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

doi:10.3182/20110828-6-IT-1002.00763

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 proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy
Editors	S. Bittanti, A. Cenedese, S. Zampieri
Pages	9953-9958
DOIs	https://doi.org/10.3182/20110828-6-IT-1002.00763
Publication status	Published - 2011
Event	18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress) - Milano, Italy Duration: 28 Aug 2011 → 2 Sep 2011 Conference number: 18 http://www.ifac2011.org/

Conference

Conference	18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress)
Abbreviated title	IFAC 2011
Country/Territory	Italy
City	Milano
Period	28/08/11 → 2/09/11
Internet address	http://www.ifac2011.org/

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10.3182/20110828-6-IT-1002.00763

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Bombois, X., Dekker, den, A. J., Rojas, C. R., Hjalmarsson, H., & Hof, Van den, P. M. J. (2011). Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging. In S. Bittanti, A. Cenedese, & S. Zampieri (Eds.), Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy (pp. 9953-9958) https://doi.org/10.3182/20110828-6-IT-1002.00763

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booktitle = "Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy",

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Bombois, X, Dekker, den, AJ, Rojas, CR, Hjalmarsson, H & Hof, Van den, PMJ 2011, Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging. in S Bittanti, A Cenedese & S Zampieri (eds), Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy. pp. 9953-9958, 18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress), Milano, Italy, 28/08/11. https://doi.org/10.3182/20110828-6-IT-1002.00763

Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging. / Bombois, X.; Dekker, den, A.J.; Rojas, C.R. et al.

Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy. ed. / S. Bittanti; A. Cenedese; S. Zampieri. 2011. p. 9953-9958.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - 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).

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Bombois X, Dekker, den AJ, Rojas CR, Hjalmarsson H, Hof, Van den PMJ. Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging. In Bittanti S, Cenedese A, Zampieri S, editors, Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy. 2011. p. 9953-9958 doi: 10.3182/20110828-6-IT-1002.00763

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

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