title: Adaptive filtering and random variables coefficient for analyzing functional magnetic resonance imaging data.
abstract: Functional magnetic resonance imaging (fMRI) is used to study brain functional connectivity (FC) after filtering the physiological noise (PN). Herein, we employ: adaptive filtering for removing nonstationary PN; random variables (RV) coefficient for FC analysis. Comparisons with standard techniques were performed by quantifying PN filtering and FC in neural vs. non-neural regions. As a result, adaptive filtering plus RV coefficient showed a greater suppression of PN and higher connectivity in neural regions, representing a novel effective approach to analyze fMRI data.
authors.affiliation: Department of Energy and Systems Engineering, University of Pisa, Largo Lucio Lazzarino, Pisa, 56122, Italy. paolo.piaggi@gmail.com
authors.forename: Paolo
authors.initials: P
authors.lastname: Piaggi
authors.forename: Danilo
authors.initials: D
authors.lastname: Menicucci
authors.forename: Claudio
authors.initials: C
authors.lastname: Gentili
authors.forename: Giacomo
authors.initials: G
authors.lastname: Handjaras
authors.forename: Angelo
authors.initials: A
authors.lastname: Gemignani
authors.forename: Alberto
authors.initials: A
authors.lastname: Landi
mesh_terms: D000704:Analysis of Variance; D016477:Artifacts; D001921:Brain / Q000098:blood supply* / Q000502:physiology*; D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D009434:Neural Pathways / Q000098:blood supply; D010100:Oxygen / Q000097:blood; D059629:Signal-To-Noise Ratio
chemical_list: D010100:Oxygen