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An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them.

Original publication

DOI

10.1162/jocn_a_00077

Type

Journal article

Journal

Journal of cognitive neuroscience

Publication Date

12/2011

Volume

23

Pages

4022 - 4037

Addresses

Research Imaging Institute, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900, USA. lairda@uthscsa.edu

Keywords

Brain, Nerve Net, Neural Pathways, Humans, Brain Mapping, Cluster Analysis, Psychomotor Performance, Classification, Databases, Factual