Data Analysis in Functional MRI

Benali H.1, Descombes X.2, Kruggel F.3, Rajapakse J.C.4, Svensen M.5

1 Faculte de Medecine Pitie-Salpetriere, 2 INRIA, Sophia Antipolis, 3 University of California, Irvine, 4 Nanyang Technological University, Singapore, 5 Max-Planck-Institute of Cognitive Neuroscience, Leipzig

Most functional MRI (fMRI) studies apply the blood-oxygen-level-dependent (BOLD) effect, where an indirect correlate of brain activation, the so-called hemodynamic response (HR) of the vascular system, is measured. Activations are found as stimulus-linked and time-dependent local intensity changes in the images. Data analysis is complicated by the following circumstances: the effect is rather small, data are noisy and overlaid by artifacts, the HR due to a brief stimulus is typically delayed by 3-5 s and dispersed by 1.5-2.5 s, and perhaps also displaced with respect to the activation site. So the question remained open, how much could be inferred from the HR shape characteristics about the underlying neuronal activation. Strategies for fMRI data analysis are best cast in a classical framework for signal analysis:


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