Glossary Terms  Home

M

Magnetic Field Mapping

The collection of explicit information about the strength of the magnetic field at different spatial locations.

Magnetic Moment 

The torque (turning force) exerted on a magnet, moving electrical charge, or current-carrying coil when it is placed in a magnetic field.

Magnetic Resonance

The absorption of energy from a magnetic field that oscillates at a particular frequency.

Magnetic Susceptibility

The intensity of magnetization of a substance when placed within a magnetic field.

Magnetoencephalography (MEG)

A noninvasive function neuroimaging technique that measures very small changes in magnetic field caused by the electrical activity of neurons, with potentially high spatial and temporal resolution.

Matched filters

The principle that the filter of the same frequency as the signal of interest provides maximal signal-to-noise ratio.

Matrix

A set of numbers arranged in a grid of rows and columns.

Mock Scanner

A simulated MRI scanner that does not have a magnetic field present, used for training research participants. Some mock scanners simulate scanner noises and measure subject head movement.

Model Factors

A set of hypothesized changes in BOLD activity associated with the manipulations of the independent variables or with other known sources of variability.

Morphometric

Relating to the measurement of shape.

MR Signal

The current measured in a detector coil following excitation and reception.

Multiple Comparison Problem

The increase in the number of false-positive results (i.e., Type I errors) with increasing number of statistical tests.  It si of particular consequence for voxelwise fMRI analyses, which may have many thousands of statistical tests. 

Mutual Information

In the context of MRI, the amount of information about one image that is provided by knowledge of another image. For example, T1 and T2 images have different contrast and thus are very different on measures of squared deviation. However, the intensity of a voxel in a T1 image can be predicted based on its intensity in a T2 image, so T1 and T2 images of the same brain would have high mutual information.