Evaluation of statistical inference on empirical resting state fMRI.

ABSTRACT: Modern statistical inference techniques may be able to improve the sensitivity and specificity of resting state functional magnetic resonance imaging (rs-fMRI) connectivity analysis through more realistic assumptions. In simulation, the advantages of such methods are readily demonstrable. However, quantitative empirical validation remains elusive in vivo as the true connectivity patterns are unknown and noise distributions are challenging to characterize, especially in ultra-high field (e.g., 7T fMRI). Though the physiological characteristics of the fMRI signal are difficult to replicate in controlled phantom studies, it is critical that the performance of statistical techniques be evaluated. The SIMulation EXtrapolation (SIMEX) method has enabled estimation of bias with asymptotically con

SUBMITTER: Yang X 

PROVIDER: S-EPMC5826557 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature