ArticleFrontiers in systems neuroscience2020
Influence of Autapses on Synchronization in Neural Networks With Chemical Synapses.
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 8 papers.
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Who cites it
8 citing papers in PubMed.
- Spike-timing-dependent plasticity offers delay-gated oscillatory potentiation for autaptic weights.Frontiers in neural circuits · 2025Article
- The Roles of Potassium and Calcium Currents in the Bistable Firing Transition.Brain sciences · 2023Article
- The Role of Potassium and Calcium Currents in the Bistable Firing Transition.bioRxiv : the preprint server for biology · 2023Article
- Bursting hierarchy in an adaptive exponential integrate-and-fire network synchronization.Biological cybernetics · 2022Article
- Control of noise-induced coherent oscillations in three-neuron motifs.Cognitive neurodynamics · 2022Article
- Robust spike timing in an excitable cell with delayed feedback.Journal of the Royal Society, Interface · 2021Article
- Correlation Analysis of Synchronization Type and Degree in Respiratory Neural Network.Computational intelligence and neuroscience · 2021Article
- Emergence of Neuronal Synchronisation in Coupled Areas.Frontiers in computational neuroscience · 2021Article
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Authors and funding
6 authors.
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Abstract
A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronization. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behavior. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behavior depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses.
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