Exploratory Approach to fMRI Study with Fuzzy Clustering and General Linear Model

Functional magnetic resonance imaging (fMRI) studies have shown that different cognitive functions activate overlapping brain regions and the functional responses of the brain differ from region to region. The modified fuzzy c-means (FCM) clustering is used for exploratory analysis of fMRI signals in which the cluster centroids represent typical hemodynamics responses of relatively wide brain regions. This paper shows how blood oxygen level-dependent (BOLD) signals can be approximated by a small number of cluster centroids and presents a framework that allows FCM clustering technique to be implemented in conjunction with the general linear model (GLM). The approach is illustrated with an fMRI experiment of recalling sentences. A subject consolidated the memory of English sentences using mnemonics called the method of loci. During experimental session the subject recalled the sentences by recalling the images of their associated places. Because the recalling by way of mnemonics is a brain activity with heavy burden, almost the whole cerebrum activate simultaneously. The brain activations synchronized widely and quite similar activation patterns were observed. This makes it difficult to distinguish the roles of the brain regions. The exploratory approach clarifies the slightly different responses of different brain regions to the heavy tasks of recalling sentences.