@article {47599, title = {A large fraction of neocortical myelin ensheathes axons of local inhibitory neurons.}, journal = {eLife}, year = {2016}, month = {2016 Jul 6}, abstract = {

Myelin is best known for its role in increasing the conduction velocity and metabolic efficiency of long-range excitatory axons. Accordingly, the myelin observed in neocortical gray matter is thought to mostly ensheath excitatory axons connecting to subcortical regions and distant cortical areas. Using independent analyses of light and electron microscopy data from mouse neocortex, we show that a surprisingly large fraction of cortical myelin (half the myelin in layer 2/3 and a quarter in layer 4) ensheathes axons of inhibitory neurons, specifically of parvalbumin-positive basket cells. This myelin differs significantly from that of excitatory axons in distribution and protein composition. Myelin on inhibitory axons is unlikely to meaningfully hasten the arrival of spikes at their pre-synaptic terminals, due to the patchy distribution and short path-lengths observed. Our results thus highlight the need for exploring alternative roles for myelin in neocortical circuits.

}, doi = {10.7554/eLife.15784}, author = {Micheva, Kristina D and Wolman, Dylan and Mensh, Brett D and Pax, Elizabeth and Buchanan, JoAnn and Smith, Stephen J and Bock, Davi D} } @article {6904, title = {The Open Connectome Project Data Cluster: Scalable analysis and vision for high-throughput neuroscience.}, journal = {Scientific and Statistical Database Management: International Conference, SSDBM ... : Proceedings. International Conference on Scientific and Statistical Database Management}, year = {2013}, month = {2013 Jun 18}, abstract = {

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

}, doi = {10.1145/2484838.2484870}, author = {Burns, Randal and Roncal, William Gray and Kleissas, Dean and Lillaney, Kunal and Manavalan, Priya and Perlman, Eric and Berger, Daniel R. and Bock, Davi D and Chung, Kwanghun and Grosenick, Logan and Kasthuri, Narayanan and Weiler, Nicholas C and Deisseroth, Karl and Kazhdan, Michael and Lichtman, Jeff and Reid, R Clay and Smith, Stephen J and Szalay, Alexander S and Vogelstein, Joshua T and Vogelstein, R Jacob} } @article {4326, title = {Large-scale automated histology in the pursuit of connectomes.}, journal = {The Journal of Neuroscience: The Official Journal of the Society for Neuroscience}, volume = {31}, year = {2011}, month = {2011 Nov 9}, pages = {16125-38}, abstract = {

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain{\textquoteright}s computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.4077-11.2011}, author = {Kleinfeld, David and Bharioke, Arjun and Blinder, Pablo and Bock, Davi D and Briggman, Kevin L and Chklovskii, Dmitri B and Denk, Winfried and Helmstaedter, Moritz and Kaufhold, John P and Lee, Wei-Chung Allen and Meyer, Hanno S and Micheva, Kristina D and Oberlaender, Marcel and Prohaska, Steffen and Reid, R Clay and Smith, Stephen J and Takemura, Shinya and Tsai, Philbert S and Sakmann, Bert} }