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Assumptions and Validations of Statistical Tests for Functional Neuroimaging
Article first published online: 7 APR 2006
DOI: 10.1111/j.1460-9568.1996.tb01186.x
1460-9568/asset/cover.gif?v=1&s=f24cc0b5582a6f8af7d83eee00b2056f825c5624 "European Journal of Neuroscience")
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How to Cite
Roland, P. E. and Gulyas, B. (1996), Assumptions and Validations of Statistical Tests for Functional Neuroimaging. European Journal of Neuroscience, 8: 2232–2235. doi: 10.1111/j.1460-9568.1996.tb01186.x
Publication History
- Issue published online: 7 APR 2006
- Article first published online: 7 APR 2006
- Received 26 March 1996, accepted 17 June 1996
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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.