Information Flow in Ising Models on Brain Networks

Stramaglia, Sebastiano; Cortes, Jesús M.; Angelini, L.; Pellicoro, M.; Marinazzo, Daniele

doi:10.1007/978-3-319-08672-9_35

Cited by 1 publication

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“…We study the effect of interaction range on the morphology of neuron activity pattern. Several previous works on ising model has calculated nearest neighbor interaction at different temperature and found that it could depict the functional brain activity at criticality [ 21 , 27 , 54 ]. We have simulated a system of 2-D non- conserved ising model, far from equillibrium with Glauber dynamics considering a parameter that controls the coupling strength over interaction range and obtained patterns of neural activity represented as a domain showing the modularity of functional brain networks at far below and near criticality.…”

Section: Summary and Discussionmentioning

confidence: 99%

Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality

Gundh

Singh

2015

PLoS ONE

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We study the domain ordering kinetics in d = 2 ferromagnets which corresponds to populated neuron activities with both long-ranged interactions, V(r) ∼ r −n and short-ranged interactions. We present the results from comprehensive Monte Carlo (MC) simulations for the nonconserved Ising model with n ≥ 2, interaction range considering near and far neighbors. Our model results could represent the long-ranged neuron kinetics (n ≤ 4) in consistent with the same dynamical behaviour of short-ranged case (n ≥ 4) at far below and near criticality. We found that emergence of fast and slow kinetics of long and short ranged case could imitate the formation of connections among near and distant neurons. The calculated characteristic length scale in long-ranged interaction is found to be n independent (L(t) ∼ t 1/(n−2)), whereas short-ranged interaction follows L(t) ∼ t 1/2 law and approximately preserve universality in domain kinetics. Further, we did the comparative study of phase ordering near the critical temperature which follows different behaviours of domain ordering near and far critical temperature but follows universal scaling law.

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Section: Summary and Discussionmentioning

confidence: 99%