Information transfer rate in fMRI experiments measured using mutual information theory Journal Article


Authors: Ward, B. D.; Mazaheri, Y.
Article Title: Information transfer rate in fMRI experiments measured using mutual information theory
Abstract: Information theory provides a mathematical framework for analysis of fMRI experiments. By modeling the fMRI experiment as a communication system, various results from information theory can be applied to measure information transfer rate in fMRI experiments. The information transfer rate has important implications for design and analysis of brain-computer interface (BCI) experiments. A key factor in the effective implementation of BCI techniques is to achieve maximum information transfer rate. In this report, mutual information rate (MIR) was used to evaluate the efficiency of alternative experimental designs. The channel capacity, a fundamental physical limit on the rate at which information can be extracted from an fMRI experiment, was estimated and compared with the theoretical limit specified by the Hartley-Shannon Theorem. We present an information theory framework for the analysis of fMRI time-series assuming a known hemodynamic response function. Using MIR to evaluate fMRI experimental designs, we show that block lengths of 3-5 s have maximum information transfer rates. For designs with shorter block lengths, the MIR is limited by the channel capacity. For experimental designs with longer block lengths, the MIR is limited by the low source information transmission rate. © 2007.
Keywords: magnetic resonance imaging; oxygen; signal noise ratio; user-computer interface; brain; data analysis; functional magnetic resonance imaging; information science; experimental design; technique; hemodynamics; normal human; monte carlo method; human experiment; brain-computer interface (bci); functional magnetic resonance imaging (fmri); information theory; information transfer rate; mutual information rate (mir); brain computer interface; data extraction; numerical analysis, computer-assisted
Journal Title: Journal of Neuroscience Methods
Volume: 167
Issue: 1
ISSN: 0165-0270
Publisher: Elsevier B.V.  
Date Published: 2008-01-15
Start Page: 22
End Page: 30
Language: English
DOI: 10.1016/j.jneumeth.2007.06.027
PUBMED: 17919734
PROVIDER: scopus
DOI/URL:
Notes: --- - "Cited By (since 1996): 1" - "Export Date: 17 November 2011" - "CODEN: JNMED" - "Source: Scopus"
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