title: Assumptions and validations of statistical tests for functional neuroimaging.
abstract: 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.
authors.affiliation: Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
authors.forename: P E
authors.initials: PE
authors.lastname: Roland
authors.forename: B
authors.initials: B
authors.lastname: Gulyás
mesh_terms: D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging* / Q000502:physiology*; D001931:Brain Mapping; D002560:Cerebrovascular Circulation; D016000:Cluster Analysis; D005189:False Positive Reactions; D006801:Humans; D015233:Models, Statistical; D012039:Regional Blood Flow; D015203:Reproducibility of Results; D014055:Tomography, Emission-Computed / Q000379:methods