Parametric analysis of fMRI data using linear systems methods

MS Cohen - Neuroimage, 1997 - Elsevier
Neuroimage, 1997Elsevier
Using a model of the functional MRI (fMRI) impulse response based on published data, we
have demonstrated that the form of the fMRI response to stimuli of freely varied timing can be
modeled well by convolution of the impulse response with the behavioral stimulus. The
amplitudes of the responses as a function of parametrically varied behavioral conditions are
fitted well using a piecewise linear approximation. Use of the combined model, in
conjunction with correlation analysis, results in an increase in sensitivity for the MRI study …
Using a model of the functional MRI (fMRI) impulse response based on published data, we have demonstrated that the form of the fMRI response to stimuli of freely varied timing can be modeled well by convolution of the impulse response with the behavioral stimulus. The amplitudes of the responses as a function of parametrically varied behavioral conditions are fitted well using a piecewise linear approximation. Use of the combined model, in conjunction with correlation analysis, results in an increase in sensitivity for the MRI study. This approach, based on the well-established methods of linear systems analysis, also allows a quantitative comparison of the response amplitudes across subjects to a broad range of behavioral conditions. Fit parameters, derived from the amplitude data, are relatively insensitive to a variety of MRI-related artifacts and yield results that are compared readily across subjects.
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