Selection of temporal models for event-related fMRI

Sophie Donnet; Marc Lavielle; Philippe Ciuciu; Jean Baptiste Paline

doi:10.1109/ISBI.2004.1398707

Selection of temporal models for event-related fMRI

Sophie Donnet
, Marc Lavielle
, Philippe Ciuciu
, Jean Baptiste Paline

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

Abstract

In functional Magnetic Resonance Imaging (fMRI), recent works have addressed the non parametric estimation of the Hemodynamic Response Function (HRF) under linearity and stationarity in time hypotheses. We propose to test a more flexible model that allows for the variation of the magnitude of the HRF with time. Under this model, the magnitude of the HRF evoked by a single event may vary with other occurrences of the same kind of event. This model is tested against a simpler model with a fixed magnitude. We develop a stochastic version of the EM algorithm to identify the magnitudes and the HRF. We also address the problem of model specification. It is usually assumed that every event type evokes a response. Our scheme uses a model selection approach which provides the best subset of event types maximizing the likelihood of the fMRI signal. Our methodology is exemplified by simulated and fMRI data.

Original language	English
Title of host publication	2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	Macro to Nano
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	992-995
Number of pages	4
ISBN (Print)	0780383885, 9780780383883
DOIs	https://doi.org/10.1109/ISBI.2004.1398707
Publication status	Published - 1 Jan 2004
Externally published	Yes
Event	2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, ISBI 2004 - Arlington, VA, United States Duration: 18 Apr 2004 → 18 Apr 2004

Publication series

Name	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume	1

Conference

Conference	2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, ISBI 2004
Country/Territory	United States
City	Arlington, VA
Period	18/04/04 → 18/04/04

Access to Document

10.1109/ISBI.2004.1398707

Cite this

Donnet, S., Lavielle, M., Ciuciu, P., & Paline, J. B. (2004). Selection of temporal models for event-related fMRI. In 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (pp. 992-995). (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISBI.2004.1398707

@inproceedings{94b20afad95b4988ba507196e28ef545,

title = "Selection of temporal models for event-related fMRI",

abstract = "In functional Magnetic Resonance Imaging (fMRI), recent works have addressed the non parametric estimation of the Hemodynamic Response Function (HRF) under linearity and stationarity in time hypotheses. We propose to test a more flexible model that allows for the variation of the magnitude of the HRF with time. Under this model, the magnitude of the HRF evoked by a single event may vary with other occurrences of the same kind of event. This model is tested against a simpler model with a fixed magnitude. We develop a stochastic version of the EM algorithm to identify the magnitudes and the HRF. We also address the problem of model specification. It is usually assumed that every event type evokes a response. Our scheme uses a model selection approach which provides the best subset of event types maximizing the likelihood of the fMRI signal. Our methodology is exemplified by simulated and fMRI data.",

author = "Sophie Donnet and Marc Lavielle and Philippe Ciuciu and Paline, \{Jean Baptiste\}",

year = "2004",

month = jan,

day = "1",

doi = "10.1109/ISBI.2004.1398707",

language = "English",

isbn = "0780383885",

series = "2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "992--995",

booktitle = "2004 2nd IEEE International Symposium on Biomedical Imaging",

note = "2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, ISBI 2004 ; Conference date: 18-04-2004 Through 18-04-2004",

}

Donnet, S, Lavielle, M, Ciuciu, P & Paline, JB 2004, Selection of temporal models for event-related fMRI. in 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 992-995, 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, ISBI 2004, Arlington, VA, United States, 18/04/04. https://doi.org/10.1109/ISBI.2004.1398707

Selection of temporal models for event-related fMRI. / Donnet, Sophie; Lavielle, Marc; Ciuciu, Philippe et al.
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. Institute of Electrical and Electronics Engineers Inc., 2004. p. 992-995 (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 1).

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

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AU - Lavielle, Marc

AU - Ciuciu, Philippe

AU - Paline, Jean Baptiste

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N2 - In functional Magnetic Resonance Imaging (fMRI), recent works have addressed the non parametric estimation of the Hemodynamic Response Function (HRF) under linearity and stationarity in time hypotheses. We propose to test a more flexible model that allows for the variation of the magnitude of the HRF with time. Under this model, the magnitude of the HRF evoked by a single event may vary with other occurrences of the same kind of event. This model is tested against a simpler model with a fixed magnitude. We develop a stochastic version of the EM algorithm to identify the magnitudes and the HRF. We also address the problem of model specification. It is usually assumed that every event type evokes a response. Our scheme uses a model selection approach which provides the best subset of event types maximizing the likelihood of the fMRI signal. Our methodology is exemplified by simulated and fMRI data.

AB - In functional Magnetic Resonance Imaging (fMRI), recent works have addressed the non parametric estimation of the Hemodynamic Response Function (HRF) under linearity and stationarity in time hypotheses. We propose to test a more flexible model that allows for the variation of the magnitude of the HRF with time. Under this model, the magnitude of the HRF evoked by a single event may vary with other occurrences of the same kind of event. This model is tested against a simpler model with a fixed magnitude. We develop a stochastic version of the EM algorithm to identify the magnitudes and the HRF. We also address the problem of model specification. It is usually assumed that every event type evokes a response. Our scheme uses a model selection approach which provides the best subset of event types maximizing the likelihood of the fMRI signal. Our methodology is exemplified by simulated and fMRI data.

U2 - 10.1109/ISBI.2004.1398707

DO - 10.1109/ISBI.2004.1398707

M3 - Conference contribution

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T3 - 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano

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T2 - 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, ISBI 2004

Y2 - 18 April 2004 through 18 April 2004

ER -

Selection of temporal models for event-related fMRI

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