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A robust signal detection method for fMRI data under correct Rice conditions
Vrije Universiteit Brussel.
Vrije Universiteit Brussel.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences. (Elektronik)
2012 (English)In: Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International, 2012Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we tackle the problem of signal detection in functional Magnetic Resonance Imaging (fMRI) data by means of a statistical analysis. The main problem of the commonly used statistical tests is that they are based on the assumption that the data are Gaussian distributed, which is only valid for high signal-to-noise ratios (SNRs). Hence, for low SNRs the classical statistical tests are inadequate due to the wrong normality assumption, since it is known from literature that fMRI data follow a Rice distribution. In order to handle both high and low SNRs, we present in this paper a correction for the simplest and most widely used t-test by incorporating the correct Rice conditions. The performance of the Rice-corrected statistical test is shown through simulations and compared with its uncorrected counterpart.

Place, publisher, year, edition, pages
2012.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hig:diva-12707DOI: 10.1109/I2MTC.2012.6229243Scopus ID: 2-s2.0-84864257713ISBN: 978-1-4577-1773-4 (print)OAI: oai:DiVA.org:hig-12707DiVA: diva2:547645
Conference
Instrumentation and Measurement Technology Conference (I2MTC), 13-16 May 2012, Graz, Austria
Available from: 2012-08-28 Created: 2012-08-28 Last updated: 2012-08-29Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf