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35 Publications

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    12/01/11 | Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain.
    Rivera-Alba M, Vitaladevuni SN, Mischenko Y, Lu Z, Takemura S, Scheffer L, Meinertzhagen I, Chklovskii D, Polavieja G
    Current Biology. 2011 Dec;21(23):2000-5. doi: 10.1016/j.cub.2011.10.022

    Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement.

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    01/01/11 | High resolution segmentation of neuronal tissues from low depth-resolution EM imagery.
    Glasner D, Hu T, Nunez-Iglesias J, Scheffer L, Xu C, Hess H, Fetter R, Chklovskii D, Basri R
    8th International Conference of Energy Minimization Methods in Computer Vision and Pattern Recognition Energy Minimization Methods in Computer Vision and Pattern Recognition. 2011;6819:261-72

    The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack of EM images into the individual neurons is difficult, due to the low depth-resolution in existing high-throughput EM technology, such as serial section Transmission EM (ssTEM). In this paper we propose methods for detecting the high resolution locations of membranes from low depth-resolution images. We approach this problem using both a method that learns a discriminative, over-complete dictionary and a kernel SVM. We test this approach on tomographic sections produced in simulations from high resolution Focused Ion Beam (FIB) images and on low depth-resolution images acquired with ssTEM and evaluate our results by comparing it to manual labeling of this data.

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    10/01/10 | Semi-automated reconstruction of neural circuits using electron microscopy.
    Chklovskii DB, Vitaladevuni S, Scheffer LK
    Current Opinion in Neurobiology. 2010 Oct;20:667-75. doi: 10.1371/journal.pcbi.1001066

    Reconstructing neuronal circuits at the level of synapses is a central problem in neuroscience, and the focus of the nascent field of connectomics. Previously used to reconstruct the C. elegans wiring diagram, serial-section transmission electron microscopy (ssTEM) is a proven technique for the task. However, to reconstruct more complex circuits, ssTEM will require the automation of image processing. We review progress in the processing of electron microscopy images and, in particular, a semi-automated reconstruction pipeline deployed at Janelia. Drosophila circuits underlying identified behaviors are being reconstructed in the pipeline with the goal of generating a complete Drosophila connectome.

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    01/01/10 | Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction.
    Veeraraghavan A, Genkin AV, Vitaladevuni S, Scheffer L, Xu C, Hess H, Fetter R, Cantoni M, Knott G, Chklovskii DB
    Computer Vision and Pattern Recognition (CVPR). 2010:1767-74. doi: 10.1109/CVPR.2010.5539846
    01/01/10 | Serial-section EM derived synaptic circuits in the fly’s visual system: the medulla opens up.
    Meinertzhagen IA, Takemura S, Vitaladevuni S, Lu Z, Scheffer L, Chklovskii D
    Journal of Neurogenetics. 2010;24:9