Signal-to-noise ratio and frequency analysis of continuous loop averaging deconvolution (CLAD) of overlapping evoked potentials

In this study, a frequency domain formulation of continuous loop averaging deconvolution (CLAD) of overlapping evoked potentials is developed and applied for the extraction of transient responses from recordings obtained at high stimulation rates. This formulation allows for a faster execution of CLAD by using fast Fourier transform algorithms. The frequency characteristics of the deconvolution filter depends exclusively on the stimulus sequence and determines whether the noncoherent noise is amplified or attenuated in different frequencies. A formula for calculating the signal-to-noise ratio (SNR) achieved by the deconvolution process is developed. The newly developed theory and the methodology is applied to the extraction of the auditory brainstem and middle latency responses using various sequences. The effects of the sequence used and the number of sweeps averaged in ongoing acquisition on SNR are examined by using single sweep recordings. The results verify the deconvolution theory and the methodology and show its limitations. Depending on the frequency characteristics of the sequence, the deconvolution process can amplify or attenuate the EEG noise. Proper selection of the stimulus sequence can increase the SNR enhancement obtained with conventional averaging.