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Abstract #2080

Optimization of ICA for Detection of Weak and Focal Activations in FMRI

Waqas Majeed1, 2, Feng Wang1, 2, Robert M. Friedman3, Chaohui Tang1, 2, Malcolm J. Avison1, 2

1Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University, Nashville, TN, United States; 2Department of Radiology, Vanderbilt University, Nashville, TN, United States; 3Department of Psychology, Vanderbilt University, Nashville, TN, United States

In this study, we describe an approach for detecting weak and focal activity patterns in fMRI data. High resolution cerebral blood volume weighted images were acquired from squirrel monkeys during tactile stimulation of digits 1 and 3. The data were preprocessed to enhance effective contrast-to-noise ratio, and the model order was estimated in a data-driven fashion (based upon stability of the principal modes). Activation patterns associated with stimulation of individual digits were successfully detected using ICA. In future, we intend to use this approach to investigate the presence of local functional connectivity networks within the somatosensory cortex of squirrel monkeys.