Recently, the temporal clustering analysis (TCA) method is introduced to analyze functional MRI (fMRI) data without any priori information about the activation patterns or the experimental paradigms. It has been successfully applied to situation where the timing of events of interesting is not known. However, the useful information regarding the spatial correlation of the activation pixels with its neighbors is not taken into account in the original TCA method. In this study, we propose a new method called “STCA” which incorporates the spatial information with TCA method to improve the sensitivity in detecting the time window. The spatial information is defined as the correlation coefficient of the time activity curve between each pixel and its neighbors. The inclusion of spatial information can effectively reduce the contribution from noisy pixel and enhance the sensitivity. Both simulated data and in vivo fMRI experiments are tested to verify the method. Preliminary results show that the proposed method has increased the sensitivity by 24% for in vivo fMRI data in detecting the activation response time

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