NSF East Asia and Pacific Summer Institute (EAPSI) for FY 2013 in Korea

Hildebrand David, Boston MA

Investigators

Abstract

This action funds David Grant Colburn Hildebrand of Harvard University to conduct a research project in Biological Sciences during the summer of 2013 at Ulsan National Institute of Science and Technology in Ulsan, Korea. The project title is "Automatically Finding the Same Neurons in Optical and Electron Microscopy Datasets to Enable Investigations of the Relationship Between Structure and Function in the brain." The host scientist is Won-Ki Jeong, Ph.D. Determining how the connectivity of neuronal circuits influences their functional properties is one of the most difficult endeavors the field of neuroscience has ever faced. This is due to the fact that these studies require untangling and making sense of dense hairballs of dendrites and axons known as neuropil. While we now have methods to create neuronal connectivity maps, few experimental techniques and software tools for linking studies of neuron functional properties to those of neuronal circuit connectivity exist. This project creates software that resolves this problem after interrogating which computational algorithms are best suited to identifying, localizing, and corresponding the same neurons in optical and electron microscopy datasets, which provide information about neuron function and circuit structure, respectively. Broader impacts of an EAPSI fellowship include providing the Fellow a first-hand research experience outside the U.S.; an introduction to the science, science policy, and scientific infrastructure of the respective location; and an orientation to the society, culture and language. These activities meet the NSF goal to educate for international collaborations early in the career of its scientists, engineers, and educators, thus ensuring a globally aware U.S. scientific workforce. Furthermore, this project will generate open-source software tools that make it possible for others in the field to perform similar studies and for teachers to bring together students interested in life sciences and computer science. Small example datasets will be made available with the software tools for teachers and self-learners to illustrate to students how relatively simple "connect-the-dots" relationships in the brain can carry important implications for biological function.