Behavioral Interpretations of Intrinsic Connectivity Networks

摘要

An increasingly large number of neuroimaging studies haveninvestigated functionally connected networks during rest, providingninsight into human brain architecture. Assessment of the functionalnqualities of resting state networks has been limited by thentask-independent state, which results in an inability to relate thesennetworks to specific mental functions. However, it was recentlyndemonstrated that similar brain networks can be extracted fromnresting state data and data extracted from thousands of task-basednneuroimaging experiments archived in the BrainMap database.nHere, we present a full functional explication of these intrinsicnconnectivity networks at a standard low order decomposition usingna neuroinformatics approach based on the BrainMap behavioralntaxonomy as well as a stratified, data-driven ordering of cognitivenprocesses. Our results serve as a resource for functional interpretationsnof brain networks in resting state studies and future investigationsninto mental operations and the tasks that drive them.