Reproducibility and robustness of graph measures of the associative-semantic network.

ABSTRACT: Graph analysis is a promising tool to quantify brain connectivity. However, an essential requirement is that the graph measures are reproducible and robust. We have studied the reproducibility and robustness of various graph measures in group based and in individual binary and weighted networks derived from a task fMRI experiment during explicit associative-semantic processing of words and pictures. The nodes of the network were defined using an independent study and the connectivity was based on the partial correlation of the time series between any pair of nodes. The results showed that in case of binary networks, global graph measures exhibit a good reproducibility and robustness for networks which are not too sparse and these figures of merit depend on the graph measure and on the dens

SUBMITTER: Wang Y 

PROVIDER: S-EPMC4264875 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature