ArticleFrontiers in computational neuroscience2018
Beta-Rhythm Oscillations and Synchronization Transition in Network Models of Izhikevich Neurons: Effect of Topology and Synaptic Type.
Article in Frontiers in computational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 31 citations in OpenAlex.
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- Synchronization and oscillation behaviors of excitatory and inhibitory populations with spike-timing-dependent plasticity.Cognitive neurodynamics · 2023Article
- Long-range connections are crucial for synchronization transition in a computational model of Drosophila brain dynamics.Scientific reports · 2022Article
- Phase synchronization and measure of criticality in a network of neural mass models.Scientific reports · 2022Article
- Phase transitions in biology: from bird flocks to population dynamics.Proceedings. Biological sciences · 2021Article
- Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling.Frontiers in computational neuroscience · 2020Article
- A Mathematical Model for the Signal of Death and Emergence of Mind Out of Brain in Izhikevich Neuron Model.Open access Macedonian journal of medical sciences · 2019Article
- Spike-Timing-Dependent Plasticity With Axonal Delay Tunes Networks of Izhikevich Neurons to the Edge of Synchronization Transition With Scale-Free Avalanches.Frontiers in systems neuroscience · 2019Article
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2 authors at 1 institution in 1 country.
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Abstract
Despite their significant functional roles, beta-band oscillations are least understood. Synchronization in neuronal networks have attracted much attention in recent years with the main focus on transition type. Whether one obtains explosive transition or a continuous transition is an important feature of the neuronal network which can depend on network structure as well as synaptic types. In this study we consider the effect of synaptic interaction (electrical and chemical) as well as structural connectivity on synchronization transition in network models of Izhikevich neurons which spike regularly with beta rhythms. We find a wide range of behavior including continuous transition, explosive transition, as well as lack of global order. The stronger electrical synapses are more conducive to synchronization and can even lead to explosive synchronization. The key network element which determines the order of transition is found to be the clustering coefficient and not the small world effect, or the existence of hubs in a network. These results are in contrast to previous results which use phase oscillator models such as the Kuramoto model. Furthermore, we show that the patterns of synchronization changes when one goes to the gamma band. We attribute such a change to the change in the refractory period of Izhikevich neurons which changes significantly with frequency.
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