Paper
20 April 2000 Application of a linear time-invariant model in the Fourier domain to perform statistical analysis of functional magnetic resonance images
Daniel E. Rio, Robert R. Rawlings, Daniel Hommer
Author Affiliations +
Abstract
A linear time invariant model is applied to functional fMRI blood flow data. This model assumes that the fMRI stochastic output sequence can be determined by a constant plus a linear filter (hemodynamic response function) of several fixed deterministic inputs and an error term, assumed stationary with zero mean and error spectrum. An on-off finger tapping experiment was performed where the subject repetitively tapped their fingers for 30 seconds and remained still for 30 seconds. Thirty three disjoint frequency bands, 3 wave numbers wide were chosen to analyze the data. At each band an F- statistical image was constructed to test ((alpha) equals .05/33) whether power from the input signal induced a response in the output signal. Activation was seen at frequency .0154 Hz close to the frequency for maximum power of the input signal, .0167 Hz in the contralateral motor strip and motor cortex. In conclusion, (1) No assumptions are made about the filter. (2) Several different deterministic inputs may be applied. (3) Problems with temporal correlation are avoided by performing the statistics in the Fourier domain. (4) Testing can be performed for differences in the hemodynamic transfer function at different spatial locations under different experimental conditions.
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Daniel E. Rio, Robert R. Rawlings, and Daniel Hommer "Application of a linear time-invariant model in the Fourier domain to perform statistical analysis of functional magnetic resonance images", Proc. SPIE 3978, Medical Imaging 2000: Physiology and Function from Multidimensional Images, (20 April 2000); https://doi.org/10.1117/12.383406
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Cited by 4 scholarly publications.
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KEYWORDS
Statistical analysis

Functional magnetic resonance imaging

Data modeling

Hemodynamics

Statistical modeling

Magnetism

Brain

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