Analysis of Spatio-temporal Patterns

Abstract

In the foregoing section we saw how spatio-temporal patterns can be built up from elementary spatial patterns, i.e. from the v’s. In the analysis of spatio-temporal patterns in nature, including those occurring in brain activities, we are quite often confronted with the reverse problem. As we have seen in Sect. 2.5, experiments may provide us with spatio-temporal patterns, such as those of the EEG and MEG, and then the question arises of whether these patterns are built up of simpler patterns from which we may gain insight into the underlying time-dependent dynamics. In this section we present two methods that allow us to perform such a decomposition. We start with a decomposition that has been used in EEG and MEG analysis and is also widely used in pattern recognition.1 KeywordsState VectorGeometric ApproachForegoing SectionPotential LandscapeComplex Order ParameterThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.