Behavioral Interpretations of Intrinsic Connectivity Networks

TLDR

Resting‑state functional connectivity studies have mapped brain networks, but their task‑independent nature has limited functional interpretation until recent work showed that similar networks can be derived from both resting and thousands of task‑based experiments in the BrainMap database. The study aims to provide a comprehensive functional interpretation of intrinsic connectivity networks using a low‑order decomposition and a neuroinformatics approach grounded in the BrainMap behavioral taxonomy and a stratified, data‑driven ordering of cognitive processes. The authors employ a neuroinformatics pipeline that maps intrinsic connectivity networks onto the BrainMap behavioral taxonomy and orders cognitive processes stratified by data‑driven criteria. The resulting atlas offers functional interpretations of resting‑state networks, serving as a resource for future research linking mental operations to specific tasks.

Abstract

Abstract 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.