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Published December 20, 2022 | Version 1.0
Dataset Open

A brain-wide, annotated dataset of WFA-positive perineuronal nets and parvalbumin neurons in the adult mouse brain

  • 1. BIO@SNS lab, Scuola Normale Superiore, Pisa, Italy
  • 2. Institute of Information Science and Technologies (ISTI-CNR), Pisa, Italy
  • 3. University of Pisa, Pisa, Italy
  • 4. Institute of Neuroscience (IN-CNR), Pisa, Italy
  • 1. BIO@SNS lab, Scuola Normale Superiore, Pisa, Italy
  • 2. Institute of Information Science and Technologies (ISTI-CNR), Pisa, Italy
  • 3. University of Pisa, Pisa, Italy
  • 4. Institute of Neuroscience (IN-CNR), Pisa, Italy

Description

Microscopy dataset for perineuronal nets and parvalbumin-positive interneurons in the adult mouse brain

This dataset contains the data used in the paper titled:

A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain

Content

The dataset contains microscopy images of coronal brain slices of 7 adult mice and several kinds of biological annotations.

For each mouse, the annotations contain information about:

  • Several files related to the alignment of each brain slice to the Allen Brain Institute CCFv3 atlas (for a more detailed description see here)
  • Location of individual PNNs and PV cells in each slice

Folder Structure

There are separate folders for each mouse. Each folder is named with the ID of that mouse.

Each mouse folder contains:

  1. a MOUSEID-info.xml file - Contains general information for the mouse and images
  2. a MOUSEID-quicknii.xml file - Contains information for the alignment to the Allen Brain Atlas CCFv3
  3. a MOUSEID-visualign.json file - Contains information for the alignment to the Allen Brain Atlas CCFv3
  4. a counts folder - Contains annotations for PNNs and PV cell locations for each slice
  5. a dispField folder - Contains displacement fields for non-rigid alignment to the Allen Brain Atlas CCFv3
  6. a hiRes folder - Contains original, full-resolution, experimental images
  7. a masks folder - Contains binary masks for restricting the analysis
  8. a thumbnails folder - Contains low-resolution

Files Description

  • MOUSEID-info.xml
    • XML file containing information about this mouse and details on each image
  • MOUSEID-quicknii.xml
    • XML file used for global alignment of all the images to the CCFv3 using the software QuickNII
  • MOUSEID-visualign.json
    • JSON file used for the interactive local non-rigid alignment of brain slices to the CCFv3 using the software VisuAlign
  • counts folder
    • Folder containing two .csv files for each high-resolution image. Each .csv file contains the (x,y) location of all PNNs (channel 1) and PV cells (channel 2) detected in that image
  • dispField folder
    • This folder contains displacement fields in the X and Y direction for each image. These files are meant to be loaded in MATLAB and fed to the function imwarp. This function can be used to apply a non-rigid transformation to the reference volume slices in order for it to closely match experimental images.
  • hiRes folder
    • Folder containing high-resolution experimental images split by channels
  • masks folder
    • Folder containing binary masks. These files are used to restrict the analysis to portions of the image containing biological tissue and to exclude areas where the tissue was damaged or presented artifacts
  • thumbnails folder
    • Folder containing a low-resolution RGB version of the experimental images 

 

Notes

This work was funded by: AI4Media - A European Excellence Centre for Media, Society and Democracy (EC, H2020 n. 951911); the Tuscany Health Ecosystem (THE) Project (CUP I53C22000780001), funded by the National Recovery and Resilience Plan (NRPP), within the NextGeneration Europe (NGEU) Program; PRIN2017 2017HMH8FA to T.P., R.M. was supported by Fondazione Umberto Veronesi.

Files

rawData.zip

Files (48.7 GB)

Name Size Download all
md5:c8c57aa74182207db67aa0b8072be3a7
48.7 GB Preview Download

Additional details

Related works

Continues
Dataset: 10.5281/zenodo.7886215 (DOI)