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Experimental quality control induces changes in Allen mouse brain connectomes.

Code ↔ Paper

15 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 15 matches · 3 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Defining injection density and projection density ↔ before_manual_qc/download_knox_conn_data.sh, the whole file · a weak match · score 0.79 · injection fraction, WT experiments, injection density, Allen API, projection density, downloaded
  2. [2] § Methods › Defining injection density and projection density ↔ before_manual_qc/multiply_threshold_inj_proj.sh, the whole file · a weak match · score 0.77 · injection fraction, WT experiments, injection density, Allen API, projection density, tracer
  3. [3] § Methods › Nested leave-one-out cross-validation analysis ↔ run-all-after-manual-QC.sh, lines 46–123 · score 0.70 · nested homogeneous, nested voxel, compile, connectivity models, sensitivity, py
  4. [4] § Methods › Automated quality control ↔ before_manual_qc/create_automated_qc_csv.R, lines 48–94 · score 0.67 · cerebral aqueduct, injection density, thin, misalignment, ventricular, manual QC
  5. [5] § Methods › Manual quality control ↔ before_manual_qc/make_qc_images_bin_threshold.sh, lines 41–122 · score 0.64 · QC images, slice images, projection densities, sh, cropping, manual QC
  6. [6] § Methods › Defining injection density and projection density ↔ before_manual_qc/multiply_threshold_inj_proj.sh, the whole file · a weak match · score 0.61 · injection fraction, injection density, projection density, segmented, connectomes
  7. [7] § Methods › Automated quality control ↔ after_manual_qc/overall_qc_exclusion.R, lines 1–43 · score 0.61 · robust outlier filtering, ventricular voxels, skewness, threshold, injection
  8. [8] § Methods › Rebuilding the regionalized voxel and homogeneous model connectomes ↔ after_manual_qc/build_model_new_excluded.py, lines 47–151 · score 0.59 · build model, normalized connection strengths, hyperparameter, weights, fitted, rebuilt
  9. [9] § Methods › Rebuilding the regionalized voxel and homogeneous model connectomes ↔ run-all-after-manual-QC.sh, lines 1–44 · score 0.58 · mouse_connectivity_models, Allen API, Knox connectome, rebuild, rebuilt, QC
  10. [10] § Methods › Nested leave-one-out cross-validation analysis ↔ after_manual_qc/run_nested_homogeneous_new_excluded.py, lines 35–48 · score 0.57 · nested homogeneous, cross validation, error, models, QC
  11. [11] § Methods › Rich club and community detection analysis ↔ graph_theory/rich_club_connectome_bin.m, lines 1–5 · score 0.57 · Brain Connectivity Toolbox, Rich Club, MATLAB
  12. [12] § Methods › Rebuilding the regionalized voxel and homogeneous model connectomes ↔ run-all-after-manual-QC.sh, lines 46–123 · score 0.51 · hyperparameter selection, py, homogeneous, Rebuilding, rebuilt, model
  13. [13] § Results › Manual QC reveals spatially and qualitatively diverse failures ↔ after_manual_qc/overall_qc_exclusion.R, lines 181–257 · score 0.51 · cortical leaking, Manual QC, nonspecific, misaligned, removal, injections
  14. [14] § Methods › Nested leave-one-out cross-validation analysis ↔ after_manual_qc/run_hyperparameter_selection_new_excluded.py, lines 35–56 · score 0.51 · voxel model, optimal, hyperparameter, fitted, kernel, Nested
  15. [15] § Methods › Rich club and community detection analysis ↔ visualizations/figure_5.R, lines 297–353 · score 0.51 · Louvain community assignments, rich club, connections

Paper

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The authors' code

Shell · 123 lines · 5.5 KB · no license · 3 matches

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It can be read at the source: run-all-after-manual-QC.sh.

Overview

Authors: Vikram Nathan1,2, Stephanie Tullo1, Lizette Herrera-Portillo1,2, Gabriel A Devenyi1,3, Yohan Yee4,5, M Mallar Chakravarty1,3,6
ORCID iDs: Vikram Nathan
  1. Cerebral Imaging Center, Douglas Mental Health University Institute, Montréal, QC, Canada
  2. Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada
  3. Department of Psychiatry, McGill University, Montréal, Canada
  4. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
  5. Experimental Imaging Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
  6. Department of Biological & Biomedical Engineering, McGill University, Montréal, Canada
Institutions: Douglas Mental Health University Institute (Canada); McGill University (Canada); University of Calgary (Canada)
Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1310
Dates: received 23 February 2026; accepted 15 June 2026; published online 28 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/imag.a.1310 · PMID 42529501 · PMCID PMC13417618 · OpenAlex W7167062594
Open access: diamond, a free copy (OpenAlex)
Status: code verified
Categories: mouse (organism), methods / tools (subfield)
Methods: Connectivity, Machine learning, Statistics, fMRI & imaging, Physiology & signal measures
Keywords: connectomics, quality control, tracer-derived connectivity, Allen mouse brain connectivity atlas (AMBCA)
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Douglas Foundation; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé
Citations: not cited yet (Europe PMC); 72 references in the paper

Abstract

The Allen Mouse Brain Connectivity Atlas (AMBCA) is widely used to represent structural connectivity in the mouse brain. The AMBCA consists of tracer injection experiments where neuronal projections axonally connected to the initial injection site are labeled. The resulting whole-brain structural connectomes, derived from a subset of these experiments in C57BL/6 mice, have been used in several studies of connectomic architectures. However, through close inspection of n = 437 distinct experiments used in a publicly-available connectome (Knox et al., 2018), we observed experiments with off-target injections, diffuse projections, unrealistically small injections and projections, and anatomical misalignments, affecting the accuracy and applicability of these connectivity experiments. We applied a combined automated and manual quality control (QC) and identified n = 56 (~13% of the original n = 437) experiments representing a wide variety of injection and projection failures across the brain. Automated QC was used to detect extreme injection and projection sizes and misalignments, while manual QC was used to detect subtle off-target tracer spreading. Using the remaining n = 381 experiments, we rebuilt two different connectomes using previously-published methods; specifically: the regionalized voxel model from Knox et al. (2018), and the homogeneous model from Oh et al. (2014). Our rebuilt connectomes show strong losses in connectivity between regions with limited evidence of structural connectivity by other methods (e.g., hippocampus-medulla, cerebellum-isocortex) and gains in connectivity between regions with strong connectivity evidence (hypothalamus-cerebellum, hypothalamus-isocortex). Finally, we analyzed the rich club and community organization to demonstrate the potential downstream impacts on the representation of the overall structural connectome architectures of our QC’d connectomes and observed subtle whole-brain organizational changes. We present our rebuilt connectomes, and particularly highlight the regionalized voxel model, as more accurate representations of structural connectivity derived from the AMBCA.

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

Repository

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vik16nathan/allen_connectome_qc

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: df87f4e22d1c1b8407fc2d5bfc6c781e93c8a243, 10 August 2026
Languages: Shell (14), R (13), Python (10), MATLAB (2)
Size: 161 files, 39 scripts
Software Heritage: not archived
Found in: “Data and Code Availability”
Holds: README, environment (pyproject.toml)
Not found: license file, CITATION.cff, tests, continuous integration, documentation
Tools: tidyverse (13 files), NumPy (9 files), AllenSDK (6 files), ggplot2 (5 files), scikit-learn (5 files), pandas (4 files), patchwork (4 files), ANTs (3 files), pheatmap (3 files), Brain Connectivity Toolbox (2 files), SciPy (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
40 files, not copied: shown from their source

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At the source: github.com/vik16nathan/allen_connectome_qc

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

Tracing map

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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;
  • 39 scripts, each with its path and the digest of its content;
  • 15 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

All code is stored on https://github.com/vik16nathan/allen_connectome_qc. All input data is publicly available and downloaded from the Allen API.

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

Versions

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Version 2, 28 September 2026

  • Funding: added Douglas Foundation; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 6 authors, 4 keywords, 72 references.

Cite

This paper

Nathan, V., Tullo, S., Herrera-Portillo, L., Devenyi, G. A., Yee, Y., & Chakravarty, M. M. (2026). Experimental quality control induces changes in Allen mouse brain connectomes. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1310. https://doi.org/10.1162/imag.a.1310

BibTeX

@article{nathan2026experimental,
author = {Nathan, Vikram and Tullo, Stephanie and Herrera-Portillo, Lizette and Devenyi, Gabriel A and Yee, Yohan and Chakravarty, M Mallar},
title = {{Experimental quality control induces changes in Allen mouse brain connectomes}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = jul,
volume = {4},
pages = {IMAG.a.1310},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/imag.a.1310},
url = {https://doi.org/10.1162/imag.a.1310},
pmid = {42529501},
pmcid = {PMC13417618}
}

RIS

TY - JOUR
AU - Nathan, Vikram
AU - Tullo, Stephanie
AU - Herrera-Portillo, Lizette
AU - Devenyi, Gabriel A
AU - Yee, Yohan
AU - Chakravarty, M Mallar
TI - Experimental quality control induces changes in Allen mouse brain connectomes
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/07/28
VL - 4
SP - IMAG.a.1310
SN - 2837-6056
PB - MIT Press
DO - 10.1162/imag.a.1310
UR - https://doi.org/10.1162/imag.a.1310
LA - en
ER -

CSL-JSON

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