Signal Modeling in Functional MRI
Kruggel F.1, Rajapakse J.C.2, Svensen M.3
1 University of California, Irvine, 2 Nanyang Technological University, Singapore, 3 Max-Planck-Institute of Cognitive Neuroscience, Leipzig
Signal description aims at modeling the response shape by parameters and relating these parameter values to variables of the stimulation context. A flexible nonlinear regression context was proposed to model the hemodynamic response (HR) as a sum of a deterministic function and a stochastic part. By adaptation of the model function to the observed HR, we obtain parameters that characterize the HR shape, such as the gain (height of the HR), the lag (time from stimulation onset to maximum) and dispersion (temporal width of the HR). These parameters are compared with the stimulation context in a subsequent regression model.
An item recognition task proves this concept in a complex event-related experiment. Subjects were shown a cue set of 3-6 letters. After a variable delay length (2.0-7.0 s) a probe letter appeared, and the subject was asked to respond via a button press whether the probe letter belonged to the previously presented set. Subjects completed 192 different combinations. Because cue and probe phases were expected to elicit HRs, we used a sum of two Gaussian functions as a model function. The cue phase response was found to depend on the set size only, with a gain increase of up to 15% per set item in activations along the inferior frontal sulcus. The lag of the probe phase response depended obviously on the delay time, but on the set size (+80 ms per item) and on the hit/foil manipulation (+200 ms). Responses in both phases decreased during experimental time by more than 50% in some focal activations, indicating an on-going parallel optimization of the task.
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Left: Activated brain regions in a fMRI experiment on working memory. Right: A few trials from the spatially averaged time course of the signal in two sample regions. Dotted lines denote the visual stimulation. Note the variable delay time between cue and probe phase. Thick dots correspond to the measurements, and black lines to the estimated waveforms.
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