Spatial mapping of multimodal data in neuroscience
Friday, 15 April, 10:00am-10:50am
Abstract
Spatial mapping of multimodal data in neuroscience employs techniques that are essential for the construction of digital atlases of the brain. Such atlases are increasingly used in the study of both humans and model organisms and enable scientists to access and analyze data in novel and meaningful ways. A broad spectrum of neuroinformatics methods from data mapping, analysis, and visualization are employed in the development of effective digital atlases. The challenges of atlas development and more general common coordinate frameworks include accurate image registration and quantification. Surmounting these issues for multimodal data are key to providing powerful interoperable environments that enable meaningful data sharing and inquiry. By highlighting some of the resulting analyses, we review the methods used in the development of the suite of atlas tools developed as part of Allen Institute for Brain Science resources.
Biography
Mike Hawrylycz joined the Allen Institute for Brain Science in 2003. He is responsible for the direction of the Modeling, Analysis, and Theory groups at the Institute. He has worked in a variety of applied mathematics and computer science areas, such as consumer and investment finance, electrical engineering and image processing, and computational biology and genomics. Hawrylycz received his Ph.D. in applied mathematics at the Massachusetts Institute of Technology and subsequently was a post-doctoral researcher in the Center for Nonlinear Studies at the Los Alamos National Laboratory.
Other plenary speakers
| Gene MYERS | Milan ŠONKA | K. Kirk SHUNG | ||
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