Functional Region Hierarchy: Representation and Modeling of Spatial Activation Patterns in fMRI
Speaker: Professor Polina Golland , CSAIL, MIT
Date: November 9 2006
Time: 1:30PM to 2:30PM
Location: 32-D507
Host: Wanmei Ou, CSAIL
Contact: Wanmei Ou, 3-4143, wanmei@mit.edu
In this talk, I will present a novel approach to computational
modeling of spatial activation patterns observed through
fMRI. Functional connectivity analysis is widely used in fMRI studies
for detection and analysis of large networks that co-activate with a
user-selected `seed' region of interest. In contrast, our method is
based on clustering; it simultaneously identifies interesting seed
time courses and associates voxels with the respective networks. This
generalization eliminates the sensitivity to the threshold used to
classify voxels as members of a network and enables discovery of
co-activated networks without user selection of seed regions.
Based on the empirical observation that the detected patterns of
co-activation are inherently hierarchical, we propose a new
representation for spatial patterns of functional organization. Just
like the anatomical hierarchies represent the structure of the brain
as a tree of increasingly simple systems, we believe that the
functional description of the brain should also be of a hierarchical
nature. We introduce Functional Region Hierarchy, a top-down
representation that encapsulates the notion that functionally defined
regions should be viewed at different resolutions, as dictated by the
observed activation pattern. We construct the functional region
hierarchy through an iterative decomposition that utilizes clustering
for network subdivision at each step.
The experimental results demonstrate that the functional region
hierarchy provides a robust and anatomically meaningful model for
spatial patterns of co-activation in fMRI. The hierarchical
representation leads to insights into the structure of the functional
networks that are not immediately apparent from flat representations
that segment the brain into a large number of small regions. In
addition, subject-specific region hierarchies tend to share common
tree structure, further confirming the validity of this representation
for modeling group-wise patterns of co-activation.
See other events that are part of Biomedical Imaging and Analysis 2006/2007
See other events happening in November 2006
