Topographic time-frequency decomposition of the EEG.
Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.
Koenig
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T
Cuban Neuroscience Center, La Habana, Cuba.
Marti-Lopez
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F
Valdes-Sosa
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P
D000328:Adult; D000513:Alpha Rhythm; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000503:physiopathology*; D002648:Child; D004569:Electroencephalography; D004833:Epilepsy, Temporal Lobe / Q000175:diagnosis / Q000503:physiopathology*; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D008432:Mathematical Computing; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted; D012894:Sleep Stages / Q000502:physiology