TTC post-processing is beneficial for functional MRI at low magnetic field: a comparative study at 1 T and 3 T

An iterative two-threshold analysis for single-subject functional MRI of the human brain

OBJECTIVES

Current thresholding strategies for the analysis of functional MRI (fMRI) datasets may suffer from specific limitations (e.g. with respect to the required smoothness) or lead to reduced performance for a low signal-to-noise ratio (SNR). Although a previously proposed two-threshold (TT) method offers a promising solution to these problems, the use of preset settings limits its performance. This work presents an optimised TT approach that estimates the required parameters in an iterative manner.

METHODS

The iterative TT (iTT) method is compared with the original TT method, as well as other established voxel-based and cluster-based thresholding approaches and spatial mixture modelling (SMM) for both simulated data and fMRI of a hometown walking task at different experimental settings (spatial resolution, filtering and SNR).

RESULTS

In general, the iTT method presents with remarkable sensitivity and good specificity that outperforms all conventional approaches tested except for SMM in a few cases. This also holds true for challenging conditions such as high spatial resolution, the absence of filtering, high noise level, or a low number of task repetitions.

CONCLUSION

Thus, iTT emerges as a good candidate for both scientific fMRI studies at high spatial resolution and more routine applications for clinical purposes.