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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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. https://doi.org/10.1007/978-3-540-30110-3_123
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DOI: https://doi.org/10.1007/978-3-540-30110-3_123
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