title: A modified temporal self-correlation method for analysis of fMRI time series.
abstract: Temporal self-correlation has recentlybeen proposed as a measure for fMRI-activation detection. In this paper, a modified temporal self-correlation method is introduced. The modified temporal self-correlation is based on the expectation value and standard deviation of the correlation coefficients between all pairs of epochs, while the original temporal self-correlation method is only based on the expectation value. Performance of the proposed method is evaluated on both simulated and in vivo fMRI data. Compared with the original temporal self-correlation method, the proposed method shows a significant improvement. In addition, a technique for quantitative comparison of different fMRI data analysis methods is proposed.
authors.affiliation: National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China.
authors.forename: Yingli
authors.initials: Y
authors.lastname: Lu
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Zang
authors.forename: Tianzi
authors.initials: T
authors.lastname: Jiang
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001921:Brain / Q000378:metabolism / Q000502:physiology; D001931:Brain Mapping; D003198:Computer Simulation; D005583:Fourier Analysis; D007839:Functional Laterality; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results