Nonparametric hierarchical Bayesian model for functional brain parcellation

Nonparametric hierarchical Bayesian model for functional brain parcellation

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary act...

Full description

Bibliographic Details
Main Authors: Lashkari, Danial (Contributor), Sridharan, Ramesh (Contributor), Vul, Edward (Contributor), Hsieh, Po-Jang (Contributor), Kanwisher, Nancy (Contributor), Golland, Polina (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), McGovern Institute for Brain Research at MIT (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers / IEEE Computer Society, 2011-04-15T19:57:34Z.
Subjects:
Article
Online Access:Get fulltext

Internet

Get fulltext

Similar Items