Independent component analysis of high-resolution imaging data identifies distinct functional domains

@article{Reidl2007IndependentCA,
  title={Independent component analysis of high-resolution imaging data identifies distinct functional domains},
  author={J{\"u}rgen Reidl and Jens Starke and David B. Omer and Amiram Grinvald and Hartwig Spors},
  journal={NeuroImage},
  year={2007},
  volume={34},
  pages={94-108}
}
In the vertebrate brain external stimuli are often represented in distinct functional domains distributed across the cortical surface. Fast imaging techniques used to measure patterns of population activity record movies with many pixels and many frames, i.e., data sets with high dimensionality. Here we demonstrate that principal component analysis (PCA) followed by spatial independent component analysis (sICA), can be exploited to reduce the dimensionality of data sets recorded in the… CONTINUE READING
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