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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

4 Citaten (Scopus)

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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).

Originele taal-2	Engels
Titel	Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy
Redacteuren	S. Bittanti, A. Cenedese, S. Zampieri
Pagina's	9953-9958
DOI's	https://doi.org/10.3182/20110828-6-IT-1002.00763
Status	Gepubliceerd - 2011
Evenement	18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress) - Milano, Italië Duur: 28 aug. 2011 → 2 sep. 2011 Congresnummer: 18 http://www.ifac2011.org/

Congres

Congres	18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress)
Verkorte titel	IFAC 2011
Land/Regio	Italië
Stad	Milano
Periode	28/08/11 → 2/09/11
Ander	The 18th World Congress of the International Federation of Automatic Control (IFAC)
Internet adres	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 (editors), Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy (blz. 9953-9958) https://doi.org/10.3182/20110828-6-IT-1002.00763

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title = "Optimal experiment design for hypothesis testing applied to functional magnetic resonance imaging",

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).",

author = "X. Bombois and {Dekker, den}, A.J. and C.R. Rojas and H. Hjalmarsson and {Hof, Van den}, P.M.J.",

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

note = "18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress), IFAC 2011 ; Conference date: 28-08-2011 Through 02-09-2011",

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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 (redactie), Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy. blz. 9953-9958, 18th World Congress of the International Federation of Automatic Control (IFAC 2011 World Congress), Milano, Italië, 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. redactie / S. Bittanti; A. Cenedese; S. Zampieri. 2011. blz. 9953-9958.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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N2 - 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).

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, redacteurs, Proceedings of the 18th IFAC World Congress (IFAC 2011), 28 August - 2 September 2011, Milano, Italy. 2011. blz. 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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