ArticleFrontiers in systems neuroscience2020
Hopf Bifurcation in Mean Field Explains Critical Avalanches in Excitation-Inhibition Balanced Neuronal Networks: A Mechanism for Multiscale Variability.
Article in Frontiers in systems neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 38 citations in OpenAlex.
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- Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance.Cognitive neurodynamics · 2023Article
- Quasiuniversal scaling in mouse-brain neuronal activity stems from edge-of-instability critical dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Less is more: wiring-economical modular networks support self-sustained firing-economical neural avalanches for efficient processing.National science review · 2022Article
- Neuronal Population Transitions Across a Quiescent-to-Active Frontier and Bifurcation.Frontiers in physiology · 2022Article
- Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks.PLoS computational biology · 2022Article
- Long range temporal correlations (LRTCs) in MEG-data during emerging psychosis: Relationship to symptoms, medication-status and clinical trajectory.NeuroImage. Clinical · 2021Article
- Gamma Oscillations Facilitate Effective Learning in Excitatory-Inhibitory Balanced Neural Circuits.Neural plasticity · 2021Article
- Hopf Bifurcation in Mean Field Explains Critical Avalanches in Excitation-Inhibition Balanced Neuronal Networks: A Mechanism for Multiscale Variability.Frontiers in systems neuroscience · 2020Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Cortical neural circuits display highly irregular spiking in individual neurons but variably sized collective firing, oscillations and critical avalanches at the population level, all of which have functional importance for information processing. Theoretically, the balance of excitation and inhibition inputs is thought to account for spiking irregularity and critical avalanches may originate from an underlying phase transition. However, the theoretical reconciliation of these multilevel dynamic aspects in neural circuits remains an open question. Herein, we study excitation-inhibition (E-I) balanced neuronal network with biologically realistic synaptic kinetics. It can maintain irregular spiking dynamics with different levels of synchrony and critical avalanches emerge near the synchronous transition point. We propose a novel semi-analytical mean-field theory to derive the field equations governing the network macroscopic dynamics. It reveals that the E-I balanced state of the network manifesting irregular individual spiking is characterized by a macroscopic stable state, which can be either a fixed point or a periodic motion and the transition is predicted by a Hopf bifurcation in the macroscopic field. Furthermore, by analyzing public data, we find the coexistence of irregular spiking and critical avalanches in the spontaneous spiking activities of mouse cortical slice
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