Automatic segmentation of Drosophila neural compartments using GAL4 expression data reveals novel visual pathways

Abstract We made use of two recent, large-scale Drosophila GAL4 libraries and associated confocal imaging datasets to automatically segment large brain regions into smaller putative functional units such as neuropils and fiber tracts. The method we developed is based on the hypothesis that molecular identity can be used to assign individual voxels to biologically meaningful regions. Our results (available at https://strawlab.org/braincode) are consistent with this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. We then applied the algorithm to the central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 10 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates.