Detecting auditory cortex: A comparison of SPM and WSPM

Nowadays, statistical parametric mapping (SPM) is the most widely-used method for the analysis of fMRI data. As the progress of SPM, some researchers have proposed WSPM, a new method based on wavelet transform. The advantage of WSPM is that it can not only reduce the spatial bias of SPM, but also sh...

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Bibliographic Details
Published in:2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008-01, p.3937-3940
Main Authors: Shaojie-Sun, Liuhong-Zhu, Shuqian-Luo
Format: Article
Language:English
Subjects:
Biomedical engineering
Biomedical imaging
Discrete wavelet transforms
Functional magnetic resonance imaging
Smoothing methods
Online Access:Request full text
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Summary:Nowadays, statistical parametric mapping (SPM) is the most widely-used method for the analysis of fMRI data. As the progress of SPM, some researchers have proposed WSPM, a new method based on wavelet transform. The advantage of WSPM is that it can not only reduce the spatial bias of SPM, but also shows the closer result to the true active areas. In this paper, there are eight sets of fMRI data stimulated by voice, from which we want to figure out the active brain areas under the stimulation. To confirm the active areas, we used the two methods based on different smoothing methods and made comparison. WSPM was showed to have stronger control of type-I error (false positives) than SPM.
ISSN:1094-687X
1558-4615
DOI:10.1109/IEMBS.2008.4650071