December 06, 2006 -- David Wipf, a recent graduate of the electrical and computer engineering Ph.D. program at UC San Diegos Jacobs School of Engineering, has won a 2006 Outstanding Student Paper Award at a prestigious conference for his work on human functional brain imaging. The conference -- the 2006 Neural Information Processing Systems Conference or NIPS is being held in Vancouver this week.
"With this work, functional brain imaging practitioners should be better able to assess the relative strengths and weaknesses of competing Bayesian approaches for source localization," said David Wipf, who performed the research and wrote the paper while at UCSD.
"NIPS is a premier conference and this is quite an achievement," said Bhaskar Rao, an ECE professor at UCSDs Jacobs School and David Wipfs Ph.D. dissertation advisor.
The new work, which is largely theoretical, may also lead to improvements of existing algorithms that attempt to determine what parts of the brain are producing the electromagnetic fields that are measured by functional brain imaging techniques such as magnetoencephalography (MEG) or closely-related electroencephalography (EEG).
MEG and EEG use an array of sensors to take electromagnetic field measurements from on or near the scalp surface with excellent temporal resolution. Using this information to create accurate maps of neural activity with the highest possible spatial and temporal resolution, and relating these time-and-space activity patterns to behavioral, perceptual, cognitive and motor processes is one of the ultimate goals of human functional brain imaging. However, determining exactly what parts of the brain produce the electromagnetic fields is a difficult and unresolved issue.
Researchers often use Bayesian statistical methods and algorithms to try to determine the source, within the brain, of recorded neuroelectromagnetic fields. Trying to answer the source localization question req
Contact: Daniel Kane
University of California - San Diego