Accurate modeling of temporal correlations in rapidly sampled fMRI time series.

ABSTRACT: Rapid imaging techniques are increasingly used in functional MRI studies because they allow a greater number of samples to be acquired per unit time, thereby increasing statistical power. However, temporal correlations limit the increase in functional sensitivity and must be accurately accounted for to control the false-positive rate. A common approach to accounting for temporal correlations is to whiten the data prior to estimating fMRI model parameters. Models of white noise plus a first-order autoregressive process have proven sufficient for conventional imaging studies, but more elaborate models are required for rapidly sampled data. Here we show that when the "FAST" model implemented in SPM is used with a well-controlled number of parameters, it can successfully prewhiten 80% of grey

SUBMITTER: Corbin N 

PROVIDER: S-EPMC6175228 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature