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Time Series Analysis & Modelling



Andreas Galka 

State space modelling of time series in the neurosciences

Abstract:
In contemporary research in the neurosciences extensive spatiotemporal
data sets are recorded, reflecting the electromagnetical,  
metabolical or
chemical processes in neural assemblies, from the level of single  
cells to
the entire brain. Such data sets pose new challenges for quantitative
analysis. I will discuss how state-space modelling can be applied  
to this
situation, with particular emphasis on two aspects, namely dynamical
source estimation and independent component analysis.



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