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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Beckmann, C.F. Smith, S.M. |
| Copyright Year | 1982 |
| Abstract | We present an integrated approach to probabilistic independent component analysis (ICA) for functional MRI (FMRI) data that allows for nonsquare mixing in the presence of Gaussian noise. In order to avoid overfitting, we employ objective estimation of the amount of Gaussian noise through Bayesian analysis of the true dimensionality of the data, i.e., the number of activation and non-Gaussian noise sources. This enables us to carry out probabilistic modeling and achieves an asymptotically unique decomposition of the data. It reduces problems of interpretation, as each final independent component is now much more likely to be due to only one physical or physiological process. We also describe other improvements to standard ICA, such as temporal prewhitening and variance normalization of timeseries, the latter being particularly useful in the context of dimensionality reduction when weak activation is present. We discuss the use of prior information about the spatiotemporal nature of the source processes, and an alternative-hypothesis testing approach for inference, using Gaussian mixture models. The performance of our approach is illustrated and evaluated on real and artificial FMRI data, and compared to the spatio-temporal accuracy of results obtained from classical ICA and GLM analyses. |
| Sponsorship | IEEE Engineering in Medicine and Biology Society IEEE Nuclear and Plasma Sciences Society IEEE Signal Processing Society IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society |
| Page Count | 16 |
| File Size | 758965 |
| Starting Page | 137 |
| Ending Page | 152 |
| File Format | |
| ISSN | 02780062 |
| Volume Number | 23 |
| Issue Number | 2 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-02-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Independent component analysis Magnetic resonance imaging Testing Magnetic analysis Gaussian noise Signal analysis Image analysis Signal processing Biomedical imaging Noise reduction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Computer Science Applications Radiological and Ultrasound Technology Software |
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