University College London London UK
  2. Translational and Clinical Research Institute, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne UK
  3. Department of Radiology The University of Iowa Iowa City Iowa USA
  4. Department of Neurosurgery The University of Iowa Iowa City Iowa USA
  5. Department of Imaging Neuroscience University College London London UK
  6. Biosciences Institute, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne UK
Institutions: University College London (United Kingdom); Newcastle University (United Kingdom); University of Iowa (United States); University of Iowa Health Care (United States)
Journal: Human brain mapping, volume 47, issue 4, article e70492
Dates: received 7 May 2025; accepted 26 February 2026; published online 8 March 2026; in print March 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1002/hbm.70492 · PMID 41797407 · PMCID PMC12968464 · OpenAlex W7134234545
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), cognitive (subfield)
Methods: Statistics, Machine learning, Connectivity, fMRI & imaging, Physiology & signal measures
Keywords: auditory cognition, auditory memory, hippocampus, navigation, sound, working memory
MeSH: Auditory Perception*, Brain Mapping*, Hippocampus*, Memory, Short-Term*, Spatial Navigation*, Acoustic Stimulation, Adult, Auditory Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Young Adult (* major topic)
Topic: Memory and Neural Mechanisms (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Wellcome Trust (WT106964MA, 203147/Z/16/Z); UK Medical Research Council (MR/T032553/1)
Citations: cited by 1 paper (Europe PMC); 60 references in the paper

Abstract

Whether physical navigation shares neural substrates with mental travel in other behaviourally relevant domains is debated. With respect to sound, pure‐tone working memory in humans elicits hippocampal as well as auditory cortical and inferior frontal activity, and rodent work suggests that hippocampal cells that usually track an animal's physical location can also map to tone frequency when task‐relevant. We generated a sound dimension based on the density of random‐frequency tones in a stack, resulting in a percept ranging from low‐ (‘beepy’) to high‐density (‘noisy’). We established that unlike tone frequency, which listeners automatically associate with vertical position, this density dimension elicited no consistent spatial mapping. During functional magnetic resonance imaging, human participants held in mind the density of a series of tone stacks and, after a short maintenance period, adjusted further stacks to match the target (‘navigation’). Density of the currently heard sound was represented most strongly in bilateral non‐primary auditory cortex, specifically bilateral planum polare, whereas density of the maintained target was represented in right anterior hippocampus and left inferior temporal gyrus. Encoding and maintenance activity in bilateral hippocampus, inferior frontal gyrus, planum polare and posterior cingulate was positively associated with subsequent navigation success. Bilateral inferior frontal gyrus and hippocampus were among regions with elevated activity during adjustment, compared to a parity‐judgement condition with closely matched acoustics and motor demands. Bilateral orbitofrontal cortex was more active when navigation was toward a target density than when participants adjusted density in a control condition with no particular target. We find that self‐initiated travel along a non‐spatial auditory dimension engages a brain system overlapping with that supporting physical navigation.

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 3 matches between paragraphs and lines of code.

fil-physics/gadgetron-matlab

License: BSD-3-Clause
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 09c53cade9012d948350b75e7013bf259b782244, 9 September 2026
Languages: MATLAB (105), Shell (14), Java (1)
Size: 141 files, 120 scripts
Software Heritage: archived
Found in: the text, “MRI Data Acquisition”
Holds: README, license file, environment (FIL-recon/docker-containers/image-files/FIL-EXTRAS.Dockerfile), tests
Not found: CITATION.cff, continuous integration, documentation
Tools: Image Processing Toolbox (1 file), Parallel Computing Toolbox (1 file), Tools for NIfTI and ANALYZE image (MATLAB) (1 file), SPM (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
122 files
At the source: github.com/fil-physics/gadgetron-matlab/tree/master/FIL-recon

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;
  • 120 scripts, each with its path and the digest of its content;
  • 3 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 Statement

The data that support the findings of this study are openly available in BIDS format at OpenNeuro at https://openneuro.org/datasets/ds006211.

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, 9 authors, 6 keywords, 13 MeSH terms, 2 funders, 60 references.

Cite

This paper

Billig, A. J., Sedley, W., Gander, P. E., Kumar, S., Lad, M., Chait, M., Mohammadi, Y., Berger, J. I., & Griffiths, T. D. (2026). Brain Bases for Navigating Acoustic Features. Human brain mapping, 47(4), e70492. https://doi.org/10.1002/hbm.70492

BibTeX

@article{billig2026brain,
author = {Billig, Alexander J. and Sedley, William and Gander, Phillip E. and Kumar, Sukhbinder and Lad, Meher and Chait, Maria and Mohammadi, Yousef and Berger, Joel I. and Griffiths, Timothy D.},
title = {{Brain Bases for Navigating Acoustic Features}},
journal = {Human brain mapping},
year = {2026},
month = mar,
volume = {47},
number = {4},
pages = {e70492},
publisher = {Wiley},
issn = {1065-9471},
doi = {10.1002/hbm.70492},
url = {https://doi.org/10.1002/hbm.70492},
pmid = {41797407},
pmcid = {PMC12968464}
}

RIS

TY - JOUR
AU - Billig, Alexander J.
AU - Sedley, William
AU - Gander, Phillip E.
AU - Kumar, Sukhbinder
AU - Lad, Meher
AU - Chait, Maria
AU - Mohammadi, Yousef
AU - Berger, Joel I.
AU - Griffiths, Timothy D.
TI - Brain Bases for Navigating Acoustic Features
T2 - Human brain mapping
J2 - Hum Brain Mapp
PY - 2026
DA - 2026/03/01
VL - 47
IS - 4
SP - e70492
SN - 1065-9471
PB - Wiley
DO - 10.1002/hbm.70492
UR - https://doi.org/10.1002/hbm.70492
LA - en
ER -

CSL-JSON

{
"id": "10.1002/hbm.70492",
"type": "article-journal",
"title": "Brain Bases for Navigating Acoustic Features",
"container-title": "Human brain mapping",
"author": [
{
"family": "Billig",
"given": "Alexander J."
},
{
"family": "Sedley",
"given": "William"
},
{
"family": "Gander",
"given": "Phillip E."
},
{
"family": "Kumar",
"given": "Sukhbinder"
},
{
"family": "Lad",
"given": "Meher"
},
{
"family": "Chait",
"given": "Maria"
},
{
"family": "Mohammadi",
"given": "Yousef"
},
{
"family": "Berger",
"given": "Joel I."
},
{
"family": "Griffiths",
"given": "Timothy D."
}
],
"container-title-short": "Hum Brain Mapp",
"volume": "47",
"issue": "4",
"page": "e70492",
"DOI": "10.1002/hbm.70492",
"PMID": "41797407",
"PMCID": "PMC12968464",
"ISSN": "1065-9471",
"publisher": "Wiley",
"URL": "https://doi.org/10.1002/hbm.70492",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
1
]
]
}
}

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

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Journal: Nature communications
In common: Image Processing Toolbox, 4 references
[10] doi:10.1016/j.isci.2026.116903 [code]
Neurobiological and behavioral relevance of intrinsic functional connectome constraints on task-evoked neural activation.
Journal: iScience
In common: Tools for NIfTI and ANALYZE image (MATLAB), SPM, Image Processing Toolbox, cognitive, 1 reference

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