siibra is a toolsuite which connects neuroscience data from different modalities and resources to anatomical structures defined in brain parcellation maps, and links reference coordinates spaces at macroscopic and microscopic resolution into a common informatics framework. It enables anatomical characterization and multimodal profiling of various forms of regions of interest in the brain. The number of connected data resources is constantly growing, and includes measures of cellular and molecular architecture, parcellation-based connectivity, and microscopy image resources hosted on cloud resources. siibraLab is a toolbox for accessing data and functionalities offered by siibra conveniently from Matlab®.
siibra provides structured acccess to parcellation schemes in different brain reference spaces, including volumetric reference templates at both macroscopic and microscopic resolutions as well as surface representations. It supports both discretely labelled and continuous (probabilistic) parcellation maps, which can be used to assign brain regions to spatial locations and image signals, to retrieve region-specific neuroscience datasets from multiple online repositories, and to sample information from high-resolution image data. Among the datasets anchored to brain regions are many different modalities from in-vivo and post mortem studies, including regional information about cell and transmitter receptor densties, structural and functional connectivity, gene expressions, and more.
Tip
We recommend checking out our walkthrough tutorial, it's only one click away:
The toolbox is under active developmemt. We publish releases on matlab file exchange. To understand the concepts, it is also useful to skim through the siibra-python documentation and to have a look at the interactove 3D viewer siibra-explorer, which is hosted on EBRAINS. If you want to get in touch regarding future developments, drop us a note.