@article {6676, title = {Electron microscopy reconstruction of brain structure using sparse representations over learned dictionaries.}, journal = {IEEE Transactions on Medical Imaging}, volume = {32}, year = {2013}, month = {2013 Aug 2}, pages = {2179-88}, abstract = {

A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically 5) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.

}, issn = {1558-254X}, doi = {10.1109/TMI.2013.2276018}, author = {Hu, Tao and Nunez-Iglesias, Juan and Vitaladevuni, Shiv and Scheffer, Lou and Xu, Shan and Bolorizadeh, Mehdi and Hess, Harald and Fetter, Richard and Chklovskii, Dmitri} } @article {6178, title = {A visual motion detection circuit suggested by Drosophila connectomics.}, journal = {Nature}, volume = {500}, year = {2013}, month = {2013 Aug 7}, pages = {175{\textendash}81}, abstract = {

Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here we develop a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

}, issn = {1476-4687}, doi = {doi:10.1038/nature12450}, url = {http://www.nature.com/nature/journal/v500/n7461/full/nature12450.html}, author = {Takemura, Shin-ya and Bharioke, Arjun and Lu, Zhiyuan and Nern, Aljoscha and Vitaladevuni, Shiv and Rivlin, Patricia K. and Katz, William T. and Olbris, Donald J. and Plaza, Stephen M and Winston, Philip and Zhao, Ting and Horne, Jane Anne and Fetter, Richard D and Takemura, Satoko and Blazek, Katerina and Chang, Lei-Ann and Ogundeyi, Omotara and Saunders, Mathew A. and Shapiro, Victor and Sigmund, Christopher and Rubin, Gerald M and Scheffer, Louis K and Meinertzhagen, Ian A. and Chklovskii, Dmitri B} } @article {1245, title = {Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction.}, journal = {Computer Vision and Pattern Recognition (CVPR)}, year = {2010}, month = {2010}, pages = {1767-74}, issn = {1063-6919}, doi = {10.1109/CVPR.2010.5539846}, author = {Veeraraghavan, Ashok and Genkin, Alex V and Vitaladevuni, Shiv and Scheffer, Lou and Xu, CShan and Hess, Harald and Fetter, Richard and Cantoni, Marco and Knott, Graham and Chklovskii, Dmitri B} } @article {1234, title = {Semi-automated reconstruction of neural circuits using electron microscopy.}, journal = {Current Opinion in Neurobiology}, volume = {20}, year = {2010}, month = {2010 Oct}, pages = {667-75}, abstract = {

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.

}, issn = {1873-6882}, doi = {10.1371/journal.pcbi.1001066}, author = {Chklovskii, Dmitri B and Vitaladevuni, Shiv and Scheffer, Louis K} }