A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data

C. W. Hesse; P. F. Buur; D. G. Norris

doi:10.1007/978-3-540-89208-3_168

A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data

C. W. Hesse
, P. F. Buur
, D. G. Norris

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

1 Citation (Scopus)

Abstract

This work presents a novel application of a subspace Wiener filtering approach to multi-echo functional magnetic resonance imaging (fMRI) data from a cognitive neuroscience experiment in order to extract task-related brain activity at each voxel. Subspace Wiener filtering maximizes the correlation of a linear combination of multiple echo time-series with the signal subspace spanned by a set of target waveforms, e.g., the condition dependent modeled hemodynamic response derived from the design matrix. Compared with existing echo combination methods against a single echo baseline, subspace Wiener filtering leads to an increased selective enhancement of the signal components reflecting task-related BOLD activation, and could be useful for pre-processing multi-echo fMRI data.

Original language	English
Title of host publication	4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008
Pages	705-708
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-540-89208-3_168
Publication status	Published - 2008
Externally published	Yes
Event	4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008 - Antwerp, Belgium Duration: 23 Nov 2008 → 27 Nov 2008 Conference number: 4

Publication series

Name	IFMBE Proceedings
Volume	22
ISSN (Print)	1680-0737

Conference

Conference	4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008
Abbreviated title	ECIFMBE 2008
Country/Territory	Belgium
City	Antwerp
Period	23/11/08 → 27/11/08

Keywords

Functional magnetic resonance imaging (fMRI)
Multi-echo fMRI
Neuroimaging
Wiener filtering
n/a OA procedure

Access to Document

10.1007/978-3-540-89208-3_168

Cite this

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title = "A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data",

abstract = "This work presents a novel application of a subspace Wiener filtering approach to multi-echo functional magnetic resonance imaging (fMRI) data from a cognitive neuroscience experiment in order to extract task-related brain activity at each voxel. Subspace Wiener filtering maximizes the correlation of a linear combination of multiple echo time-series with the signal subspace spanned by a set of target waveforms, e.g., the condition dependent modeled hemodynamic response derived from the design matrix. Compared with existing echo combination methods against a single echo baseline, subspace Wiener filtering leads to an increased selective enhancement of the signal components reflecting task-related BOLD activation, and could be useful for pre-processing multi-echo fMRI data.",

keywords = "Functional magnetic resonance imaging (fMRI), Multi-echo fMRI, Neuroimaging, Wiener filtering, n/a OA procedure",

author = "Hesse, \{C. W.\} and Buur, \{P. F.\} and Norris, \{D. G.\}",

year = "2008",

doi = "10.1007/978-3-540-89208-3\_168",

language = "English",

isbn = "9783540892076",

series = "IFMBE Proceedings",

pages = "705--708",

booktitle = "4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008",

note = "4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008, ECIFMBE 2008 ; Conference date: 23-11-2008 Through 27-11-2008",

}

Hesse, CW, Buur, PF & Norris, DG 2008, A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data. in 4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008. IFMBE Proceedings, vol. 22, pp. 705-708, 4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008, Antwerp, Belgium, 23/11/08. https://doi.org/10.1007/978-3-540-89208-3_168

A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data. / Hesse, C. W.; Buur, P. F.; Norris, D. G.
4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008. 2008. p. 705-708 (IFMBE Proceedings; Vol. 22).

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

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T1 - A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data

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AU - Norris, D. G.

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AB - This work presents a novel application of a subspace Wiener filtering approach to multi-echo functional magnetic resonance imaging (fMRI) data from a cognitive neuroscience experiment in order to extract task-related brain activity at each voxel. Subspace Wiener filtering maximizes the correlation of a linear combination of multiple echo time-series with the signal subspace spanned by a set of target waveforms, e.g., the condition dependent modeled hemodynamic response derived from the design matrix. Compared with existing echo combination methods against a single echo baseline, subspace Wiener filtering leads to an increased selective enhancement of the signal components reflecting task-related BOLD activation, and could be useful for pre-processing multi-echo fMRI data.

KW - Functional magnetic resonance imaging (fMRI)

KW - Multi-echo fMRI

KW - Neuroimaging

KW - Wiener filtering

KW - n/a OA procedure

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DO - 10.1007/978-3-540-89208-3_168

M3 - Conference contribution

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SN - 9783540892076

T3 - IFMBE Proceedings

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BT - 4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008

T2 - 4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008

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ER -

A subspace wiener filtering approach for extracting task-related brain activity from multi-echo fMRI Data

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Keywords

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