The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.
Recent years have witnessed a rapid growth of interest in moving functional magnetic resonance imaging (fMRI) beyond simple scan-length averages and into approaches that capture time-varying properties of connectivity. In this Perspective we use the term "chronnectome" to describe metrics that allow a dynamic view of coupling. In the chronnectome, coupling refers to possibly time-varying levels of correlated or mutually informed activity between brain regions whose spatial properties may also be temporally evolving. We primarily focus on multivariate approaches developed in our group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component analysis. We also discuss the potential these approaches offer to improve characterization and understanding of brain function. There are a number of methodological directions that need to be developed further, but chronnectome approaches already show great promise for the study of both the healthy and the diseased brain.
The Mind Research Network & LBERI, Albuquerque, NM 87106, USA; Department of ECE, University of New Mexico, Albuquerque, NM 87131, USA. Electronic address: vcalhoun@unm.edu.
Vince D
VD
Calhoun
The Mind Research Network & LBERI, Albuquerque, NM 87106, USA.
Robyn
R
Miller
Olin Neuropsychiatry Research Center, Hartford, CT 06114, USA.
Godfrey
G
Pearlson
Department of CSEE, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.
Tulay
T
Adalı
D000818:Animals; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D009434:Neural Pathways / Q000502:physiology*; D013997:Time Factors