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Frontoparietal control-default mode connectivity predicts TMS effects on cognitive control.

Code ↔ Paper

5 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 5 matches
  1. [1] § Methods › Behavioral data processing and modeling ↔ 4_DDM_Validation.Rmd, lines 148–218 · score 0.67 · posterior predictive checks, fast dm, Validations, DDM, model
  2. [2] § Methods › Behavioral data processing and modeling ↔ 3_DDMAnalysis.Rmd, lines 421–500 · score 0.56 · Exploratory factor, paran, parallel, psych, factor model, components
  3. [3] § Methods › Behavioral data processing and modeling ↔ 5_Alternative_Models_Raw.Rmd, lines 473–552 · score 0.56 · Exploratory factor, paran, parallel, psych, factor model, components
  4. [4] § Methods › Statistical analysis ↔ 7_Alternative_Model_MRI_SCRUBBED_DDM_Analysis.Rmd, lines 17–88 · score 0.56 · framewise displacement, FD, MRI, head, models
  5. [5] § Results › Validation of factor structure ↔ 5_Alternative_Models_Raw.Rmd, lines 621–633 · score 0.52 · chi square, full model, CFA, CFI, RMSEA, SRMR

Paper

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The authors' code

R Markdown · 2,660 lines · 108 KB · no license · 2 matches

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Overview

Authors: Brian Kim1, John D. Medaglia1,2
ORCID iDs: Brian Kim
  1. Department of Applied Cognitive and Brain Sciences, Drexel University, Philadelphia, PA, United States
  2. Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
Institutions: Drexel University (United States); University of Pennsylvania (United States)
Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1298
Dates: received 21 January 2026; accepted 4 June 2026; published online 14 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/imag.a.1298 · PMID 42459500 · PMCID PMC13370750 · OpenAlex W7165898388
Open access: diamond, a free copy (OpenAlex)
Status: code verified
Categories: other (modality), human (organism), cognitive (subfield)
Methods: Statistics, fMRI & imaging
Keywords: cognitive control, neuromodulation, TMS, LFPN/MFPN connectivity, DDM, individual differences, latent factor analysis
Topic: Transcranial Magnetic Stimulation Studies (Neurology, Neuroscience), according to OpenAlex
Funding: National Institutes of Health (1-DP5-OD-021352-01); Starfish Neuroscience
Citations: not cited yet (Europe PMC); 74 references in the paper

Abstract

Transcranial Magnetic Stimulation (TMS) is a promising tool to probe and enhance cognitive control, yet effects are often inconsistent across individuals. These inconsistencies may arise from individual differences in Lateral Frontoparietal (Control) Network (L-FPN) and Medial Frontoparietal (Default) Network (M-FPN) interactions, essential for suppressing internal distraction and facilitating cognitive control. We tested whether baseline connectivity between the L-FPN and M-FPN moderates TMS outcomes in cognitive control tasks. We used the generalized drift rate as a task-general behavioral index of cognitive control, as it overcomes the reliability and interpretability limitations of standard difference measures. Participants completed inhibition (Stroop), working memory (n-back), and flexibility (Navon) tasks before and after intermittent theta-burst stimulation (iTBS) to the L-FPN, dorsal frontoparietal (attention) network (D-FPN), or cranial vertex. Stimulation targets were defined using individualized resting-state parcellations to maximize precision. We found that baseline connectivity moderated stimulation outcomes: individuals with more integrated L-FPN/M-FPN networks benefited most from L-FPN stimulation, whereas those with more segregated networks showed greater improvements from D-FPN stimulation. Notably, stimulation of a single site did not uniformly enhance performance, underscoring the importance of individual network profiles. These findings highlight L-FPN/M-FPN interactions as a basis for individualized TMS interventions and the utility of combining precise network mapping with robust behavioral modeling to optimize neuromodulation interventions.

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 5 matches between paragraphs and lines of code.

CogNeW/project_L-FPN_M-FPN_cc_stim

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: dcc0852cf6df646a29ebb848890f5b2d251860a2, 7 July 2026
Languages: R (7)
Size: 1,587 files, 7 scripts
Software Heritage: not archived
Found in: “Data and Code Availability”
Holds: README, 7 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (7 files), ggplot2 (6 files), data.table (4 files), lmerTest (4 files), emmeans (3 files), lavaan (2 files), psych (2 files), patchwork (1 file), reshape2 (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
8 files, not copied: shown from their source

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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;
  • 7 scripts, each with its path and the digest of its content;
  • 5 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 and Code Availability

The R Code and raw data files required to reproduce the analyses reported are available at: https://github.com/CogNeW/project_L-FPN_M-FPN_cc_stim

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

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 2 authors, 7 keywords, 2 funders, 74 references.

Cite

This paper

Kim, B., & Medaglia, J. D. (2026). Frontoparietal control-default mode connectivity predicts TMS effects on cognitive control. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1298. https://doi.org/10.1162/imag.a.1298

BibTeX

@article{kim2026frontoparietal,
author = {Kim, Brian and Medaglia, John D.},
title = {{Frontoparietal control-default mode connectivity predicts TMS effects on cognitive control}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = jul,
volume = {4},
pages = {IMAG.a.1298},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/imag.a.1298},
url = {https://doi.org/10.1162/imag.a.1298},
pmid = {42459500},
pmcid = {PMC13370750}
}

RIS

TY - JOUR
AU - Kim, Brian
AU - Medaglia, John D.
TI - Frontoparietal control-default mode connectivity predicts TMS effects on cognitive control
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/07/14
VL - 4
SP - IMAG.a.1298
SN - 2837-6056
PB - MIT Press
DO - 10.1162/imag.a.1298
UR - https://doi.org/10.1162/imag.a.1298
LA - en
ER -

CSL-JSON

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