title: A new spatially constrained NMF with application to fMRI.
abstract: In this paper the problem of BOLD detection is addressed. The focus here is on non-negative matrix factorization (NMF), which is a data driven method and able to provide part-based representation of data. A new constrained optimization problem is proposed for the purpose of BOLD detection. The proposed constraint imposes some prior spatial information of active area inside the brain, on the decomposition process. The constraint is built up based on the type of stimulus and available physiological knowledge of the brain performance. The simulation results on both synthetic and real fMRI data show that applying the proposed constraint improves the BOLD detection performance.
authors.affiliation: Department of Computing, Faculty of Engineering and Physical Sciences, University of Surrey, United Kingdom. s.ferdowsi@surrey.ac.uk
authors.forename: Saideh
authors.initials: S
authors.lastname: Ferdowsi
authors.forename: Vahid
authors.initials: V
authors.lastname: Abolghasemi
authors.forename: Bahador
authors.initials: B
authors.lastname: Makkiabadi
authors.forename: Saeid
authors.initials: S
authors.lastname: Sanei
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity