Explorations

EBRAINS Explorations offer hands-on ways to discover EBRAINS data and tools. Each guided activity provides step-by-step instructions, taking you from quick visual exploration to more advanced analyses, with tutorials available to support every stage.

Themes

Explore neural connectivity in the mouse brain through virtual microscopy and 3D visualisation

Explore how brain regions are connected using EBRAINS’ collection of murine tract-tracing datasets. Through virtual microscopy and interactive 3D visualisation, you can examine neural pathways, investigate brain network organisation, and gain insights into the architecture of neural circuits.

Explore brain-wide cellular and receptor architecture

Discover how cells and receptors are organised across the brain using EBRAINS atlas-integrated histological datasets. These resources allow you to step inside the brain one section at a time and examine how molecular and cellular markers are distributed across regions in mouse and rat brains. Using interactive 3D rodent atlases, you can inspect histological image series, identify labeled structures, and relate spatial patterns to brain anatomy.

Explore cellular architecture of the human cortex

Explore the human cerebral cortex down to individual cells: The BigBrain model provides scans of histological sections at 1 µm resolution, integrated with cytoarchitectonic maps, a model of the cortical layers, and multimodal regional data.

Live Papers: explore the data, code and models behind published research

Go beyond the PDF. EBRAINS Live Papers are structured, interactive documents that can stand alone or sit alongside a published article and give you direct access to the data, code and models behind its figures and results. Plot a recording, manipulate a reconstructed neuron in 3D, run a simulation in your browser…then build a live paper of your own to accompany your next publication.

Dive into electrophysiology data exploration

Explore electrophysiology datasets using in-depth metadata. When searching for an appropriate dataset on EBRAINS with the aim of enriching analyses, building a computational model, training a machine learning algorithm, creating tutorials or research tools designed to link different types of neuroscience or brain-related data, finding this dataset can be challenging. A simple search offers significantly limited options. The abundance of metadata, with well-detailed information about the experimental and analysis protocol associated with the data, contributes to increased findability of suitable datasets.

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