Finite-size correlation behavior near a critical point: A simple metric for monitoring the state of a neural network.

@article{Trejo2022FinitesizeCB,
  title={Finite-size correlation behavior near a critical point: A simple metric for monitoring the state of a neural network.},
  author={Eyisto J. Aguilar Trejo and Daniel A. Martin and Dulara De Zoysa and Zac Bowen and Tom{\'a}s S. Grigera and Sergio A. Cannas and Wolfgang Losert and Dante R. Chialvo},
  journal={Physical review. E},
  year={2022},
  volume={106 5-1},
  pages={
          054313
        }
}
In this article, a correlation metric κ_{c} is proposed for the inference of the dynamical state of neuronal networks. κ_{C} is computed from the scaling of the correlation length with the size of the observation region, which shows qualitatively different behavior near and away from the critical point of a continuous phase transition. The implementation is first studied on a neuronal network model, where the results of this new metric coincide with those obtained from neuronal avalanche… 
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