In your approach, we need recording the exact spike trains to use any metric on them. But there is a probabilistic way to predict the distance between spike trains. may we use probabilistic metric spaces to this prediction?
Somothink like this I was found immediatly for you question. See web link below.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2713191/
All that matters is that there is a meaningful measure of the distance between spike trains; this could be a probabilistic measure.
Dear Professor Houghton, thank you for responce. Actually there is a significant difference between a classical spike measure and the probabilistic one. that is the probabilistic metric on spike trains space may predict the distance between two unhappen spike trains and it may be more usefull. I'm trying to establish a probabilistic metric on spike train and theoritically I've almost finished it. I need a expert person like you to complete the idea.
I'm afraid I am not sure what you mean; do you mean that you have some generative model for the spike trains and you are trying to find the distribution of distances for the spike trains the model produces?
Yes. you are right. I'm trying to find the distribution of distances for the spike trains using the probabilistic metric spaces. In fact, the Idea is replacing distribution functions instead of non negative real numbers. It may produces the probability that the distance between two spike trains is less than a number.
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