Effects of spatial and temporal correlation in general linear modeling of fMRI

Current functional magnetic resonance imaging (fMRI) analysis utilizes a false discover rate (FDR) based on the assumption of independent voxels. Our fMRI general linear model simulation accurately portrays the expected FDR. We hypothesis that spatial and temporal correlation reduces the sensitivity of the analysis. Moreover, the FDR methods become ineffective in properly diagnosing fMRI results.;We compared our model with no correlation to assess the effects of various levels of temporal and spatial correlation. Low levels of correlation that have very minimal changes in the simulated hemodynamic response function (HRF) produced similar expected results from using a FDR. High levels of correlations, levels that are realistic variations, produce results that undermine the effectiveness of using the FDR.;An increased temporal and spatially correlation of fMRI HRFs reduces the validity of the expected FDR approaches. fMRI image analysis should account for repeated stimulus and adjacent brain activity.