title: Task fMRI data analysis based on supervised stochastic coordinate coding.
abstract: Task functional magnetic resonance imaging (fMRI) has been widely employed for brain activation detection and brain network analysis. Modeling rich information from spatially-organized collection of fMRI time series is challenging because of the intrinsic complexity. Hypothesis-driven methods, such as the general linear model (GLM), which regress exterior stimulus from voxel-wise functional brain activity, are limited due to overlooking the complexity of brain activities and the diversity of concurrent brain networks. Recently, sparse representation and dictionary learning methods have attracted increasing interests in task fMRI data analysis. The major advantage of this methodology is its promise in reconstructing concurrent brain networks systematically. However, this data-driven strategy is, to some extent, arbitrary and does not sufficiently utilize the prior information of task design and neuroscience knowledge. To bridge this gap, we here propose a novel supervised sparse representation and dictionary learning framework based on stochastic coordinate coding (SCC) algorithm for task fMRI data analysis, in which certain brain networks are learned with known information such as pre-defined temporal patterns and spatial network patterns, and at the same time other networks are learned automatically from data. Our proposed method has been applied to two independent task fMRI datasets, and qualitative and quantitative evaluations have shown that our method provides a new and effective framework for task fMRI data analysis.
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA; Translational Neuroscience, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
authors.forename: Jinglei
authors.initials: J
authors.lastname: Lv
authors.affiliation: Department of Computational Medicine and Bioinformatics & Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Binbin
authors.initials: B
authors.lastname: Lin
authors.affiliation: Department of Computer Science and Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: Qingyang
authors.initials: Q
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, USA.
authors.forename: Wei
authors.initials: W
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, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.
authors.forename: Xi
authors.initials: X
authors.lastname: Jiang
authors.affiliation: School of Automation, Northwestern Polytechnical University, Xi'an, PR China.
authors.forename: Lei
authors.initials: L
authors.lastname: Guo
authors.affiliation: School of Automation, Northwestern Polytechnical University, Xi'an, PR China.
authors.forename: Junwei
authors.initials: J
authors.lastname: Han
authors.affiliation: School of Automation, Northwestern Polytechnical University, Xi'an, PR China.
authors.forename: Xintao
authors.initials: X
authors.lastname: Hu
authors.affiliation: Translational Neuroscience, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
authors.forename: Christine
authors.initials: C
authors.lastname: Guo
authors.affiliation: Department of Computational Medicine and Bioinformatics & Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Jieping
authors.initials: J
authors.lastname: Ye
authors.affiliation: Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA. Electronic address: tliu@uga.edu.
authors.forename: Tianming
authors.initials: T
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D063132:Connectome; D006801:Humans; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009048:Motor Skills; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes
keywords: Brain networks; Supervised sparse coding; Task fMRI