3D Spatial Analysis of fMRI Data on a Word Perception Task

  • Ingo R. Keck
  • Fabian J. Theis
  • Peter Gruber
  • Elmar W. Lang
  • Karsten Specht
  • Carlos G. Puntonet
Conference paper

DOI: 10.1007/978-3-540-30110-3_123

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3195)
Cite this paper as:
Keck I.R., Theis F.J., Gruber P., Lang E.W., Specht K., Puntonet C.G. (2004) 3D Spatial Analysis of fMRI Data on a Word Perception Task. In: Puntonet C.G., Prieto A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg

Abstract

We discuss a 3D spatial analysis of fMRI data taken during a combined word perception and motor task. The event – based experiment was part of a study to investigate the network of neurons involved in the perception of speech and the decoding of auditory speech stimuli. We show that a classical general linear model analysis using SPM does not yield reasonable results. With blind source separation (BSS) techniques using the FastICA algorithm it is possible to identify different independent components (IC) in the auditory cortex corresponding to four different stimuli. Most interesting, we could detect an IC representing a network of simultaneously active areas in the inferior frontal gyrus responsible for word perception.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ingo R. Keck
    • 1
  • Fabian J. Theis
    • 1
  • Peter Gruber
    • 1
  • Elmar W. Lang
    • 1
  • Karsten Specht
    • 2
  • Carlos G. Puntonet
    • 3
  1. 1.Institute of Biophysics, Neuro- and Bioinformatics GroupUniversity of RegensburgRegensburgGermany
  2. 2.Institute of MedicineResearch Center JülichJülichGermany
  3. 3.Departamento de Arquitectura y Tecnologia de ComputadoresUniversidad de Granada/ESIIGranadaSpain

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