Wavelet transforms and surrogate data for electroencephalographic spike and seizure localization

Wavelet transforms are used to analyze electroencephalographic data recorded from individual subdural electrodes and 2-D electrode grids in direct contact with the brain. Surrogate data techniques are used to filter noise and resolve structure in the data. Spike and seizure detection from individual electrodes with wavelet transforms are compared with windowed Fourier transforms. Wavelet transforms are a powerful means to identify epileptiform activity such as spikes from such data and also ofter a method to localize the foci of epileptic seizures from electrode grids.