Browsing by Author "Wang, Guo-Tzau"

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Kaleido: Visualizing Big Brain Data with Automatic Color Assignment for Single-Neuron Images
(2018-04-01)
Wang, Ting-Yuan
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Chen, Nan-Yow
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He, Guan-Wei
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Wang, Guo-Tzau
;
Shih, Chi-Tin
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 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
(2011-01-11)
Chiang, Ann-Shyn
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Lin, Chih-Yung
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Chuang, Chao-Chun
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Chang, Hsiu-Ming
;
Hsieh, Chang-Huain
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.