Overview of functional magnetic resonance imaging

Abstract

Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) depicts changes in deoxyhemoglobin concentration consequent to task-induced or spontaneous modulation of neural metabolism. Since its inception in 1990, this method has been widely employed in thousands of studies of cognition for clinical applications such as surgical planning, for monitoring treatment outcomes, and as a biomarker in pharmacologic and training programs. More recently, attention is turning to the use of pattern classification and other statistical methods to draw increasingly complex inferences about cognitive brain states from fMRI data. This article reviews the methods, challenges, and future of fMRI.

Figure 1

Sketch of brain tissue containing a capillary during rest (top) and activation (bottom). Red and blue circles represent red blood cells that are fully oxygenated (HbO2) and fully deoxygenated (Hb), respectively. The MRI signal is depressed in the venous side of the capillary due to the paramagnetic susceptibility of the HB acting as an endogenous contrast agent (shown darker). In the stimulated condition, increased blood flow causes the Hb to be swept out and replaced by HbO2, causing a BOLD signal increase.

Figure 2

Block design fMRI experiment. A neural response to the state change from A to B in the stimulus is accompanied by a hemodynamic response (as shown in Fig. 1) that is detected by the rapid and continuous acquisition of MR images sensitized to BOLD signal changes. Using single- or multi-variate time series analysis methods, the average signal difference between the two states is computed for the scan and a contrast map generated. A statistical activation map is finally obtained using a suitable threshold for the difference; the map depicts the probability that a voxel is activated given the uncertainty due to noise and the small BOLD signal differences.