Accurate estimation of the temporal correlations that exist in fMRI time-series is essential in order to avoid a high false positive rate. A common approach is to pre-whiten data using an AR(1)+white noise model. However, this approach proves insufficient for repetition times (TR) <1.5s. An alternative is to expand the set of covariance components included in the model (of serial correlations), as in the “FAST” option implemented by SPM12. Here, we show that this model can be used to accurately pre-whiten rapidly sampled data, and identify an upper bound on the parameterisation (i.e., number of covariance components) that precludes numerical overflow with ill-conditioned matrices. Such a model is important given the increasing use of rapid imaging techniques, such as multiband imaging. Using this technique, 18 components provided robust results with TR times ranging from 0.35s to 2.8s.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords