The last decade has seen a dramatic increase in the size, complexity, and availability of fruit fly brain data. This has included large-scale neuroanatomical, genetic, and electrophysiological data. However, there has been a lack of computational tools capable of bridging these data modalities at the scale and speed required to investigate the functional logic underpinning fruit fly brain circuitry. To facilitate the required data integration to accomplish this feat, Aurel Lazar and colleagues at Columbia University have developed FlyBrainLab, an interactive software for visualizing and uncovering the function of circuits created from large-scale fruit fly brain data.
FlyBrainLab is designed to provide 3D visualization and exploration of data as well as the creation of executable circuits from that data and interactive investigation of the logic within those circuits. The FlyBrainLab website provides installation instructions, extensive documentation and tutorials, publically available datasets, and troubleshooting. The FlyBrainLab paper compliments these materials with six cases presenting the types of data visualization and analysis that the tool is capable of that may be of particular interest. Thus, FlyBrainLab is an environment where researchers are able visualize, execute, and interactively investigate neural circuits thereby accelerating the discovery of functional logic in the Drosophila brain.
This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. RRID:SCR_022337
Get access to necessary files and code for installing FlyBrainLab from their GitHub repository!
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