Useful Papers - Physiology and fMRI
Summary: Glover et. al describe a fast and effective retrospective algorithm to identify physiological noise in raw data and remove it; the algorithm is based on sorting images based on their point in the cardiac and/or respiratory cycles. They show it to be more effective than a popular k-space correction program.
Summary: The group uses a retrospective gating method in real data to find voxels that are significantly affected by cardiac-cycle noise, to see if that noise affects parts of the brain worse than others. Unsurprisingly, the noise is found to be especially bad near major arteries, as well as near the sinus regions.
Summary: Presents a correction method (innovatively named DORK, thanks to our own Gary Glover) that operates using a navigator echo to correction off-resonance artifacts largely induced by respiration (see Van de Mooretele et. al, below). Can also be used with slightly reduced effectiveness without the navigator. Best for correcting global effects - less effect on cardiac, as those artifacts are more local.
Summary: A companion paper to Pfeuffer et. al above, this discusses the sources of those respiration-induced global frequency shifts. The authors examined data at 7T to mathematically model the changes in susceptibility and B0 induced by respiration, and describe a previously published mathematical model than can model those changes well.
Summary: Authors attempt to devise a method to help distinguish long-term gradual global changes - like those induced by a sudden temperature change and vasoconstriction, or those induced by gradual "kicking in" of a pharmacological agent - from focal changes, to enable use of those factors in studying global and local interactions. The method is simple and probably easily confounded, but low in calculation effort and straightforward.