Network based neuronunit tests and data to inform the construction of such tests.

[russelljjarvis]

For the ICON lab hackathon it is desirable for some data to be digitised to inform network wide sciunit tests. I propose measuring multivariate spike distance (a-synchrony), Spike Train Distance. Data for entrorhinal cortex at the bottom of this paper: https://www.sciencedirect.com/science/article/pii/S0165027007002671 It would be great if someone who needs a task could digitize it.

In the future it might be desirable to make multivariate transfer entropy tests too.

[russelljjarvis]

In a previous ICON lab meeting it was proposed that we could use parietal lobe CV data as network dynamic test, however, these CV properties pertain to single unit recordings all over the parietal lobe. Reference: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743683/. In in pers comm communications at the ICON lab, it was pointed out that CV is more a measure of individual neuronal activity (although CV may also reflect both intrinsic firing properties and how influenced a neuron was by other neurons).

I wonder if the intention of using this test is to create a comparison between a distribution of experimental observed CVs, on a per simulated cell basis? Or would we just pool all the spike times from different neurons in sub-populations from the network together, and measure the aggregate CV for different subpopulations? Both seem feasible.

[rgerkin]

I don't think the CV data was meant as a network test, but it is a good data to use with the CV tests you have already created for single neurons.

[russelljjarvis]

Yes, makes sense.