July 31, 2025Open Access

Is the cortical dynamics ergodic? A numerical study in partially symmetric networks of spiking neurons

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MAIN FINDING: Slow dynamics emerge in spiking neuron networks due to partial symmetry in synaptic connectivity.
KEY EVIDENCE: Strong excitatory self-coupling results in long-lived fluctuations and multiple equilibrium states.
APPROACH: The study employs numerical simulations to analyze dynamics in balanced networks of spiking neurons.
SIGNIFICANCE: Findings may provide insights into the persistent memory effects in cortical networks and their collective behavior.

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Implication

Numerical study shows slow dynamics and broken ergodicity in spiking neuron networks with partial synaptic symmetry, indicating new equilibrium states.

Cite This Study

Tixidre et al. (2025) studied this question.

synapsesocial.com/papers/689a0c65e6551bb0af8cf864 https://doi.org/10.1101/2025.07.28.666831

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Implication

Numerical study shows slow dynamics and broken ergodicity in spiking neuron networks with partial synaptic symmetry, indicating new equilibrium states.

Is the cortical dynamics ergodic? A numerical study in partially symmetric networks of spiking neurons

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Discussion

Implication

Cite This Study

Is the cortical dynamics ergodic? A numerical study in partially symmetric networks of spiking neurons

Key Points

Discussion

Implication

Cite This Study

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