Behavioral interpretations of intrinsic connectivity networks

Author: Angela R Laird1, P Mickle Fox, Simon B Eickhoff, Jessica A Turner, Kimberly L Ray, D Reese McKay, David C Glahn, Christian F Beckmann, Stephen M Smith, Peter T Fox
1 Research Imaging Institute, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900, USA.
Conference/Journal: J Cogn Neurosci
Date published: 2011 Dec 1
Other: Volume ID: 23 , Issue ID: 12 , Pages: 4022-37 , Special Notes: doi: 10.1162/jocn_a_00077. , Word Count: 151

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.

PMID: 21671731 PMCID: PMC3690655 DOI: 10.1162/jocn_a_00077