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Elucidation of principle of neural circuits using small circuits

開催日 2014/9/12
時間 17:10 - 19:10
会場 Room F(302)
Chairperson(s) 上川内 あづさ / Azusa Kamikouchi (名古屋大学大学院理学研究科 生命理学専攻 / Graduate School of Sciene, Nagoya University, Japan)
森 郁恵 / Ikue Mori (名古屋大学大学院理学研究科 / Graduate School of Sciene, Nagoya University, Japan)

Brain wide connectomics analysis of using Drosophila as a model

  • S2-F-3-3
  • 伊藤 啓 / Kei Ito:1 谷村 純 / Jun Tanimura: ムルタン クロエ / Chloe Murtin: 伊藤 正芳 / Masayoshi Ito: 
  • 1:東京大院分生研 / Institute of Molecular and Cellular Biosciences, University of Tokyo, Japan 

Thorough understanding of neural networks is a prerequisite to analyze how information is processed in the brain. For this one has to understand the connectivity between the computational units of the brain, the neurons. Magnetic resonance imaging (MRI) cannot resolve single neurons, and it is hard to trace the entire neural projections of a neuron using electron microscopy (EM). High-resolution light microscopy is therefore the most efficient way to analyze neural networks. To resolve neural projections, only a small subset of neurons should be visualized at one time. However, this makes it impossible to trace connections between neurons. To address this problem, we visualize not only neuronal fibers of selective neurons but also distributions of their input (post) and output (pre) synaptic sites by driving the expression of multiple proteins: a membrane-bound tag and the tags fused with the proteins associated with transmitter receptors and synaptic vesicles. In addition, gross synaptic density of the brain is labeled using an antibody. Because the latter signal is common across samples, images of different neurons that are obtained from different brains can be spatially matched (or registered) to a standard brain template by comparing its signal density distribution. Co-localization between the output synaptic sites of one neuron type and the input synaptic sites of another neuron type is a prerequisite, albeit not the proof, of their synaptic contacts. Using sophisticated expression driver systems of Drosophila, we obtain an array of 3- or 4-channel, very high-resolution, three-dimensionally matched confocal image datasets of diverse neurons to estimate possible connections between different neurons and between different regions of the brain.

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