title: Reducing correlated noise in fMRI data.
abstract: The sensitivity of functional MRI (fMRI) in detecting neuronal activation is dependent on the relative levels of signal and noise in the time-series data. The temporal noise level within a single voxel is generally substantially higher than the intrinsic NMR (thermal) noise, and the noise is often correlated between voxels. This work introduces and evaluates a method that allows fMRI sensitivity improvement by reduction of these correlated noise sources. The method allows model-free estimation of the correlated noise from brain regions not activated by the functional paradigm using a short (1-2 min) reference scan. A single regressor representing this noise-source estimate is added to the design matrix used in the data analysis. Results obtained from five volunteers show an average t-score improvement of 11.3% and a 24.2% increase in the size of the activated area.
authors.affiliation: Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892-1065, USA. Jacco.deZwart@nih.gov
authors.forename: Jacco A
authors.initials: JA
authors.lastname: de Zwart
authors.forename: Peter van
authors.initials: Pv
authors.lastname: Gelderen
authors.forename: Masaki
authors.initials: M
authors.lastname: Fukunaga
authors.forename: Jeff H
authors.initials: JH
authors.lastname: Duyn
mesh_terms: D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic