Multisubject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery
Year: 2012
Type: review
Abstract: Since the discovery of functional connectivity in fMRI data (i.e., temporal correlations between spatially distinct regions of the brain) there has been a considerable amount of work in this field. One important focus has been on the analysis of brain connectivity using the concept of networks instead of regions. Approximately ten years ago, two important research areas grew out of this concept. First, a network proposed to be "a default mode of brain function" since dubbed the default mode network was proposed by Raichle. Secondly, multisubject or group independent component analysis (ICA) provided a data-driven approach to study properties of brain networks, including the default mode network. In this paper, we provide a focused review of how ICA has contributed to the study of intrinsic networks. We discuss some methodological considerations for group ICA and highlight multiple analytic approaches for studying brain networks. We also show examples of some of the differences observed in the default mode and resting networks in the diseased brain. In summary, we are in exciting times and still just beginning to reap the benefits of the richness of functional brain networks as well as available analytic approaches.
Authors: Vince D. Calhoun, Tülay Adali
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Awards: A Unified Framework for Flexible Brain Image Analysis, Unified multivariate data-driven solutions for static and dynamic brain connectivity, Neural Mechanism of Schizophrenia: Use of Multiple Neuroimaging Tools to Examine, Multimodal Imaging of Neuropsychiatric Disorders (MIND): Mechanisms &, Multivariate methods for identifying multitask/multimodal brain imaging biomarkers
OpenAlex ID: W1986589478