A mathematically accurate angular regression model optimizes phase activation and yields additional physiological...

In functional magnetic resonance imaging (fMRI), it is important to observe the functioning brain as fast as possible and at as high of a spatial resolution as possible. Increased spatial and temporal speed results in voxels with increased noise relative to signal and contrast. There is much evidence to suggest that there is important biological information contained within the phase component of the fMRI signal. When the signal-to-noise ratio within a voxel is low, as when there is ultra-high resolution, the marginal statistical distribution of the phase is non-standard and difficult to work with. This non-standard marginal phase distribution at high signal-to-noise ratios is Normally distributed, but at low signal-to-noise ratios needs to be utilized for accurate modeling. In this work, phase-only activation will be computed directly from Lathi's mathematically correct non-Normal distribution, yielding additional physiological information to what is typically observed.