Brain Topography

, Volume 2, Issue 1, pp 73-80

First online:

Data reduction of multichannel fields: Global field power and Principal Component Analysis

  • Wolfgang SkrandiesAffiliated withMax-Planck-Institute for Physiological and Clinical Research

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Electroencephalographic data recorded for topographical analysis constitute multidimensional observations, and the present paper illustrates methods of data analysis of multichannel recordings where components of evoked brain activity are identified quantitatively. The computation of potential field strength (Global Field Power, GFP) is used for component latency determination. Multivariate statistical methods like Principal Component Analysis (PCA) may be applied to the topographical distribution of potential values. The analysis of statistically defined components of visually elicited brain activity is illustrated with data sets stemming from different experiments. With spatial PCA the dimensionality of multichannel data is reduced to only three components that account for more than 90% of the variance. The results of spatial PCA relate to experimental conditions in a meaningful way, and this method may also be used for time segmentation of topographic potential maps series.


Visual Evoked Potential (VEP) Brain mapping Global Field Power (GFP) Multivariate statistics Principal Component Analysis (PCA) Spatial PCA Time segmentation