5. Localized Cluster Enhancement: TFCE revisited with valid error control

COEX 

Cluster-size inference is one of the most popular approaches in neuroimaging analysis but has been criticized for its dependence on an arbitrary (but important) cluster-forming threshold. Threshold-Free Cluster Enhancement (TFCE) was proposed in Smith (2009) with the aim of 1) decreasing the arbitrariness of the cluster-forming threshold and 2) being more sensitive to brain activation. Here we will show that TFCE does not achieve these aims. First, TFCE introduces more free parameters into the model than cluster-size inference, making it more dependent on researchers' choices. Second, the large clusters of TFCE, often mistakenly interpreted voxel-wise, actually hamper interpretation as the spatial specificity paradox increases. We will show, using recent advances in multiple testing, that cluster-size inference is a more robust way of doing neuroimaging analyses.