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- I. Schießl,
M. Stetter, J. E. W. Mayhew, S. Askew, N. McLoughlin, J. B. Levitt, J. S.
Lund, and K. Obermayer. Blind separation of spatial signal patterns from
optical imaging records.
.
In ICA99 - International workshop on Idependent Component Analysis and
Blind Source Separation, pages 179-184, 1999.
(FTP Gzipped PostScript, 6 pages, 729 kb)
Optical imaging of intrinsic signals measures two-dimensional
neuronal activity patterns by detecting small activity-related changes in the
light reflectance of neural tissue. We test, to what extent blind source
separation methods, which are based on the spatial independence of different
signal components, are suitable for the separation of these neural-activity
related signal components from nonspecific background variations of the light
reflectance. Two ICA algorithms (Infomax and kurtosis optimization) and blind
source separation by extended spatial decorrelation are compared to each
other with respect to their robustness against sensor noise, and are applied
to optical recordings from macaque primary visual cortex. We find that
extended spatial decorrelation is superior to both the ICA algorithms and
standart methods, because it explicitely takes advantage of the spatial
smoothness of the intrinsic signal components.
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