Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13207
Title: Nonlinear canonical correlation analysis of fMRI signals using hDR models
Authors: Wang, DF
Shi, L
Yeung, DS
Tsang, ECC
Keywords: Biomedical MRI
Blood
Correlation methods
Haemodynamics
Physiological models
Statistical analysis
Time series
Issue Date: 2005
Publisher: IEEE
Source: 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005 : IEEE-EMBS 2005, September 2005, Shanghai, p. 5896-5899 How to cite?
Abstract: A nonlinear canonical correlation analysis (CCA) for detecting neural activation in fMRI data is proposed in this paper. We use the BOLD response based on the HDR models with various parameters as reference signals. Instead of characterizing the relationship between the paradigm and time series using the oversimplified linear model, we employ the kernel trick that maps the intensities of the voxels within a small cubic at each time point into a high-dimensional kernel space, where the linear combinations correspond to nonlinear ones in the original space. The experimental results show that the proposed nonlinear CCA can improve the detection performance of traditional linear CCA
URI: http://hdl.handle.net/10397/13207
ISBN: 0-7803-8741-4
DOI: 10.1109/IEMBS.2005.1615832
Appears in Collections:Conference Paper

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