What is signal-to-noise ratio (in the context of a neuroscience experiment)?
The signal-to-noise ratio allows us to quantify the size of the applied or controlled signal relative to fluctuations that are outside experimental control. It has general applicability to the analysis of sensory discrimination (by nerve cells and by whole organisms) and to the performance of networks. A common use of SNR is to compare the quality of electrophysiological recordings containing events (for instance action potentials) recorded in the presence of noise. This measure is used (although often just approximately by reading off an oscilloscope by eye) to decide whether a recording location is adequate to begin spike sorting, or whether to move the electrode on. This can be quantified by the ratio of the variances of the event signal train and the noise. Another application, which we will discuss in more detail, is the use of signal-to-noise ratio to characterise the reliability of neural information transmission. For the sake of choosing language we will examine SNR in a sensor
