Download PDF by Christoph Stippich: Clinical Functional MRI: Presurgical Functional Neuroimaging

By Christoph Stippich

ISBN-10: 3540244697

ISBN-13: 9783540244691

This is often the 1st textbook on scientific fMRI. it's dedicated to preoperative fMRI in sufferers with mind tumors and epilepsies, that are the main well-established scientific purposes. state of the art fMRI approaches are awarded, with unique attention of the physiological and methodological history, imaging and information processing, basic and pathological findings, diagnostic probabilities and obstacles, and different similar recommendations.

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Extra info for Clinical Functional MRI: Presurgical Functional Neuroimaging

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The design matrix on the left contains only one predictor, the constant term. The estimated beta weight (b0) scales the constant term to the mean signal level. The design matrix in the middle adds a predictor for “green” main condition. The estimated beta weights (b0, b1) scale the predictors and the weighted sum explains more variance than the fi rst model, but residual variance is still high. The third model (right) adds a predictor for “red” main condition. The estimated beta weights (b0, b1, b2) scale the predictors and the weighted sum now explains all taskrelated signal fluctuations.

Another correction method incorporating the observation that neighboring voxels often activate in clusters is based on Monte Carlo simulations calculating the likelihood to obtain clusters of different sizes (Forman et al. 1995). 05 is met. This approach does not require spatial smoothing and appears highly appropriate for fMRI data. The only disadvantage is that the method is quite computer intensive.

Another temporal preprocessing step consists in temporal smoothing of voxel time courses removing high-frequency signal fluctuations, which are considered as noise. While this step increases the signal-to-noise ratio, temporal smoothing is not recommended when analyzing event-related designs since it may distort estimates of temporally relevant parameters, such as the onset or width of average event-related responses. Fig. 13. Principle of temporal fi ltering using Fourier analysis. The time-domain signal can be converted in an equivalent frequency-domain signal using the Fourier transform (upper row).

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Clinical Functional MRI: Presurgical Functional Neuroimaging by Christoph Stippich

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