CONNECTOME PROJECT DATA MANAGEMENT AND IMAGE ASSEMBLY WITH CLAY REID

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The goal of this project is to acquire, assemble, and analyze images of brain circuitry in experimental animals with the aim of understanding the structure and function of neural circuits. Our initial work is to align the largest possible serial section transmission electron microscopy (TEM) image sets produced by Harvard's semi-automated TEM capture system. These data are being used to study the operation of circuits in the mouse visual cortex and are co-registered with in-vivo calcium images of the same specimen while exposed to various visual stimuli. The current Harvard instrument, operating at ~20 Mpixels/sec, captures mosaic image sets of 50nm thick rectangular sections up to 1200 by 750 microns at 4 nm in-plane resolution in less than an hour each. These data consist of thousands of camera frames, ~10 Mpixels each, that must be aligned in 2D to produce full planar images up to 56 GBytes. The planes must then be aligned in 3D to produce registered volumetric data that can be analyzed much more easily than individual planes or camera frames. The first two datasets, currently being aquired over a period of ~6 months, are larger than 10 TBytes each. Methods developed at this stage will be applied to even larger datasets produced by a faster next generation capture system to be built during the next 2 years. The resulting PetaByte data will cover volumes up to 1mm3 which are sufficient to contain an entire cortical column extending from the brain surface into the white matter.