title: A Space Affine Matching Approach to fMRI Time Series Analysis.
abstract: For fMRI time series analysis, an important challenge is to overcome the potential delay between hemodynamic response signal and cognitive stimuli signal, namely the same frequency but different phase (SFDP) problem. In this paper, a novel space affine matching feature is presented by introducing the time domain and frequency domain features. The time domain feature is used to discern different stimuli, while the frequency domain feature to eliminate the delay. And then we propose a space affine matching (SAM) algorithm to match fMRI time series by our affine feature, in which a normal vector is estimated using gradient descent to explore the time series matching optimally. The experimental results illustrate that the SAM algorithm is insensitive to the delay between the hemodynamic response signal and the cognitive stimuli signal. Our approach significantly outperforms GLM method while there exists the delay. The approach can help us solve the SFDP problem in fMRI time series matching and thus of great promise to reveal brain dynamics.
authors.forename: Liang
authors.initials: L
authors.lastname: Chen
authors.forename: Weishi
authors.initials: W
authors.lastname: Zhang
authors.forename: Hongbo
authors.initials: H
authors.lastname: Liu
authors.forename: Shigang
authors.initials: S
authors.lastname: Feng
authors.forename: C L Philip
authors.initials: CL
authors.lastname: Chen
authors.forename: Huili
authors.initials: H
authors.lastname: Wang
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D001921:Brain / Q000000981:diagnostic imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D013997:Time Factors; D055815:Young Adult