If you have a signal to noise ratio of 1:2, what will be the effect of averaging 64 responses?

Averaging multiple responses is a widely used technique in neurophysiological monitoring to enhance the quality of a signal, particularly in the presence of noise. When you have a signal to noise ratio (SNR) of 1:2, this indicates that the noise level is greater than the signal level.

By averaging 64 responses, you are effectively integrating multiple data points, which allows for more reliable signal detection. The principle behind this is that as you average more responses, the effects of random noise diminish, while the true signal remains relatively constant. Specifically, the noise reduces by the square root of the number of trials averaged, which in this scenario is the square root of 64.

Calculating that gives us a reduction of the noise level by a factor of 8, meaning the noise level reduces significantly while the signal remains the same. Originally, the SNR was 1:2, which you can also express as 1 / (2). When you reduce the noise by a factor of 8, the new noise level becomes 2 / 8 (or 0.25).

This results in a new SNR of 1 (the original signal) to 0.25 (the reduced noise), which