A spatial coding scheme to define the neuron types in the Drosophila brain
Year: 2014
Type: article
Abstract: Event Abstract Back to Event A spatial coding scheme to define the neuron types in the Drosophila brain Chao-Chun Chuang1*, Chang-Wei Yeh2, Chang-Huain Hsieh2, Hsiu-Ming Chang3 and Jenn-Kang Hwang4 1 National Center for High-Performance Computing; Institute of Bioinformatics, National Chiao Tung University, Taiwan, Province China 2 National Center for High-Performance Computing, Taiwan, Province China 3 Brain Research Center, National Tsing Hua University, Taiwan, Province China 4 Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Taiwan, Province China A neuron type is an element to be manipulated for neuronal circuit analysis in the Drosophila brain. With classification and definition of neuron types, we will have a detailed look at how neurons work together. In this report, we provide a method to classify neuron types in the Drosophila brain from their spatial distributions in the brain: neurons exhibit the similar structure in the circuit belongs to the same neuron type. However, massive morphology alignment with direct 3D structural comparison is too difficult to be carried out in a high-throughput screening procedure. Thus, we developed a new approach to translate 3D neuronal morphology into the one-dimensional spatial sequence. By the alignment of the spatial sequences, we can find the neurons with similar morphology disregard their lateralization and gender differences. Finally, we have clustered 689 AL PNs in Flycircuit in to 76 neuron types and found that projection neurons with very similar morphology were formed at different developmental stages. Other cases, we found multiple genes were expressed neurons of similar morphology. In addition, sexual dimorphisms in neuron structures were detected. These results corresponded with the actual anatomy atlas, demonstrating our algorithm to be effective and accurate in a high-throughput screening procedure. In conclusion, we provide a novel approach to integrate anatomy and informatics. It can handle massive 3D neuronal image data collected in experiments from different research groups as well as manage bio-images with deeper neurological insight. Keywords: computational neuroscience, Drosophila brain, neuronal circuit analysis, 3D structural, Neuronal image Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012. Presentation Type: Poster Topic: Neuroinformatics Citation: Chuang C, Yeh C, Hsieh C, Chang H and Hwang J (2014). A spatial coding scheme to define the neuron types in the Drosophila brain. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00039 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2013; Published Online: 27 Feb 2014. * Correspondence: Dr. Chao-Chun Chuang, National Center for High-Performance Computing; Institute of Bioinformatics, National Chiao Tung University, unset, Taiwan, Province China, [email protected] Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Chao-Chun Chuang Chang-Wei Yeh Chang-Huain Hsieh Hsiu-Ming Chang Jenn-Kang Hwang Google Chao-Chun Chuang Chang-Wei Yeh Chang-Huain Hsieh Hsiu-Ming Chang Jenn-Kang Hwang Google Scholar Chao-Chun Chuang Chang-Wei Yeh Chang-Huain Hsieh Hsiu-Ming Chang Jenn-Kang Hwang PubMed Chao-Chun Chuang Chang-Wei Yeh Chang-Huain Hsieh Hsiu-Ming Chang Jenn-Kang Hwang Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.
Source: Frontiers in Neuroinformatics
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W2320120293