Decomposition Techniques In Neuroscience
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M. De Vos, Lieven De Lathauwer and S. Van Huffel
Cognitive sciences try to understand the working of the brain. As the most important recording
techniques (Electroencephalogram and functional Magnetic Resonance Imaging) only measure a
combination of different active brain sources, Blind Source Separation (BSS) techniques have a
wide range of applications in this field. BSS aims at extracting individual brain processes.
The current state of the art of BSS in neuroscience will be discussed. This chapter aims at clarifying
why different problems are solved in different ways that reflect different assumptions. We
will explain some algorithms in detail. We will focus on Canonical Correlation Analysis (CCA),
Independent Component Analysis (ICA) and CPA (Canonical/Parallel Factor Analysis).
It will be shown how these algorithms can be applied to enhance brain research. We will highlight
the potential and limitations of current BSS techniques.
decomposition, neuroscience, ICA, CCA, CPA, EEG
Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium