BOLD Noise Assumptions in fMRI
This paper discusses the assumption of Gaussian noise in the blood-oxygenation-dependent (BOLD) contrast for functional MRI (fMRI). In principle, magnitudes in MRI images follow a Rice distribution. We start by reviewing differences between Rician and Gaussian noise. An analytic expression is derive...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2006-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/IJBI/2006/12014 |
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| _version_ | 1832550075185758208 |
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| author | Alle Meije Wink Jos B. T. M. Roerdink |
| author_facet | Alle Meije Wink Jos B. T. M. Roerdink |
| author_sort | Alle Meije Wink |
| collection | DOAJ |
| description | This paper discusses the assumption of Gaussian noise in the
blood-oxygenation-dependent (BOLD) contrast for functional MRI
(fMRI). In principle, magnitudes in MRI images follow a Rice
distribution. We start by reviewing differences between Rician and
Gaussian noise. An analytic expression is derived for the null
(resting-state) distribution of the difference between two Rician
distributed images. This distribution is shown to be symmetric,
and an exact expression for its standard deviation is derived.
This distribution can be well approximated by a Gaussian, with
very high precision for high SNR, and high precision for lower
SNR. Tests on simulated and real MR images show that subtracting
the time-series mean in fMRI yields asymmetrically distributed
temporal noise. Subtracting a resting-state time series from the
first results in symmetric and nearly Gaussian noise. This has
important consequences for fMRI analyses using standard
statistical tests. |
| format | Article |
| id | doaj-art-6a341b41e25242a68fc310a56b3a92b7 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2006-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-6a341b41e25242a68fc310a56b3a92b72025-02-03T06:07:45ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962006-01-01200610.1155/IJBI/2006/1201412014BOLD Noise Assumptions in fMRIAlle Meije Wink0Jos B. T. M. Roerdink1Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge CB2 2QQ, United KingdomInstitute for Mathematics and Computing Science, University of Groningen, P.O. Box 800, Groningen 9700 AV, The NetherlandsThis paper discusses the assumption of Gaussian noise in the blood-oxygenation-dependent (BOLD) contrast for functional MRI (fMRI). In principle, magnitudes in MRI images follow a Rice distribution. We start by reviewing differences between Rician and Gaussian noise. An analytic expression is derived for the null (resting-state) distribution of the difference between two Rician distributed images. This distribution is shown to be symmetric, and an exact expression for its standard deviation is derived. This distribution can be well approximated by a Gaussian, with very high precision for high SNR, and high precision for lower SNR. Tests on simulated and real MR images show that subtracting the time-series mean in fMRI yields asymmetrically distributed temporal noise. Subtracting a resting-state time series from the first results in symmetric and nearly Gaussian noise. This has important consequences for fMRI analyses using standard statistical tests.http://dx.doi.org/10.1155/IJBI/2006/12014 |
| spellingShingle | Alle Meije Wink Jos B. T. M. Roerdink BOLD Noise Assumptions in fMRI International Journal of Biomedical Imaging |
| title | BOLD Noise Assumptions in fMRI |
| title_full | BOLD Noise Assumptions in fMRI |
| title_fullStr | BOLD Noise Assumptions in fMRI |
| title_full_unstemmed | BOLD Noise Assumptions in fMRI |
| title_short | BOLD Noise Assumptions in fMRI |
| title_sort | bold noise assumptions in fmri |
| url | http://dx.doi.org/10.1155/IJBI/2006/12014 |
| work_keys_str_mv | AT allemeijewink boldnoiseassumptionsinfmri AT josbtmroerdink boldnoiseassumptionsinfmri |