@article {46226,
	title = {Annotating synapses in large EM datasets.},
	journal = {arXiv},
	year = {2014},
	month = {2014 Sep 5},
	pages = {arXiv:1409.1801 [q-bio.QM]},
	abstract = {<p>Reconstructing neuronal circuits at the level of synapses is a central problem in neuroscience and becoming a focus of the emerging field of connectomics. To date, electron microscopy (EM) is the most proven technique for identifying and quantifying synaptic connections. As advances in EM make acquiring larger datasets possible, subsequent manual synapse identification ({\em i.e.}, proofreading) for deciphering a connectome becomes a major time bottleneck. Here we introduce a large-scale, high-throughput, and semi-automated methodology to efficiently identify synapses. We successfully applied our methodology to the Drosophila medulla optic lobe, annotating many more synapses than previous connectome efforts. Our approaches are extensible and will make the often complicated process of synapse identification accessible to a wider-community of potential proofreaders.</p>
},
	url = {http://arxiv.org/abs/1409.1801},
	author = {Plaza, Stephen M and Parag, Toufiq and Huang, Gary and Olbris, Donald J. and Saunders, Mathew A. and Rivlin, Patricia K.}
}
@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 = {<p>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.</p>
},
	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}
}
