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Low signal to noise ratio11/13/2023 Two classes of experiments might be undertaken, and calculating SNR for each differs slightly. Note that the SNR values we will discuss here in general depend upon the choice of input signal used by the experimenter - they thus characterise the combination of the system plus external stimulus, rather than being an intrinsic property of the system itself. Over the course of an experiment, a distribution of different stimuli (signals) will be presented, and a distribution of responses to each stimulus recorded. For the sake of choosing language we will examine SNR in a sensory system, although a motor system could be studied the same way.Ī sensory neuroscience experiment typically involves the collection of neural responses of some kind over repeated trials in which a particular stimulus signal is presented. 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. This can be quantified by the ratio of the variances of the event signal train and the 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. It has general applicability to the analysis of sensory discrimination (by nerve cells and by whole organisms) and to the performance of networks.Ī common use of SNR is to compare the quality of electrophysiological recordings containing events (for instance action potentials) recorded in the presence of noise. 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. What is signal-to-noise ratio (in the context of a neuroscience experiment)? 5 SNR measurements in neuroscience - some exemplars.1.2 Stimuli continuously varying in time.1 What is signal-to-noise ratio (in the context of a neuroscience experiment)?.
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