Group study of simulated driving fMRI data by multiset canonical correlation analysis

© The Author(s) 2011. This article is published with open access at Springerlink.com Abstract In this work, we apply a novel statistical meth-od, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imag-ing (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions into brain ac-tivation maps and their associated time courses, such that the correlation in each group of estimated activa-tion maps across datasets is maximized. Therefore, the functional activations across all datasets are extracted in the order of consistency across different dataset. On the other hand, M-CCA preserves the uniquenes