NeuroRetriever: Automatic Neuron Segmentation for Connectome Assembly.

Segmenting individual neurons from a large number of noisy raw images is the first step in building a comprehensive map of neuron-to-neuron connections for predicting information flow in the brain. Thousands of fluorescence-labeled brain neurons have been imaged. However, mapping a complete connectome remains challenging because imaged neurons are often entangled and manual segmentation of a large population of single neurons is laborious and prone to bias. In this study, we report an automatic algorithm, NeuroRetriever, for unbiased large-scale segmentation of confocal fluorescence images of single neurons in the adult Drosophila brain. NeuroRetriever uses a high-dynamic-range thresholding method to segment three-dimensional morphology of single neurons based on branch-specific structural features. Applying NeuroRetriever to automatically segment single neurons in 22,037 raw brain images, we successfully retrieved 28,125 individual neurons validated by human segmentation. Thus, automated NeuroRetriever will greatly accelerate 3D reconstruction of the single neurons for constructing the complete connectomes.

Three-dimensional multi-gene expression maps reveal cell fate changes associated with laterality reversal of zebrafish habenula.

The conserved bilateral habenular nuclei (HA) in vertebrate diencephalon develop into compartmentalized structures containing neurons derived from different cell lineages. Despite extensive studies demonstrated that zebrafish larval HA display distinct left-right (L-R) asymmetry in gene expression and connectivity, the spatial gene expression domains were mainly obtained from two-dimensional (2D) snapshots of colorimetric RNA in situ hybridization staining which could not properly reflect different HA neuronal lineages constructed in three-dimension (3D). Combing the tyramide-based fluorescent mRNA in situ hybridization, confocal microscopy and customized imaging processing procedures, we have created spatial distribution maps of four genes for 4-day-old zebrafish and in sibling fish whose L-R asymmetry was spontaneously reversed. 3D volumetric analyses showed that ratios of cpd2, lov, ron, and nrp1a expression in L-R reversed HA were reversed according to the parapineal positions. However, the quantitative changes of gene expression in reversed larval brains do not mirror the gene expression level in the obverse larval brains. There were a total 87.78% increase in lov+ nrp1a+ and a total 12.45% decrease in lov+ ron+ double-positive neurons when the L-R asymmetry of HA was reversed. Thus, our volumetric analyses of the 3D maps indicate that changes of HA neuronal cell fates are associated with the reversal of HA laterality. These changes likely account for the behavior changes associated with HA laterality alterations.

Kaleido: Visualizing Big Brain Data with Automatic Color Assignment for Single-Neuron Images.

Effective 3D visualization is essential for connectomics analysis, where the number of neural images easily reaches over tens of thousands. A formidable challenge is to simultaneously visualize a large number of distinguishable single-neuron images, with reasonable processing time and memory for file management and 3D rendering. In the present study, we proposed an algorithm named "Kaleido" that can visualize up to at least ten thousand single neurons from the Drosophila brain using only a fraction of the memory traditionally required, without increasing computing time. Adding more brain neurons increases memory only nominally. Importantly, Kaleido maximizes color contrast between neighboring neurons so that individual neurons can be easily distinguished. Colors can also be assigned to neurons based on biological relevance, such as gene expression, neurotransmitters, and/or development history. For cross-lab examination, the identity of every neuron is retrievable from the displayed image. To demonstrate the effectiveness and tractability of the method, we applied Kaleido to visualize the 10,000 Drosophila brain neurons obtained from the FlyCircuit database ( http://www.flycircuit.tw/modules.php?name=kaleido ). Thus, Kaleido visualization requires only sensible computer memory for manual examination of big connectomics data.

Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution.

BACKGROUND: Animal behavior is governed by the activity of interconnected brain circuits. Comprehensive brain wiring maps are thus needed in order to formulate hypotheses about information flow and also to guide genetic manipulations aimed at understanding how genes and circuits orchestrate complex behaviors. RESULTS: To assemble this map, we deconstructed the adult Drosophila brain into approximately 16,000 single neurons and reconstructed them into a common standardized framework to produce a virtual fly brain. We have constructed a mesoscopic map and found that it consists of 41 local processing units (LPUs), six hubs, and 58 tracts covering the whole Drosophila brain. Despite individual local variation, the architecture of the Drosophila brain shows invariance for both the aggregation of local neurons (LNs) within specific LPUs and for the connectivity of projection neurons (PNs) between the same set of LPUs. An open-access image database, named FlyCircuit, has been constructed for online data archiving, mining, analysis, and three-dimensional visualization of all single neurons, brain-wide LPUs, their wiring diagrams, and neural tracts. CONCLUSION: We found that the Drosophila brain is assembled from families of multiple LPUs and their interconnections. This provides an essential first step in the analysis of information processing within and between neurons in a complete brain.