A Ph.D. student working with ISI's Greg Ver Steeg, Daniel Moyer, won a Young Scientist award at the October, 2016 Medical Image Computing and Computer Assisted Intervention Society (MICCAI) conference in Athens.
The paper, A Continuous Model of Cortical Connectivity, constructs a new model for brain connectivity that aims to assist neuroscientists in diagnosing brain diseases and treatment effects.
Moyer's paper was one of five recognized as outstanding Ph.D. and post-doctoral student work by MICCAI, whose members pursue interdisciplinary research and practice in robotics, biomedical imaging and other medical-image computing and computer-assisted medical interventions.
"This is one of the rare cases where 'interdisciplinary' is not just a buzz word but a really fitting adjective," says Aram Galstyan, the team's research director. "Daniel is developing state-of-the-art tools for machine learning and network modeling, and is working with domain experts to apply those models to concrete neuroscience problems."
Echoes MICCAI's mission statement, "The multidisciplinary nature of these emerging fields brings together clinicians, bioscientists, computer scientists, engineers, physicists, and other researchers who are contributing to, and need to keep abreast of, advances in the methodology and applications."
Work was conducted jointly with the Imaging Genetics Center, a team of physicians, engineers, computer scientists and neuroscientists housed at the USC Mark and Mary Stevens Neuroimaging and Informatics Institute in ISI's Marina del Rey, Calif. headquarters.
In essence, brain connectivity usually is modelled as a network. Moyer instead chose a continuous representation of connectivity similar to a graph limit, or graphon, that more closely resembles the structure of the brain. Such work ultimately may benefit neurology tools, models and results.
Moyer has worked with Ver Steeg for about 18 months. Ver Steeg and Paul Thompson of USC's computer science department serve as Moyer's co-advisors.