title: Sparse representation of whole-brain fMRI signals for identification of functional networks.
abstract: There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification.
authors.affiliation: School of Automation, Northwestern Polytechnical University, China; Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Jinglei
authors.initials: J
authors.lastname: Lv
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Xi
authors.initials: X
authors.lastname: Jiang
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Xiang
authors.initials: X
authors.lastname: Li
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Dajiang
authors.initials: D
authors.lastname: Zhu
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Hanbo
authors.initials: H
authors.lastname: Chen
authors.affiliation: School of Automation, Northwestern Polytechnical University, China; Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Tuo
authors.initials: T
authors.lastname: Zhang
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Shu
authors.initials: S
authors.lastname: Zhang
authors.affiliation: School of Automation, Northwestern Polytechnical University, China.
authors.forename: Xintao
authors.initials: X
authors.lastname: Hu
authors.affiliation: School of Automation, Northwestern Polytechnical University, China.
authors.forename: Junwei
authors.initials: J
authors.lastname: Han
authors.affiliation: Department of Computer Science and Engineering, University of Texas at Arlington, TX, United States.
authors.forename: Heng
authors.initials: H
authors.lastname: Huang
authors.affiliation: Department of Mathematics and Statistics, Georgia State University, GA, United States.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Automation, Northwestern Polytechnical University, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Guo
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, United States.
authors.forename: Tianming
authors.initials: T
authors.lastname: Liu
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D009415:Nerve Net / Q000502:physiology*
keywords: Activation; Connectivity; Intrinsic networks; Task-based fMRI