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A modified temporal self-correlation method for analysis of fMRI time series
Yingli Lu1, Yufeng Zang, Tianzi Jiang
1National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China.
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.

