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Oscillations and avalanches coexist in brain networks close to criticality

We propose a minimal and analytically tractable class of neural networks, the adaptive Ising class. By inferring the model’s parameters from resting-state brain activity recordings, we show that scale-specific oscillations and scale-free avalanches can coexist in resting brains close to a non-equilibrium critical point at the onset of self-sustained oscillations.

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Fig. 1: Coexistence of oscillations and avalanches in resting brain and sub-critical adaptive Ising model.


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This is a summary of: Lombardi, F. et al. Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. Nat. Comput. Sci. (2023).

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Oscillations and avalanches coexist in brain networks close to criticality. Nat Comput Sci 3, 194–195 (2023).

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