How to determine a suitable threshold when using amplitude thresholding method for spike detection?
For threshold-based spike detection, the threshold defines your performance in the detection vs false alarm performance. That is to say, a lower threshold will improve your probability of detecting (smaller) spikes but eventually, some of the noise may be considered a spike, increasing the probability of a false alarm, detecing a spike where there is none. A common term for showing this trade-off is ROC.
Therefore, it is highly application-dependent how to choose the threshold. If you have a specific false alarm rate that is tolerable, you can use the noise distribution to determine the threshold that gives you the desired false alarm rate (refered to as the constant false alarm rate (CFAR) approach). Same is true if you have a tolerable missed detection rate (àla I need to find at least 99.99% of the spikes).
If not, you should consider the threshold a variable and do your evaluations as a function of the threshold. This allows you to pick a threshold that optimizes your final figure of merit.