Single-trial extraction of cognitive evoked potentials by combination of third-order correlation and wavelet denoising.

The application of a recently proposed denoising implementation for obtaining cognitive evoked potentials (CEPs) at the single-trial level is shown. The aim of this investigation is to develop the technique of extracting CEPs by combining both the third-order correlation and the wavelet denoising methods. First, the noisy CEPs was passed through a finite impulse response filter whose impulse response is matched with the shape of the noise-free signal. It was shown that it is possible to estimate the filter impulse response on basis of a select third-order correlation slice (TOCS) of the input noisy CEPs. Second, the output from the third-order correlation filter is decomposed with bi-orthogonal splines at 5 levels. The CEPs is reconstructed by wavelet final approximation a5. We study its performance in simulated data as well as in cognitive evoked potentials of normal rat and Alzheimer's disease (AD) model rat. For the simulated data, the method gives a significantly better reconstruction of the single-trial cognitive evoked potentials responses in comparison with the simulated data. Moreover, with this approach we obtain a significantly better estimation of the amplitudes and latencies of the simulated CEPs. For the real data, the method clearly improves the visualization of single-trial CEPs. This allows the calculation of better averages as well as the study of systematic or unsystematic variations between trials.