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. It's seems power law scaling $\lambda_k \propto k^{-\alpha}$ with $\alpha \approx 0.5$ is more accurate for a sub-sampled system of smaller 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. subsamples_0425-3t1.svg 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.