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Web interface for large scale neural circuitreconstruction processes for connectomics

R. Clay Reid, Jeff Lichtman, Wei-Chung Allen Lee Harvard Medical School, Allen Institute for Brain Science

Center for Brain Science, Harvard UniversityDavi Bock

HMMI Janelia Farm David Hall and Scott Emmons

Albert Einstein College of Medicine

Art Wetzel - Pittsburgh Supercomputing CenterNational Resource for Biomedical Supercomputing

awetzel@psc.edu 412-268-3912www.psc.edu and www.nrbsc.org

Aug 30, 2012 Comp Sci Connectomics Data Project Overview

Source data from …

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What is Connectomics?“an emerging field defined by high-throughput generation of data about neural connectivity, and subsequent mining of that data for knowledge about the brain. A connectome is a summary of the structure of a neural network, an annotated list of all synaptic connections between the neurons inside a brain or brain region.”

DTI “tractography” Human Connectome Project at MRI 2 mm resolution

“Brainbow” stained neuropil at 300 nm optical resolution

Serial section electron microscopy reconstruction at 3-4 nm resolution

~10 MB/volume ~10 GB/mm3 ~1 PB/mm3

1.3x106 mm3

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Reconstructing brain circuits requires high resolution electron microscopy over “long” distances == BIGDATA

Recent ICs have 32nm features 22nm chips are being delivered.

A synaptic junction>500 nm wide withcleft gap ~20 nm

Vesicles ~30 nm diam.

Dendritic spine www.coolschool.ca/lor/BI12/unit12/U12L04.htm

Dendrite Gate oxide 1.2nm thick

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Current data from a 400 micron cube is greater than 100 TBs (.1 PB)

A full mouse brain would be an exabyte == 1000 PB

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Rigid alignment does not permit visualization of 3D structures

Data courtesy of Richard Fetter (UCSF)

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Non-rigid deformable registration produces useful out of plane views

Data courtesy of Richard Fetter (UCSF)

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C&S P10: Advancing high-throughput thin-section scanning EM to study relationships between neuronal circuit structure and function.

Jeff Lichtman’s team at Harvard is developing improved methods for sample handling and very high speed scanning electronMicroscopy to enable studies of large regions of brain tissue from individual specimens. We have worked closely withLichtman’s team as they have captured a leading edge dataset with a tissue volume of 400x400x300 microns. The resulting100 TByte image set is being registered as a test case of our new Signal Whitening Fourier Transform alignment method. The left image above shows an aligned and partially segmented view of a low resolution prescan of the entire 1mm wide 10,000 section specimen. This was used to select a region of interest for high resolution imaging at 4nm/pixel. The right image is a greatly reduced, ~1/200th scale, overview through the 100 TB high resolution dataset showing the smoothness and consistency of the capillary network as viewed and segmented using our PSC Volume Browser. We are continuing the full resolution alignment that is needed prior to the detailed circuit tracing of connections between the ~30,000 neurons within the ROI. Due to the very large storage requirements this dataset will also be the first large scale test of our Virtual Volume FileSystem mechanism to provide aligned views rendered on demand from original data without requiring duplicate data storage. Our methods for large scale registration and data handling will be increasingly important as Lichtman’s team installs a new parallel beam SEM that will produce 1 Gbyte/sec within the next year.

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The CS project is build a web based UI tosubmit, monitor, steer and evaluate compute tasks for EM based reconstructions.

We already have command based programs to do the processing on PSC compute cluster and storage facilities.

Biologists who capture the raw data at distant sites need a friendly and portable interface to transfer datasets, enter notes, automatically initiate compute jobs, track progress, etc.

We will provide PSC computing accounts and office space to work with PSC staff and other students working on different aspects of our connectomics projects.

You will gain experience with large scale data handling and computer operations at a major supercomputing site.

Valuable background includes web development skills, basic computer graphics, a multidisciplinary approach to problem solving and an interest in computational biology.