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Activity Number: 467
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #304830
Title: The Effects of Dimension of Wavelet Resampling on Tests for Functional Connectivity
Author(s): Ohn Jo Koh*+ and William Schucany and Richard F. Gunst and Wayne A. Woodward
Companies: Southern Methodist University and Southern Methodist University and Southern Methodist University and Southern Methodist University
Address: , , ,
Keywords: fMRI ; wavelet ; packet ; resampling ; dimension ; connectivity
Abstract:

Many fMRI studies aim to identify pathways of signal processing in the brain in response to external stimuli. Since there is some functional connectivity in the resting state, generating null data that preserve background spatial temporal correlation is needed.. The spatiotemporal wavelet packet resampling method by Patel et al. (2006) generates null data that approximates the background spatial temporal correlation better than resampling wavelet coefficients with separable bases, but at the cost of computation. They performed 2D wavelet packet resampling in axial slices and then temporally. The effects of increasing dimension of wavelet resampling is investigated based on power spectral densities, computational expense, and power comparisons from simulation tests for functional connectivity.

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