title: Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data.
abstract: Significant correlation exists in the blood-oxygen-level-dependent (BOLD) signals of resting-state fMRI across different regions in the brain. These regions form the default mode network (DMN), salience network (SN), sensory networks, and others. Among these, the DMN is widely investigated in relation to various mental diseases. Several analytic methods are available for obtaining the DMN activity from individuals' fMRI time-series signals, but a fully effective method has not yet been established. In the present study, we examined a functional connectivity analysis and three algorithms of blind source separation including independent component analysis, second-order blind identification, and non-negative matrix factorization using a set of resting-state fMRI data measured for twelve young participants. Results showed that the second-order blind identification yielded superior performance for the DMN detection, indicating significant activation in all DMN regions based on statistical parametric maps.
authors.forename: Kenta
authors.initials: K
authors.lastname: Tachikawa
authors.forename: Shun
authors.initials: S
authors.lastname: Izawa
authors.forename: Yumie
authors.initials: Y
authors.lastname: Ono
authors.forename: Shinya
authors.initials: S
authors.lastname: Kuriki
authors.forename: Atsushi
authors.initials: A
authors.lastname: Ishiyama
mesh_terms: D000465:Algorithms; D001931:Brain Mapping; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009415:Nerve Net / Q000502:physiology*; D012146:Rest / Q000502:physiology*; D055815:Young Adult