FMRI activation detection using a variant of Akaike information criterion

Abd Krim Seghouane

doi:10.1109/SSP.2012.6319669

FMRI activation detection using a variant of Akaike information criterion

Abd Krim Seghouane^*

^*Corresponding author for this work

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

7 Citations (Scopus)

Abstract

A fundamental question in functional MRI (fMRI) data analysis is to declare pixels either activated or non-activated with respect to the experimental design. A new statistical test for detecting activated pixels in fMRI data is proposed. The test is based on comparing the dimension of the parametric models fitted to the voxels fMRI time series data with and without controlled activation-baseline pattern. A corrected variant of the Akaike information criterion, is used for this comparison. This test has the advantage of not requiring any user-specified threshold to be estimated. The effectiveness of the proposed fMRI activation detection method is illustrated on real experimental data.

Original language	English
Title of host publication	2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Pages	233-236
Number of pages	4
DOIs	https://doi.org/10.1109/SSP.2012.6319669
Publication status	Published - 2012
Event	2012 IEEE Statistical Signal Processing Workshop, SSP 2012 - Ann Arbor, MI, United States Duration: 5 Aug 2012 → 8 Aug 2012

Publication series

Name	2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Conference

Conference	2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Country/Territory	United States
City	Ann Arbor, MI
Period	5/08/12 → 8/08/12

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10.1109/SSP.2012.6319669

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title = "FMRI activation detection using a variant of Akaike information criterion",

abstract = "A fundamental question in functional MRI (fMRI) data analysis is to declare pixels either activated or non-activated with respect to the experimental design. A new statistical test for detecting activated pixels in fMRI data is proposed. The test is based on comparing the dimension of the parametric models fitted to the voxels fMRI time series data with and without controlled activation-baseline pattern. A corrected variant of the Akaike information criterion, is used for this comparison. This test has the advantage of not requiring any user-specified threshold to be estimated. The effectiveness of the proposed fMRI activation detection method is illustrated on real experimental data.",

keywords = "Activation Detection, Functional MRI, corrected Akaike information criterion",

author = "Seghouane, {Abd Krim}",

year = "2012",

doi = "10.1109/SSP.2012.6319669",

language = "English",

isbn = "9781467301831",

series = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012",

pages = "233--236",

booktitle = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012",

note = "2012 IEEE Statistical Signal Processing Workshop, SSP 2012 ; Conference date: 05-08-2012 Through 08-08-2012",

}

Seghouane, AK 2012, FMRI activation detection using a variant of Akaike information criterion. in 2012 IEEE Statistical Signal Processing Workshop, SSP 2012., 6319669, 2012 IEEE Statistical Signal Processing Workshop, SSP 2012, pp. 233-236, 2012 IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, United States, 5/08/12. https://doi.org/10.1109/SSP.2012.6319669

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AU - Seghouane, Abd Krim

PY - 2012

Y1 - 2012

N2 - A fundamental question in functional MRI (fMRI) data analysis is to declare pixels either activated or non-activated with respect to the experimental design. A new statistical test for detecting activated pixels in fMRI data is proposed. The test is based on comparing the dimension of the parametric models fitted to the voxels fMRI time series data with and without controlled activation-baseline pattern. A corrected variant of the Akaike information criterion, is used for this comparison. This test has the advantage of not requiring any user-specified threshold to be estimated. The effectiveness of the proposed fMRI activation detection method is illustrated on real experimental data.

AB - A fundamental question in functional MRI (fMRI) data analysis is to declare pixels either activated or non-activated with respect to the experimental design. A new statistical test for detecting activated pixels in fMRI data is proposed. The test is based on comparing the dimension of the parametric models fitted to the voxels fMRI time series data with and without controlled activation-baseline pattern. A corrected variant of the Akaike information criterion, is used for this comparison. This test has the advantage of not requiring any user-specified threshold to be estimated. The effectiveness of the proposed fMRI activation detection method is illustrated on real experimental data.

KW - Activation Detection

KW - Functional MRI

KW - corrected Akaike information criterion

UR - http://www.scopus.com/inward/record.url?scp=84868244487&partnerID=8YFLogxK

U2 - 10.1109/SSP.2012.6319669

DO - 10.1109/SSP.2012.6319669

M3 - Conference contribution

SN - 9781467301831

T3 - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012

SP - 233

EP - 236

BT - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012

T2 - 2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Y2 - 5 August 2012 through 8 August 2012

ER -

FMRI activation detection using a variant of Akaike information criterion

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