“School of Cognitive”
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| Paper IPM / Cognitive / 7521 |
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FCM suffers from some drawbacks such as a priori definition of number of clusters, unidentified statistical significance of results, and instability of results when it is applied on raw fMRI time series. Using the randomization we developed a method to control the rate of false positive detection in FCM which gives a meaningful statistical significance to the results. Making use of it, we derived the optimum number of clusters. In this study we applied the FCM on a feature space that takes the variability of hemodynamic response function into account and compared it with the cross correlation feature space.
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