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Workstations for advanced 3-D reconstructions

Workstations for advanced 3-D reconstructions
用于高级 3D 重建的工作站
批准号:
389673-2010
负责人:
Meinertzhagen, Ian
金额:
$2.07万
依托单位:
依托单位国家:
加拿大
项目类别:
Research Tools and Instruments - Category 1 (<$150,000)
财政年份:
2009
资助国家:
加拿大
项目状态:
已结题
起止时间:
2009-01-01 至 2010-12-31

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中文摘要
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英文摘要
My NSERC program investigates simple systems of nerve cells in model species of invertebrates. I increasingly use my Discovery grant to generate three-dimensional reconstructions from serial-section electron micrographs (EMs) of identified nerve cells. Currently I am investigating the olfactory system of the fruit fly Drosophila melanogaster, and the central nervous system of the tadpole larva of the common sea squirt, Ciona intestinalis. My lab is world expert in these approaches, and we progressively analyse the synaptic circuits of different brain regions, as part of an endeavour to understand the neural basis of behaviour. I have extended this work as part of a recent appointment as a visiting scientist at the Janelia Farm campus of the Howard Hughes Medical Institute near Washington, DC, for 2 months a year. There, I work in collaboration with computer scientists who have generated methods to speed such work considerably, using algorithmic advances to reconstruct semi-automatically the three-dimensional forms of neurons from their consecutive two-dimensional images in EMs. This is part of Janelia Farm's vision to generate by automatic means a complete wiring diagram of the Drosophila brain. I plan to use the software developments at Janelia Farm to enrich and accelerate my NSERC program at Dalhousie, but need workstations to run their software on our datasets. The datasets themselves are huge, more than 1 terabyte, and require workstations with huge memory, processing speed and storage. I propose to purchase two such advanced workstations, each complete with a large, high-resolution flat screen monitors and 2TB hard drive, to mirror the 3-D reconstruction capabilities available at Janelia Farm. These will be used mainly by HQP working on such datasets for graduate or postdoctoral research, assisted by undergraduate helpers.
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