Davi Bock
Speaker of Workshop 2
Will talk about: Toward relating wiring diagrams to receptive fields: electron microscopy of calcium-imaged neurons in mouse visual cortex
Davi Bock is currently a graduate student in the Program in Neuroscience at Harvard Medical School. This fall, he will take a Fellow position at Janelia Farm, the Howard Hughes Medical Institute's research campus. In his graduate work, he spearheaded the development of a high throughput Transmission Electron Microscope Camera Array (TEMCA) for the acquisition of serial ultrathin (<50 nm) sections of brain tissue. He also developed a method for relocating neurons at the EM level whose in vivo physiology had previously been characterized using 2-photon calcium imaging. By combining these two methods, many-to-many connectivity of functionally characterized cells in mouse visual cortex can be obtained and principles of circuit structure extracted. In order to achieve this goal, tools and workflow for segmenting, annotating, and sharing multi-terabyte EM image volumes must be developed and deployed. This is a major focus of Davi's current work.
Our purpose is to combine anatomy and physiology to better understand the operation of neural circuits. We recorded the responses of a cluster of cells in mouse primary visual cortex during presentation of drifting gratings of varying orientation, using in vivo 2-photon calcium imaging. We relocated the physiologically characterized cells at the electron microscopy (EM) level and imaged a 1200 section series of ultrathin (~45 nm) sections using a custom high speed transmission electron microscopy camera array (TEMCA). The imaged field of view per section was ~430 x 300 micron, with a pixel size of ~3.75 nm, resulting in a ~115,000 x 80,000 pixel composite image per section and a ~ 10 TB net image stack. This scale and resolution is sufficient to begin extracting the anatomical connectivity of groups of functionally characterized neurons at the level of individual synapses.
I will present this work, discuss the many data handling issues we have run into along the way, and present a road map for future increases in scale.
