Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging
2011 (English)In: Proceedings of the 18th IFAC World Congress, 2011, 9953-9958 p.Conference paper (Refereed)
Hypothesis testing is a classical methodology of making decisions using experimental data. In hypothesis testing one seeks to discover evidence that either accepts or rejects a given null hypothesis H0. The alternative hypothesis H1 is the hypothesis that is accepted when H0 is rejected. In hypothesis testing, the probability of deciding H1 when in fact H0 is true is known as the false alarm rate, whereas the probability of deciding H1when in fact H1is true is known as the detection rate (or power) of the test. It is not possible to optimize both rates simultaneously. In this paper, we consider the problem of determining the data to be used for hypothesis testing that maximize the detection rate for a given false alarm rate. We consider in particular a hypothesis test which is relevant in functional magnetic resonance imaging (fMRI).
Place, publisher, year, edition, pages
2011. 9953-9958 p.
optimal experiment design; detection; hypothesis testing
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-72582DOI: 10.3182/20110828-6-IT-1002.00763ScopusID: 2-s2.0-84866745348OAI: oai:DiVA.org:kth-72582DiVA: diva2:488372
IFAC 18th World Congress. Milano, Italy. August 28th - September 2nd, 2011
QC 201204102012-02-012012-01-312012-04-10Bibliographically approved