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The Brain Image Library: A Community-Contributed Microscopy Resource for Neuroscientists.


ABSTRACT: Advancements in microscopy techniques and computing technologies have enabled researchers to digitally reconstruct brains at micron scale. As a result, community efforts like the BRAIN Initiative Cell Census Network (BICCN) have generated thousands of whole-brain imaging datasets to trace neuronal circuitry and comprehensively map cell types. This data holds valuable information that extends beyond initial analyses, opening avenues for variation studies and robust classification of cell types in specific brain regions. However, the size and heterogeneity of these imaging data have historically made storage, sharing, and analysis difficult for individual investigators and impractical on a broad community scale. Here, we introduce the Brain Image Library (BIL), a public resource serving the neuroscience community that provides a persistent centralized repository for brain microscopy data. BIL currently holds thousands of brain datasets and provides an integrated analysis ecosystem, allowing for exploration, visualization, and data access without the need to download, thus encouraging scientific discovery and data reuse.

SUBMITTER: Kenney M 

PROVIDER: S-EPMC10769375 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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The Brain Image Library: A Community-Contributed Microscopy Resource for Neuroscientists.

Kenney Mariah M   Vasylieva Iaroslavna I   Hood Greg G   Cao-Berg Ivan I   Tuite Luke L   Laghaei Rozita R   Smith Megan C MC   Watson Alan M AM   Ropelewski Alexander J AJ  

bioRxiv : the preprint server for biology 20240508


Advancements in microscopy techniques and computing technologies have enabled researchers to digitally reconstruct brains at micron scale. As a result, community efforts like the BRAIN Initiative Cell Census Network (BICCN) have generated thousands of whole-brain imaging datasets to trace neuronal circuitry and comprehensively map cell types. This data holds valuable information that extends beyond initial analyses, opening avenues for variation studies and robust classification of cell types in  ...[more]

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