Subsampling miniscope data

Random subsets of the neurons are chosen for analysis. The results are compared to original system and among different sub-sample sizes.

The errorbars are calculated from the standard deviation of 8 random subsets for each given size.

Boltzmann learning is performed for each random sub sample for the model parameters, $h_i$ and $J_{i,j}$. The specific heat curves of the resulted models are calculated and as shown below. The criticality condition ($T\approx 1.0$) appears pretty robust to sub sampling where only a portion of the neurons from a large network is observed.