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Improvement of spectral density-based activation detection of event-related fMRI data
Authors:Shing-Chung Ngan  Xiaoping Hu  Li-Hai Tan  Pek-Lan Khong
Institution:aDepartment of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China;bDepartment of Diagnostic Radiology, University of Hong Kong, Hong Kong, China;cDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA;dState Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, China
Abstract:For event-related data obtained from an experimental paradigm with a periodic design, spectral density at the fundamental frequency of the paradigm has been used as a template-free activation detection measure. In this article, we build and expand upon this detection measure to create an improved, integrated measure. Such an integrated measure linearly combines information contained in the spectral densities at the fundamental frequency as well as the harmonics of the paradigm and in a spatial correlation function characterizing the degree of co-activation among neighboring voxels. Several figures of merit are described and used to find appropriate values for the coefficients in the linear combination. Using receiver-operating characteristic analysis on simulated functional magnetic resonance imaging (fMRI) data sets, we quantify and validate the improved performance of the integrated measure over the spectral density measure based on the fundamental frequency as well as over some other popular template-free data analysis methods. We then demonstrate the application of the new method on an experimental fMRI data set. Finally, several extensions to this work are suggested.
Keywords:Template-free detection  fMRI  Spectral density
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