Advantages and disadvantages of a fast fMRI sequence in the context of EEG-fMRI investigation of XXXX @entity1 : A realistic simulation study.

@entity1 @entity302 @entity3628 @entity2996
UNASSIGNED: EEG-fMRI is an established technique to allow mapping BOLD changes in response to interictal discharges recorded in the EEG of @entity302 @entity1 . Traditional fMRI experiments rely on an @entity2996 ( @entity2996 ) sequence with a time resolution given by its time-to-repetition (TR) of ~2s. Recently, multiple fast fMRI sequences have been developed to get around the limited temporal resolution of the @entity2996 sequence, and achieved a TR in the 100ms range or lower. One such sequence is called Magnetic Resonance EncephaloGraphy (MREG). Its high temporal resolution should offer increased detection sensitivity and statistical power in the context of @entity302 studies and in fMRI experiments in general. The aim of this work was to investigate the advantages and disadvantages offered by MREG. This was done by superimposing artificial event-related BOLD responses on @entity2996 and MREG background signals, from 5 @entity302 @entity1 , that were free of @entity302 discharges (spikes) on simultaneously recorded EEG. These functional datasets simulated different spiking rates and hemodynamic response amplitudes, and were analyzed with the commonly used @entity3628 ( @entity3628 ) with the canonical hemodynamic response function (HRF) as a fixed model of the response. Robustness to violation of the assumptions of the @entity3628 was additionally assessed with similar simulations using variable spike-to-spike response amplitudes and 8 non-canonical HRFs. Consistent with previous work, MREG yields higher maximum statistical t-values than @entity2996 , but our simulations showed these statistics to be inflated, as the false positive rate at a standard threshold was high. At thresholds set to appropriately control specificity, @entity2996 showed better true positive rate and larger cluster size than MREG. However, the lack of an appropriate calibration of the amplitude of the responses across the sequences precludes definitive judgment on their relative sensitivity. In addition, we show that a mismatch between the assumed and actual HRF impairs more MREG detection performance, but that @entity2996 is more affected by non-modeled spike-to-spike variations of response amplitude. Filtering-out physiological noise, which is not aliased at the fast sampling rate of MREG, and the modeling of temporal autocorrelation are advantageous in increasing the detection power of MREG. This simulation study 1) warrants care when interpreting statistical t-values from fast fMRI sequences, 2) proposes thresholds for valid inferences and processing methods for maximal sensitivities, and 3) demonstrates the relative robustness/susceptibility of MREG and @entity2996 to violation of the @entity3628 's assumptions.
