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Protocol for whole-brain immunolabeling, clearing, and light-sheet imaging of C-FOS in the pigeon.

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 · all tie a paragraph to a whole file without given lines: weak matches, whose lines are not tinted
  1. [1] § Before you begin ↔ ClearMap/ImageProcessing/__init__.py, the whole file · a weak match · score 0.81 · iDISCO, volumetric imaging, brain sample, ClearMap, Light sheet microscopy, fast · Report a mismatch
  2. [2] § Expected outcomes ↔ ClearMap/ImageProcessing/__init__.py, the whole file · a weak match · score 0.73 · mouse brain, spot detection, ClearMap, algorithm, voxels, light sheet · Report a mismatch
  3. [3] § Expected outcomes ↔ ClearMap/Analysis/__init__.py, the whole file · a weak match · score 0.65 · mouse brain, brain atlas, ClearMap, cells · Report a mismatch

Paper

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The authors' code

Python · 72 lines · 3.3 KB · GPL-3.0 · 2 matches

  1. # -*- coding: utf-8 -*-
  2. """This sub-package provides routines for volumetric image processing in parallel
  4. This part of the *ClearMap* toolbox is designed in a modular way to allow for
  5. fast and flexible extension and addition of specific image processing
  6. algorithms.
  8. The toolbox part consists of two parts:
  9. * `Volumetric Image Processing`_
  10. * `Parallel Image Processing`_
  13. Volumetric Image Processing
  14. ---------------------------
  16. The image processing routines provided in the standard package are listed below
  18. ======================================================= ===========================================================
  19. Module Descrition
  20. ======================================================= ===========================================================
  21. :mod:`~ClearMap.ImageProcessing.BackgroundRemoval` Background estimation and removal via morphological opening
  22. :mod:`~ClearMap.ImageProcessing.IlluminationCorrection` Correction of vignetting and other illumination errors
  23. :mod:`~ClearMap.ImageProcessing.GreyReconstruction` Reconstruction of images
  24. :mod:`~ClearMap.ImageProcessing.Filter` Filtering of images via a large set of filter kernels
  25. :mod:`~ClearMap.ImageProcessing.MaximaDetection` Detection of maxima and h-max transforms
  26. :mod:`~ClearMap.ImageProcessing.SpotDetection` Detection of local peaks / spots / nuclei
  27. :mod:`~ClearMap.ImageProcessing.CellDetection` Detection of cells
  28. :mod:`~ClearMap.ImageProcessing.CellSizeDetection` Detection of cell shapes and volumes via e.g. watershed
  29. :mod:`~ClearMap.ImageProcessing.IlastikClassification` Classification of voxels via interface to `Ilastik <http://ilastik.org/>`_
  30. ======================================================= ===========================================================
  32. While some of these modules provide basic volumetric image processing
  33. functionality some routines combine those functions to provide predefined
  34. higher level cell detection, cell size and intensity measurements.
  36. The higher level routines are optimized for iDISCO+ cleared mouse brain samples
  37. stained for c-Fos expression. Other data sets might require a redesign of these
  38. higher level functions.
  41. Parallel Image Processing
  42. -------------------------
  44. For large volumetric image data sets from e.g. light sheet microscopy
  45. parallel processing is essential to speed up calculations.
  47. In this toolbox the image processing is parallelized via splitting a volumetric
  48. image stack into several sub-stacks, typically in z-direction. Because most of
  49. the image processing steps are non-local sub-stacks are created with overlaps
  50. and the results rejoined accordingly to minimize boundary effects.
  52. Parallel processing is handled via the
  53. :mod:`~ClearMap.ImageProcessing.StackProcessing` module.
  56. External Packages
  57. -----------------
  59. The :mod:`~ClearMap.ImageProcessing` module makes use of external image
  60. processing packages including:
  62. * `Open Cv2 <http://opencv.org/>`_
  63. * `Scipy <http://www.scipy.org/>`_
  64. * `Scikit-Image <http://scikit-image.org/docs/dev/api/skimage.html>`_
  65. * `Ilastik <http://ilastik.org/>`_
  67. Routines form these packages were freely chosen to optimize for speed and
  68. memory consumption
  70. """
  71. #:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
  72. #:license: GNU, see LICENSE.txt for details.

__init__.py at commit 1aeaad6, under GPL-3.0 · at the source

Overview

Authors: Spencer D. Balay1, Gregory C. Nordmann2, Simon Nimpf1, E. Pascal Malkemper3, Lukas Landler4, David A. Keays1,5,6
ORCID iDs: Spencer D. Balay, David A. Keays
  1. Department of Biology, Ludwig-Maximilians-University Munich, Planegg-Martinsried, 82152 Planegg, Germany
  2. Max Planck Institute for Biological Intelligence, Planegg-Martinsried, 82152 Planegg, Germany
  3. Max Planck Institute for Neurobiology of Behavior - Caesar, 53175 Bonn, Germany
  4. BOKU University, Institute of Zoology, Department of Ecosystem Management, Climate and Biodiversity, 1180 Vienna, Austria
  5. University of Cambridge, Department of Physiology, Development & Neuroscience, CB2 3EG Cambridge, UK
  6. Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), 1030 Vienna, Austria
Institutions: Ludwig-Maximilians-Universität München (Germany); Max Planck Institute for Biological Intelligence (Germany); Max Planck Institute for Neurobiology of Behavior – caesar (Germany); BOKU University (Austria); Research Institute of Molecular Pathology (Austria); University of Cambridge (United Kingdom); Vienna Biocenter (Austria)
Journal: STAR protocols, volume 7, issue 2, article 104462
Dates: published online 24 March 2026; in print June 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.xpro.2026.104462 · PMID 41880330 · PMCID PMC13045675 · OpenAlex W7140234844
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: histology / microscopy (modality), other (organism)
Methods: Machine learning
Keywords: Model Organisms, Neuroscience, Systems biology
MeSH: Brain*, Columbidae*, Immunohistochemistry*, Proto-Oncogene Proteins c-fos*, Animals (* major topic)
Topic: Retinal Development and Disorders (Ophthalmology, Medicine), according to OpenAlex
Funding: European Research Council (336725, 819336); NSERC (557761)
Citations: not cited yet (Europe PMC); 23 references in the paper

Abstract

Advancements in tissue clearing and light sheet microscopy have provided new ways to study neural circuits dedicated to sensory processing in a diverse range of animal species. Here, we present a modified iDISCO+ protocol for whole-brain immunolabeling with the neural activity marker C-FOS in the pigeon brain. We describe steps for whole-brain pre-processing, bleaching, and immunostaining. We then detail procedures for obtaining ultramicroscopic light-sheet images in cleared pigeon brains.

For complete details on the use and execution of this protocol, please refer to Nordmann et al.1

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 3 matches between paragraphs and lines of code.

ChristophKirst/ClearMap

License: GPL-3.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 1aeaad6078f90a44fbb4423f1e1f229b40121c6a, 17 June 2020
Languages: Python (88), JavaScript (11), MATLAB (10), C (1), Shell (1)
Size: 495 files, 111 scripts
Software Heritage: not archived
Found in: the text, “Key resources table”
Holds: README, license file, environment (setup.py), tests, documentation
Not found: CITATION.cff, continuous integration
Tools: NumPy (41 files), SciPy (12 files), Matplotlib (6 files), Image Processing Toolbox (3 files), OpenCV (3 files), scikit-image (3 files), h5py (2 files), tifffile (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
113 files
At the source: github.com/ChristophKirst/ClearMap

KeaysLab/ClearingProtocol

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 421cb6130cb920d97c245d6443fbe15390b23127, 29 January 2026
Size: 8 files, 0 scripts
Software Heritage: not archived
Found in: the text, “Expected outcomes”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
At the source: github.com/KeaysLab/ClearingProtocol

Zenodo 18406963

License: CC-BY-4.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Materials availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
  • 30 September 2026: the link answers (HTTP 200)
At the source: doi.org/10.5281/zenodo.18406963

Materials availability

• This study did not generate new unique reagents. Commercially available reagents are listed in the key resources table. • 3D printer files for the polyetheretherketone pigeon brain sample holder and dorsal/ventral insert molds have been uploaded to the Keays Lab GitHub repository (https://github.com/KeaysLab/ClearingProtocol). • Image files for the custom pigeon brain reference template have been uploaded to the Keays Lab GitHub repository (https://github.com/KeaysLab/ClearingProtocol). • The GitHub repository DOI is as follows: https://doi.org/10.5281/zenodo.18406963.

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

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:

  • 3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
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  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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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

• Raw data and statistics for the signal intensity experiment (Figure 4) are provided as a supplementary file. • This study did not generate code.

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

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 3 keywords, 5 MeSH terms, 2 funders, 23 references.

Cite

This paper

Balay, S. D., Nordmann, G. C., Nimpf, S., Malkemper, E. P., Landler, L., & Keays, D. A. (2026). Protocol for whole-brain immunolabeling, clearing, and light-sheet imaging of C-FOS in the pigeon. STAR protocols, 7(2), 104462. https://doi.org/10.1016/j.xpro.2026.104462

BibTeX

@article{balay2026protocol,
author = {Balay, Spencer D. and Nordmann, Gregory C. and Nimpf, Simon and Malkemper, E. Pascal and Landler, Lukas and Keays, David A.},
title = {{Protocol for whole-brain immunolabeling, clearing, and light-sheet imaging of C-FOS in the pigeon}},
journal = {STAR protocols},
year = {2026},
month = mar,
volume = {7},
number = {2},
pages = {104462},
publisher = {Elsevier},
issn = {2666-1667},
doi = {10.1016/j.xpro.2026.104462},
url = {https://doi.org/10.1016/j.xpro.2026.104462},
pmid = {41880330},
pmcid = {PMC13045675}
}

RIS

TY - JOUR
AU - Balay, Spencer D.
AU - Nordmann, Gregory C.
AU - Nimpf, Simon
AU - Malkemper, E. Pascal
AU - Landler, Lukas
AU - Keays, David A.
TI - Protocol for whole-brain immunolabeling, clearing, and light-sheet imaging of C-FOS in the pigeon
T2 - STAR protocols
J2 - STAR Protoc
PY - 2026
DA - 2026/03/24
VL - 7
IS - 2
SP - 104462
SN - 2666-1667
PB - Elsevier
DO - 10.1016/j.xpro.2026.104462
UR - https://doi.org/10.1016/j.xpro.2026.104462
LA - en
ER -

CSL-JSON

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"container-title": "STAR protocols",
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"language": "en",
"issued": {
"date-parts": [
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24
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]
}
}

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