"Scalable Neuroscience and the Brain Activity Mapping Project"
-- Tom Dean, Google
Abstract
Two major initiatives to accelerate research in the brain sciences have focused attention on developing a new generation of scientific instruments for neuroscience. These instruments will be used to record static (structural) and dynamic (behavioral) information at unprecedented spatial and temporal resolution and report out that information in a form suitable for computational analysis.
The technical challenge involved in building these instruments is considerable, perhaps on a par with constructing the Large Hadron Collider (LHC), but while the LHC accelerator ring is 27 km in circumference, the components composing BAM instruments might include billions of nanoscale parts and be contained entirely within a human skull.
We distinguish between recording — taking measurements of individual cells and the extracellular matrix — and reporting — transcoding, packaging and transmitting the resulting information for subsequent analysis — as these represent very different challenges as we scale the relevant technologies to support simultaneously tracking the many neurons that compose neural circuits of interest.
This lecture explores several of the key technologies being considered to address the reporting problem including nanoscale communication networks, micron-diameter fiber-optic cables, light and ultrasound microscopy, recombinant DNA and synthetic biology, categorizing their impact in terms of short-term [one to two years], medium-term [two to five years] and longer-term [five to 10 years] deliverables.
Biography
Dean is a full-time research scientist at Google in Mountain View. From 1993 to 2007, he was a professor of computer science and cognitive and linguistic sciences at Brown University. He still considers Brown his academic home and remains associated with the university through his adjunct professor position in computer science.
He received his bachelor's in mathematics from Virginia Polytechnic Institute & State University in 1982, and his master's and Ph.D. in computer science from Yale University in 1984 and 1986 respectively. His research interests include automated planning and control, computational biology, machine learning, neural modeling, probabilistic inference, robotics and spatial and temporal reasoning.
Dean was named a fellow of AAAI in 1994 and an ACM fellow in 2009. He served as the deputy provost of Brown University from 2003 to 2005; as the chair of Brown's Computer Science Department from 1997 until 2002; and as the acting vice president for Computing and Information Services from 2001 until 2002. He helped found the Academic Alliance of the National Center for Women and Information Technology, and a former member of the IJCAI Inc. Board of Trustees. He has served on the Executive Council of AAAI and the Computing Research Association Board of Directors.
He received an NSF Presidential Young Investigator Award in 1989, served as program co-chair for the 1991 National Conference on Artificial Intelligence and the program chair for the 1999 International Joint Conference on Artificial Intelligence held in Stockholm.
Dean is co-author, with Mike Wellman, of the Morgan-Kaufmann text entitled "Planning and Control," which ties together techniques from artificial intelligence, operations research, control theory and the decision sciences. He is co-author, with James Allen and John Aloimonos, of "Artificial Intelligence: Theory and Practice," an introductory text in artificial intelligence. His latest book, "Talking With Computers," is published by Cambridge University Press and examines a wide range of topics from digital logic and machine language to artificial intelligence and searching the Web.
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