A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.

A component based method (CompCor) for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented. In the proposed method, significant principal components are derived from noise regions-of-interest (ROI) in which the time series data are unlikely to be modulated by neural activity. These components are then included as nuisance parameters within general linear models for BOLD and perfusion-based fMRI time series data.

Caffeine alters the temporal dynamics of the visual BOLD response.

The blood oxygenation level-dependent (BOLD) responses to visual stimuli, using both a 1-s long single trial stimulus and a 20-s long block stimulus, were measured in a 4-T magnetic field both before and immediately after a 200-mg caffeine dose. In addition, resting levels of cerebral blood flow (CBF) were measured using arterial spin labeling. For the single trial stimulus, the caffeine dose significantly (p<0.

A signal processing model for arterial spin labeling functional MRI.

A model of the signal path in arterial spin labeling (ASL)-based functional magnetic resonance imaging (fMRI) is presented. Three subtraction-based methods for forming a perfusion estimate are considered and shown to be specific cases of a generalized estimate consisting of a modulator followed by a low pass filter. The performance of the methods is evaluated using the signal model.