Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging

X. Bombois, A.J. Dekker, den, C.R. Rojas, H. Hjalmarsson, P.M.J. Hof, Van den

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)

Abstract

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 H1 when in fact H1 is 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 geiven false alarm rate. We consider in particular a hypothesis test which is relevant in functional magnetic resonance imaging (fMRI).
Original languageEnglish
Title of host publicationProceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy
EditorsS. Bittanti, A. Cenedese, S. Zampieri
Pages9953-9958
DOIs
Publication statusPublished - 2011
Event18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress) - Milano, Italy
Duration: 28 Aug 20112 Sep 2011
Conference number: 18
http://www.ifac2011.org/

Conference

Conference18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress)
Abbreviated titleIFAC 2011
CountryItaly
CityMilano
Period28/08/112/09/11
Internet address

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