Converting spectral evoked-to-background ratio into time-domain signal-to-noise ratio - validation for high frequency...

$N$ -Interval Fourier Transform Analysis ( $N$ -FTA) allows for spectral separation of an evoked target signal from uncorrelated background activity. It computes the frequency-dependent evoked-to-background ratio (EBR). The developed method allows for conversion of the spectral EBR into expected values for improvement of signal-to-noise ratio with progressing sweep count. Our study presents the mathematical basis for this conversion along with a validation for simulated and recorded data. The major findings are: •Three factors enter the calculus of the expected signal-to-noise ratio (SNR): the ratio of durations of the single sweep cycle and the evoked response window, the mean EBR in the spectral target band, and the sweep count. By conversion of all factors to dB, the expected SNR is defined by their sum.•The two fundamental theories governing the improvement of SNR with increasing sweep count, the law of large numbers and the uncertainty principle of signal processing, deliver identical results.•Conversion of EBR to expected SNR was successfully validated by simulated and recorded data and can be applied to all types of evoked data.•A median sweep count of about 2000 (range approximately 600 to 6000) is required for extracting an HFO response at an SNR of 10dB.