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 proceedingConference contributionAcademicpeer-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 languageEnglish
Title of host publication4th European Conference of the International Federation for Medical and Biological Engineering - ECIFMBE 2008
Pages705-708
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008 - Antwerp, Belgium
Duration: 23 Nov 200827 Nov 2008
Conference number: 4

Publication series

NameIFMBE Proceedings
Volume22
ISSN (Print)1680-0737

Conference

Conference4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008
Abbreviated titleECIFMBE 2008
Country/TerritoryBelgium
CityAntwerp
Period23/11/0827/11/08

Keywords

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

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