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Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex.

Code ↔ Paper

13 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 13 matches · 2 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Precision functional network mapping ↔ screenshot_scripts/ss_tasks.R, lines 1–65 · score 0.73 · default parietal, cingulo opercular, dorsal attention, Lynch, verified, lateral
  2. [2] § RESULTS › Individual-specific LPFC networks reveal conserved motifs not present in group-averaged data ↔ screenshot_scripts/ss_motif.R, lines 91–154 · score 0.65 · network motif, rostral CO, dorsal attention, TPJ, bordered, seed
  3. [3] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Precision functional network mapping ↔ screenshot_scripts/ss_motif.R, lines 91–154 · score 0.61 · cingulo opercular, dorsal attention, Lynch, verified, V1, lateral
  4. [4] § STAR★METHODS › METHOD DETAILS › MRI acquisition ↔ external_packages/matlab/non_default_packages/palm/palm-alpha109/fileio/@nifti/private/nifti1.h, lines 1070–1158 · score 0.61 · phase encoding direction, scans, Slices, fMRI
  5. [5] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › fMRI processing ↔ stable_projects/brain_parcellation/Schaefer2018_LocalGlobal/Parcellations/Code/lib/CBIG_gwMRF_write_cifti_from_annot.m, the whole file · a weak match · score 0.60 · fslr32k, FreeSurfer, global, CIFTI, Workbench, surface
  6. [6] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Network task activity comparison ↔ screenshot_scripts/ss_tasks.R, lines 68–111 · score 0.57 · cingulo opercular, dorsal attention, LPFC network, frontoparietal, domains, Language
  7. [7] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Group-averaged network parcellation ↔ screenshot_scripts/ss_tasks.R, lines 1–65 · score 0.55 · cingulo opercular, dorsal attention, LPFC networks, frontoparietal, connectivity
  8. [8] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Border activation analysis ↔ screenshot_scripts/ss_tasks.R, lines 68–111 · score 0.54 · cingulo opercular, dorsal attention, frontoparietal, LANG, borders, activations
  9. [9] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Density rotation analysis ↔ screenshot_scripts/ss_density.R, lines 1–46 · score 0.54 · Association network density, Connectome Workbench, rotation, hemisphere, cifti
  10. [10] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › fMRI processing ↔ stable_projects/disorder_subtypes/Zhang2016_ADFactors/step3_analyses_internalUse/validateFactorsWithFSStats/CBIG_assignFactorsToStructures.m, the whole file · a weak match · score 0.54 · FreeSurfer, CSF, subcortical, fs, filtered, volume
  11. [11] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Precision functional network mapping ↔ stable_projects/brain_parcellation/Yan2023_homotopic/code/utilities/CBIG_hMRF_generate_fs6_lhrh_nborhood.m, lines 1–92 · score 0.54 · Euclidean distance, geodesic distance, matrix, vertices
  12. [12] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Border activation analysis ↔ border_activations/border_activations.m, lines 114–171 · score 0.53 · target network, borders, DN, DAN, LANG, FP
  13. [13] § RESULTS › Individual-specific LPFC networks reveal conserved motifs not present in group-averaged data ↔ screenshot_scripts/ss_motif.R, lines 41–89 · score 0.52 · rostral CO, CO region, motif, rotational, seed, LPFC

Paper

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

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The authors' code

R · 111 lines · 6.1 KB · no license · 4 matches

The registry keeps no copy of this file: its repository has no license, so its authors keep all their rights to it. Your browser shows it from its source, with JavaScript.

It can be read at the source: screenshot_scripts/ss_tasks.R.

Overview

Authors: Zach Ladwig1, Kian Z. Kermani2,3, Youngeun Park2,3, Elena Housteau4, Ally Dworetsky5,6, Nathan Labora7,5, Joanna J. Hernandez4,8, Megan Dorn9,4, Derek M. Smith10, Derek Evan Nee5, Steven E. Petersen11,6,12,13,14, Rodrigo M. Braga1,4, Caterina Gratton4,2,3,5,15
ORCID iDs: Zach Ladwig, Youngeun Park
15 affiliations
  1. Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
  2. Department of Psychology, Urbana, IL, USA
  3. Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
  4. Department of Psychology, Northwestern University, Evanston, IL 60208, USA
  5. Department of Psychology, Florida State University, Tallahassee, FL 32304, USA
  6. Department of Neurology, Washington University St. Louis School of Medicine, St. Louis, MO 63110, USA
  7. Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
  8. Department of Psychology, Harvard University, Cambridge, MA 02138, USA
  9. Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
  10. Department of Neurology, Division of Cognitive Neurology/Neuropsychology, the Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
  11. Department of Radiology, Washington University St. Louis School of Medicine, St. Louis, MO 63110, USA
  12. Department of Psychological and Brain Sciences, Washington University St. Louis School of Medicine, St. Louis, MO 63110, USA
  13. Department of Neuroscience, Washington University St. Louis School of Medicine, St. Louis, MO 63110, USA
  14. Department of Biomedical Engineering, Washington University St. Louis School of Medicine, St. Louis, MO 63110, USA
  15. Lead contact
Institutions: Northwestern University (United States); University of Illinois Urbana-Champaign (United States); Florida State University (United States); Washington University in St. Louis (United States); University of Minnesota (United States); Harvard University (United States); Johns Hopkins University (United States); Johns Hopkins Medicine (United States)
Journal: Neuron, volume 114, issue 18, pages 3499-3516.e8
Dates: published online 18 May 2026; in print 16 September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.neuron.2026.04.011 · PMID 42155453 · PMCID PMC13289807 · OpenAlex W4412721376
Open access: hybrid, a free copy (OpenAlex)
Preprint: doi:10.2139/ssrn.5369461
Status: code verified
Categories: fMRI (modality), human (organism), systems (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Preprocessing, fMRI & imaging, Single-unit activity, calcium imaging
Keywords: fMRI, Brain Networks, Lateral Prefrontal Cortex, Association Cortex, Precision Functional Mapping
MeSH: Brain Mapping*, Magnetic Resonance Imaging*, Nerve Net*, Prefrontal Cortex*, Adult, Female, Humans, Male, Neural Pathways, Young Adult (* major topic)
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: NIA NIH HHS (P30 AG013854, T32 AG020506); National Institute of Mental Health (R01MH118370, R01MH121509); National Science Foundation (T32 AG020506, NSFCAREER 2305698); National Institutes of Health; National Institute on Aging; Office of The Provost; NIMH NIH HHS (R01 MH118370, R01 MH121509); National Institute of Neurological Disorders and Stroke (R01NS124738); northwestern university; NINDS NIH HHS (R01 NS124738)
Citations: cited by 15 papers (Europe PMC); 100 references in the paper

Abstract

Dominant models of human lateral prefrontal cortex (LPFC) organization emphasize broad domain-general zones and smooth functional gradients. However, these models rely on group-averaged neuroimaging, which can obscure fine-scale cortical features in highly inter-individually variable regions such as the LPFC. To address this limitation, we collected a new precision fMRI dataset from 10 individuals, each with approximately 2 h of resting-state fMRI and 6 h of task fMRI data. We mapped individual-specific LPFC networks using resting-state data and tested network-level functional preferences using task data. We found that individual LPFC networks showed fragmented and interdigitated organization compared to the group-averaged networks, including novel conserved motifs present across individuals. Task fMRI revealed that distinct yet adjacent networks support domain-specific processes (i.e., language, social cognition, and episodic projection) versus domain-general cognitive control. Sharp functional boundaries were visible at the individual level that could not be observed in group data. These findings uncover previously hidden fine-scale organizational principles present in the LPFC.

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

Repositories

Its files are read in the Code ↔ Paper reader above, with 13 matches between paragraphs and lines of code.

GrattonLab/Ladwig-LPFC

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: ca2ae45b14fcd7f08bae4478935ca9fec66d880e, 23 February 2026
Languages: MATLAB (22), Shell (7), R (5)
Size: 51 files, 34 scripts
Software Heritage: not archived
Found in: “Data and code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: FieldTrip (21 files), Statistics and Machine Learning Toolbox (9 files), AFNI (5 files), GIfTI library for MATLAB (1 file), Parallel Computing Toolbox (1 file), Tools for NIfTI and ANALYZE image (MATLAB) (1 file), Connectome Workbench (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
35 files, not copied: shown from their source

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At the source: github.com/GrattonLab/Ladwig-LPFC

evlab.mit.edu/resources-all/download-localizer-tasks

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: the link answers
Software Heritage: not checked
Found in: the text, “Auditory language task”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)
  • 28 September 2026: the link answers (HTTP 200)
At the source: evlab.mit.edu/resources-all/download-localizer-tasks

thomasyeolab/cbig

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 35b5664bec8822e2f77da5e090e96f91d0095be6, 31 August 2026
Languages: MATLAB (2100), Shell (651), Python (571), C (113), C++ (65), C/C++ (62), R (25), Jupyter (5)
Size: 9,187 files, 3,592 scripts
Software Heritage: not archived
Found in: the text, “Group-averaged network parcellation”
Holds: README, license file, environment (external_packages/python/mapalign-master/requirements.txt, external_packages/python/mapalign-master/setup.py, external_packages/python/yapf-master/setup.cfg, external_packages/python/yapf-master/setup.py), tests, documentation, 2 notebooks
Not found: CITATION.cff, continuous integration
Tools: NumPy (130 files), PyTorch (122 files), FreeSurfer (93 files), SciPy (61 files), FieldTrip (60 files), Statistics and Machine Learning Toolbox (50 files), FSL (44 files), SPM (40 files), GIfTI library for MATLAB (10 files), Image Processing Toolbox (8 files), Connectome Workbench (8 files), scikit-learn (5 files), AFNI (2 files), Matplotlib (2 files), Tools for NIfTI and ANALYZE image (MATLAB) (2 files), ANTs (1 file), NiBabel (1 file), Nilearn (1 file), tedana (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
2,000 files
At the source: github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yeo2011_fcMRI_clustering

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

Tracing map

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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data and code availability

Preprocessed CIFTI resting-state and task data have been deposited at OpenNeuro as https://openneuro.org/datasets/ds006598/versions/1.0.0 and are publicly available as of the date of publication.

All original code has been deposited at https://github.com/GrattonLab/Ladwig-LPFC and is publicly available as of the date of publication.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request

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

Versions

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Version 2, 28 September 2026

  • Publisher: — → Cell Press

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 13 authors, 5 keywords, 10 MeSH terms, 10 funders, 97 references.

Cite

This paper

Ladwig, Z., Kermani, K. Z., Park, Y., Housteau, E., Dworetsky, A., Labora, N., Hernandez, J. J., Dorn, M., Smith, D. M., Nee, D. E., Petersen, S. E., Braga, R. M., & Gratton, C. (2026). Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex. Neuron, 114(18), 3499-3516.e8. https://doi.org/10.1016/j.neuron.2026.04.011

BibTeX

@article{ladwig2026precision,
author = {Ladwig, Zach and Kermani, Kian Z. and Park, Youngeun and Housteau, Elena and Dworetsky, Ally and Labora, Nathan and Hernandez, Joanna J. and Dorn, Megan and Smith, Derek M. and Nee, Derek Evan and Petersen, Steven E. and Braga, Rodrigo M. and Gratton, Caterina},
title = {{Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex}},
journal = {Neuron},
year = {2026},
month = may,
volume = {114},
number = {18},
pages = {3499--3516.e8},
publisher = {Cell Press},
issn = {0896-6273},
doi = {10.1016/j.neuron.2026.04.011},
url = {https://doi.org/10.1016/j.neuron.2026.04.011},
pmid = {42155453},
pmcid = {PMC13289807}
}

RIS

TY - JOUR
AU - Ladwig, Zach
AU - Kermani, Kian Z.
AU - Park, Youngeun
AU - Housteau, Elena
AU - Dworetsky, Ally
AU - Labora, Nathan
AU - Hernandez, Joanna J.
AU - Dorn, Megan
AU - Smith, Derek M.
AU - Nee, Derek Evan
AU - Petersen, Steven E.
AU - Braga, Rodrigo M.
AU - Gratton, Caterina
TI - Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex
T2 - Neuron
J2 - Neuron
PY - 2026
DA - 2026/05/18
VL - 114
IS - 18
SP - 3499
EP - 3516.e8
SN - 0896-6273
PB - Cell Press
DO - 10.1016/j.neuron.2026.04.011
UR - https://doi.org/10.1016/j.neuron.2026.04.011
LA - en
ER -

CSL-JSON

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