Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis |
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Authors: | Yi-Ou Li Tom Eichele Vince D Calhoun Tulay Adali |
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Affiliation: | (1) Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA;(2) Department of Biological and Medical Psychology, University of Bergen, Jonas Lies Vei 91, 5011 Bergen, Norway;(3) The Mind Research Network, 1101 Yale Boulevard N.E, Albuquerque, NM 87106, USA;(4) Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA;(5) Department of Psychiatry, Yale University School, of Medicine, New Haven, CT, USA |
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Abstract: | In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional
magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI
datasets from different subjects/sessions into brain activation maps and their associated time courses, such that the correlation
in each group of estimated activation 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 uniqueness
of the functional maps estimated from each dataset by avoiding concatenation of different datasets in the analysis. Hence,
the cross-dataset variation of the functional activations can be used to test the hypothesis of functional-behavioral association.
In this work, we study 120 simulated driving fMRI datasets and identify parietal-occipital regions and frontal lobe as the
most consistently engaged areas across all the subjects and sessions during simulated driving. The functional-behavioral association
study indicates that all the estimated brain activations are significantly correlated with the steering operation during the
driving task. M-CCA thus provides a new approach to investigate the complex relationship between the brain functions and multiple
behavioral variables, especially in naturalistic tasks as demonstrated by the simulated driving study. |
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