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46 results for “adult mouse brain”
A deep learning-based dataset of WFA-positive perineuronal nets and parvalbumin neurons localizations in the adult mouse brain
<p><strong>Quality-controlled predictions of deep learning models for cell counting</strong></p> <p>This dataset contains high-resolution images for the visualization of perineuronal nets (PNNs) and parvalbumin-expressing (PV) cells analyzed in the paper:</p> <p><em>A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain.</em></p> <p>The dataset integrates the raw data published on a <a href="https://zenodo.org/record/7419282">previous upload</a> on Zenodo.</p> <p>Cell locations were obtained using two deep-learning models for cell counting (publicly available on <a href="http://github.com/ciampluca/counting_perineuronal_nets">GitHub</a>, details in the paper by <a href="https://www.sciencedirect.com/science/article/pii/S1361841522001475">Ciampi et al., 2022</a>). The output of the deep-learning pipeline was filtered based on the <em>score</em> assigned to each cell prediction, by removing all the PNNs with a score lower than 0.4 and all the PV cells with a score lower than 0.55. Cases of artefactual cell detection were finally removed manually by visual inspection of the images. </p> <p><strong>Content</strong></p> <p>The dataset contains microscopy images of coronal brain slices from 7 adult mice. The objects highlighted in these images represent the final set of PNNs/PV cells that were used in all the analysis of the paper.</p> <p><strong>Folder Structure and file naming conventions</strong></p> <p>There are separate folders for each mouse. Each folder is named with the ID of that mouse. Within each folder, images are assigned a code specifying the channel (C1 for PNNs, C2 for PV cells).</p> <p> </p>
Serial Coronal Sections Of An Adult Mouse Brain - Sample Dataset
<p>Experimental data: 88 serial coronal sections of the full brain of an adult mouse.</p> <p>Preparation of the sample: details to come...</p> <p>Imaging of the sample: details to come...</p> <p>2 channels per section are present:</p> <ul> <li>DAPI</li> <li>autofluorescence</li> </ul> <p>This dataset is used in particular as a test dataset for the <a href="https://c4science.ch/w/bioimaging_and_optics_platform_biop/image-processing/image-to-atlas-registration/">Allen Brain Biop Aligner Fiji plugin</a>.</p> <p>Some sections are flipped (left / right), for workflow documentation purpose.</p> <p>Animal handling according to protocols approved by the Swiss animal license VD2808.1</p>
A brain-wide, annotated dataset of WFA-positive perineuronal nets and parvalbumin neurons in the adult mouse brain
<p><strong>Microscopy dataset for perineuronal nets and parvalbumin-positive interneurons in the adult mouse brain</strong></p> <p>This dataset contains the data used in the paper titled:</p> <p><em>A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain</em></p> <p><strong>Content</strong></p> <p>The dataset contains microscopy images of coronal brain slices of 7 adult mice and several kinds of biological annotations.</p> <p>For each mouse, the annotations contain information about:</p> <ul> <li>Several files related to the alignment of each brain slice to the Allen Brain Institute CCFv3 atlas (for a more detailed description see <a href="https://github.com/LeonardoLupori/brainAlignment">here</a>)</li> <li>Location of individual PNNs and PV cells in each slice</li> </ul> <p><strong>Folder Structure</strong></p> <p>There are separate folders for each mouse. Each folder is named with the ID of that mouse.</p> <p>Each mouse folder contains:</p> <ol> <li>a <em>MOUSEID-info.xml</em> file - Contains general information for the mouse and images</li> <li>a <em>MOUSEID-quicknii.xml</em> file - Contains information for the alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>MOUSEID-visualign.json</em> file - Contains information for the alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>counts </em>folder - Contains annotations for PNNs and PV cell locations for each slice</li> <li>a <em>dispField </em>folder - Contains displacement fields for non-rigid alignment to the Allen Brain Atlas CCFv3</li> <li>a <em>hiRes </em>folder - Contains original, full-resolution, experimental images</li> <li>a <em>masks </em>folder - Contains binary masks for restricting the analysis</li> <li>a <em>thumbnails </em>folder - Contains low-resolution</li> </ol> <p><strong>Files Description</strong></p> <ul> <li><em>MOUSEID-info.xml</em> <ul> <li>XML file containing information about this mouse and details on each image</li> </ul> </li> <li><em>MOUSEID-quicknii.xml</em> <ul> <li>XML file used for global alignment of all the images to the CCFv3 using the software <a href="https://www.nitrc.org/projects/quicknii">QuickNII</a></li> </ul> </li> <li><em>MOUSEID-visualign.json</em> <ul> <li>JSON file used for the interactive local non-rigid alignment of brain slices to the CCFv3 using the software <a href="https://www.nitrc.org/projects/visualign">VisuAlign</a></li> </ul> </li> <li><em>counts </em>folder <ul> <li>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</li> </ul> </li> <li><em>dispField </em>folder <ul> <li>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 <a href="https://it.mathworks.com/help/images/ref/imwarp.html">imwarp</a>. 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.</li> </ul> </li> <li><em>hiRes </em>folder <ul> <li>Folder containing high-resolution experimental images split by channels</li> </ul> </li> <li><em>masks </em>folder <ul> <li>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</li> </ul> </li> <li><em>thumbnails </em>folder <ul> <li>Folder containing a low-resolution RGB version of the experimental images </li> </ul> </li> </ul> <p> </p>
Data sets comparing Ca(2+) dynamics in whole-cell and β-escin-based perforated patch clamp recordings in adult mouse brain slices.
<p># Hess-et-al-beta-escin-2020<br> Data of the "Data in Brief" article concerning the added buffer approach with beta-escin perforated patch.</p> <p>A joint work by: Simon Hess (`simon.hess@uni-koeln.de`), Christophe Pouzat (`christophe.pouzat@math.unistra.fr`), and Peter Kloppenburg (`peter.kloppenburg@uni-koeln.de`).</p> <p>## Content</p> <p>This repository contains:</p> <p>- Directory `data_whole_cell` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the whole-cell configuration.<br> - Directory `data_beta_escin` contains the experimental data in [HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) format. The data contains recordings of _Substantia nigra_ dopaminergic neurons recorded in the β-escin perforated patch clamp configuration.</p>
Serial Coronal Sections Of An Adult Mouse Brain - Sample Dataset
<p>Experimental data: serial coronal sections of the brain of an adult mouse.</p> <p>20 um brain sections sampled every 80 um, imaged on an Olympus VS120 slide scanners with a 10x objective</p> <p>Contains label and overview images and 3 fluorescent channels:</p> <ul> <li>DAPI channel, cell nuclei</li> <li>FITC channel, autofluorescence</li> <li>Cy3 channel, fluorescent sparse mCherry labelled cells</li> </ul> <p>This dataset can be used as a test dataset for the <a href="https://biop.github.io/ijp-imagetoatlas/">Aligning Big Brain and Atlases</a> tool.</p> <p>Animal handling according to protocols approved by the Swiss animal license VD2808.2</p> <p>Two zipped QuPath project that are using the OMERO extension are also provided. One contains the full 97 section dataset, one contains a subset of 25 sections. These data are present in the German BioImaging public OMERO instance (<a href="https://omero-tim.gerbi-gmb.de">https://omero-tim.gerbi-gmb.de</a>).</p> <p> </p> <p> </p>
A longitudinal MRI dataset of young adult C57BL6J mouse brain
<p>This dataset contains 101 labeled young adult C57BL6J mouse brain MRI scans acquired with a 11.7T MR scanner. As part of the source domain data of Brain Extraction Net (BEN), specific analysis and usage are provided at <a href="https://github.com/yu02019/BEN">github</a> and in the <a href="https://www.biorxiv.org/content/10.1101/2022.05.25.492956v2.abstract">manuscript</a>.</p> <p>Since T2WI is the most commonly used modality for rodent brain imaging and we have accumulated extensive brain scans with high-quality annotations in our previous research studies, we first trained the model on the Mouse-T2WI-11.7T dataset, which served as the source-domain dataset, following the conventional fully supervised training strategy.</p> <p>In particular, we focus on the following features:</p> <ul> <li><strong>Transferability and flexibility</strong>: BEN can adapt to different species, modalities and platforms through its adaptive batch normalization module and semi-supervised learning module.</li> <li><strong>Automatic quality assessment</strong>: Unlike traditional toolboxes, which rely on manual inspection to assess the brain extraction quality, BEN incorporates a quality assessment module to automatically evaluate its brain extraction performance.</li> <li><strong>Speed</strong>: As a DL-based method, BEN can process an MRI volume faster (<1 second) than traditional toolboxes (several minutes or longer).</li> </ul> <p> </p>
Gene expression profile at single cell level of bone marrow and brain cells from young adult and aged mouse after chewing diet (CD) and long-term high-fat diet (HFD) feeding
GEO Series GSE217560. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Integrative multi-omic profiling of adult mouse brain endothelial cells and potential implications in Alzheimer’s disease
GEO Series GSE185642. Mus musculus. 21 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Spontaneous direct fate conversion of neuroblasts into oligodendrocytes upon demyelination in the adult mouse brain
GEO Series GSE130355. Mus musculus. 155 samples. Type: Expression profiling by high throughput sequencing.
MAPK Signaling Determines Anxiety in the Juvenile Mouse Brain but Depression-like Behavior in Adults
GEO Series GSE33618. Mus musculus. 36 samples. Type: Expression profiling by array.
A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain
GEO Series GSE116470. Mus musculus. 104 samples. Type: Expression profiling by high throughput sequencing.
Crnic Institute Human Trisome Project - Trisomy 21 Model Atlas: PolyA RNA-seq from C57BL/6 and Dp16 adult mouse brain tissue ± JAK1/2 inhibition with baricitinib
GEO Series GSE229997. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Crnic Institute Human Trisome Project - Trisomy 21 Model Atlas: PolyA RNA-seq from adult mouse brain cortex
GEO Series GSE272568. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Neurons generated by mouse ES cell with hippocampal or cortical identity display distinct projection patterns when co-transplanted in the adult brain
GEO Series GSE108466. Mus musculus. 12 samples. Type: Expression profiling by array.
High resolution analysis of genomic imprinting in the embryonic and adult mouse brain AND Sex-specific imprinting in the mouse brain
GEO Series GSE22131. Mus musculus. 32 samples. Type: Expression profiling by high throughput sequencing.
Single-cell analysis of chromatin accessibility in the adult mouse brain
GEO Series GSE246791. Mus musculus. 228 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A fluorescent perilipin 2 knock-in mouse model reveals a high abundance of lipid droplets in the developing and adult brain
GEO Series GSE267069. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Effect of chronic oxycodone self administration (SA) on gene expression in the adult male mouse brain
GEO Series GSE113948. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
Microglia-derived TGF-β1 ligand maintains microglia homeostasis via autocrine mechanism and is critical for normal cognitive function in adult mouse brain
GEO Series GSE236032. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Whole genome bisulfite and TAB-Sequencing from sorted neurons in the adult mouse brain
GEO Series GSE84506. Mus musculus. 4 samples. Type: Methylation profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.