An exponential random graph modeling approach to creating group-based representative whole-brain connectivity networks.

ABSTRACT: Group-based brain connectivity networks have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Accurately constructing these networks presents a daunting challenge given the difficulties associated with accounting for inter-subject topological variability. Viable approaches to this task must engender networks that capture the constitutive topological properties of the group of subjects' networks that it is aiming to represent. The conventional approach has been to use a mean or median correlation network (Achard et al., 2006; Song et al., 2009; Zuo et al., 2011) to embody a group of networks. However, the degree to which their topological properties conform with those of t

SUBMITTER: Simpson SL 

PROVIDER: S-EPMC3303958 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature