Ch8 - Signal, Noise, and Preprocessing of fMRI Data Flashcards
blood-oxygenation-level-dependent (BOLD) contrast
differences in signal on t2*-weighted images as a function of the amount of deoxygenated hemoglobin
preprocessing
computational procedures that are applied to fMRI data following image reconstruction but before statistical analysis
- intended to reduce variability in data not associated with experimental task
- preparation for statistical testing
signal
meaningful changes in some quantity
- fMRI: incl. changes in intensity associated with the BOLD response across a series of t2* images
noise
nonmeaningful changes in some quantity
Signal-to-Noise ratio (SNR)
relative strength of a signal compared to other sources of variability in data
raw SNR
ratio between MR signal intensity associated with the sample (brain) and thermal noise that is measured outside the sample
contrast-to-noise ratio (CNR)
magnitude of the intensity difference between different quantities divided by variability of their measurement
voxel-wise analysis
evaluation of statistical test at the level of individual voxels
region-of-interest (ROI) analysis
evaluations of hypotheses about the functional properties of brain regions
- often chosen to reflect a priori distinctions within the brain
functional signal-to-noise ratio (functional SNR)
ratio between the intensity of signal associated with changes in brain function and the variability in the data due to all sources of noise
functional resolution
ability to map measured physiological variation to underlying mental processes
partial volume effect
combination, within voxel, of signal contributions from 2+ distinct tissue types or functional regions
spatial extent
number of active voxels within a cluser of activation
susceptibility artifacts
signal losses on T2* -dependent images due to magnetic field inhomogeneities in regions with air/air adjacent tissue
sinuses
- air filled cavaties in the skull
- long venous channels that form the primary draining system for the brain
power spectrum
representation of the strenght of different frequency components within a signal
- Fourier transform converts a signal into its power spectrum
thermal noise
fluctuations in MR signal intensity over space or time that are caused by the thermal motion of electrons within the sample or scanner hardware
system noise
fluctuations in MR signal intensity over space or time that are caused by imperfect functioning of the scanner hardware
scanner drift
slow changes in voxel intensity over time
(part of system noise)
physiological noise
fluctuations in MR signal intensity over space and time due to physiological activity of the human body
- motion, respiration, cardiac activity, metabolic reactions
aliasing
the sampling of a signal at a rate insufficent to resolve the highest frequencies that are present
- energy at those frequencies become artifically expressed at lower frequencies, distorting the measured signal