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MeshView user manual

MeshView is one of several tools developed by the Human Brain Project (HBP) with the aim of facilitating brain atlas based analysis and integration of experimental data and knowledge about the human and rodent brain.

Brain atlases

LocaliZoom user manual

EBRAINS LocaliZoom serial section image viewer provides an intuitive way of navigating high-resolution 2D image series coupled with segmentation overlay, from a web browser.

Brain atlases

QuickNII user manual

QuickNII is one of several tools developed by the Human Brain Project (HBP) with the aim of facilitating brain atlas-based analysis and integration of experimental data and knowledge about the human and rodent brain.

Brain atlases

VisuAlign user manual

VisuAlign is one of several tools developed by the Human Brain Project (HBP) with the aim of facilitating brain atlas based analysis and integration of experimental data and knowledge about the human and rodent brain.

Brain atlases

QCAlign user manual

QCAlign was developed to support the use of the QUINT workflow for high-throughput studies

Brain atlases

WebAlign user manual

WebAlign is an online tool for spatial registration of histological section images from rodent brains to reference 3D atlases.

Brain atlases

WebWarp user manual

WebWarp is an online tool for nonlinear refinement of spatial registration of histological section images from rodent brains to reference 3D atlases.

Brain atlases

WHS rat brain atlas v4 (Kleven et al., 2023)

Volumetric brain atlases are increasingly used to integrate and analyse diverse experimental neuroscience data acquired from animal models, but until recently a publicly available digital atlas with complete coverage of the rat brain has been missing. Here we present the new Waxholm Space rat brain atlas, a comprehensive open-access volumetric atlas resource.

Brain atlases

WHS rat brain atlas v3 (Osen et al., 2019)

The mammalian auditory system comprises a complex network of brain regions. Interpretations and comparisons of experimental results from this system depend on appropriate anatomical identification of auditory structures.

Brain atlases

WHS rat brain atlas v2 (Kjonigsen et al., 2015)

Atlases of the rat brain are widely used as reference for orientation, planning of experiments, and as tools for assigning location to experimental data. Improved quality and use of magnetic resonance imaging (MRI) and other tomographical imaging techniques in rats have allowed the development of new three-dimensional (3-D) volumetric brain atlas templates.

Brain atlases

WHS rat brain atlas v1.01 (Papp et al., 2015)

The main focus of our original article was to describe the anatomical delineations constituting the first version of the WHS Sprague Dawley atlas, apply the Waxholm Space coordinate system, and publish the associated MRI/DTI template and segmentation volume in their original format. To increase usability of the dataset, we have recently shared an updated version of the volumetric image material (v1.01). The aims of this addendum are to inform about the improvements in the updated dataset, in particular related to navigation in the WHS coordinate system, and provide guidance for transforming coordinates acquired in the first version of the atlas.

Brain atlases

WHS rat brain atlas v1 (Papp et al., 2014)

Three-dimensional digital brain atlases represent an important new generation of neuroinformatics tools for understanding complex brain anatomy, assigning location to experimental data, and planning of experiments. We have acquired a microscopic resolution isotropic MRI and DTI atlasing template for the Sprague Dawley rat brain with 39 μm isotropic voxels for the MRI volume and 78 μm isotropic voxels for the DTI.

Brain atlases

Data Curation Collab

The aim of this collab is to provide you with all the information you need to publish your neuroscience data via the EBRAINS Knowledge Graph.

Data

Building and simulating a simple model using PyNN

In this tutorial, you will learn how to build a simple network of integrate-and-fire neurons using PyNN, how to run simulation experiments with this network using different simulators, and how to visualize the data generated by these experiments.

Modelling and simulation

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