Assumptions and Validations of Statistical Tests for Functional Neuroimaging

We contrast two statistical methods: three-dimensional cluster analysis and statistical parametric mapping. We show that three-dimensional cluster analysis is based on a neurobiological theory of the regulation of blood flow and, unlike statistical parametric mapping, carries a minimum of assumptions that are tested. Statistical parametric mapping is a formal approach, which is based on a multitude of assumptions of which the majority have not been validated. We also demonstrate that in practice three-dimensional cluster analysis has a reasonable balance between sensitivity and the probability of false positives, giving high reproducibility with data on e.g. colour discrimination.