title: Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.
abstract: The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.
authors.affiliation: Graduate School for Integrative Sciences and Engineering, National University of Singapore Singapore, Singapore.
authors.forename: Changqing
authors.initials: C
authors.lastname: Wang
authors.affiliation: Department of Biomedical Engineering, National University of Singapore Singapore, Singapore.
authors.forename: Judy
authors.initials: J
authors.lastname: Kipping
authors.affiliation: Department of Mathematics, National University of Singapore Singapore, Singapore.
authors.forename: Chenglong
authors.initials: C
authors.lastname: Bao
authors.affiliation: Department of Mathematics, National University of Singapore Singapore, Singapore.
authors.forename: Hui
authors.initials: H
authors.lastname: Ji
authors.affiliation: Department of Biomedical Engineering, National University of SingaporeSingapore, Singapore; Clinical Imaging Research Centre, National University of SingaporeSingapore, Singapore; Singapore Institute for Clinical Sciences, Agency for Science, Technology, and ResearchSingapore, Singapore.
authors.forename: Anqi
authors.initials: A
authors.lastname: Qiu
keywords: brain parcellation; cerebellum; dictionary learning; resting-state functional magnetic resonance imaging; sparse coding