ArticleComputational and mathematical methods in medicine2012
Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.
Article in Computational and mathematical methods in medicine, 2012. 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.
- Astrocyte-Mediated Plasticity: Multi-Scale Mechanisms Linking Synaptic Dynamics to Learning and Memory.Cells · 2025Review
- Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics.Frontiers in cellular neuroscience · 2021Article
- Review
- A New Computational Model for Astrocytes and Their Role in Biologically Realistic Neural Networks.Computational intelligence and neuroscience · 2018Article
- Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh-Nagumo Neurons under Direction-Dependent Coupling.Frontiers in neurorobotics · 2018Article
- Energetic Constraints Produce Self-sustained Oscillatory Dynamics in Neuronal Networks.Frontiers in neuroscience · 2017Article
- Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.International journal of molecular sciences · 2016Review
- Robust synchronization of delayed chaotic FitzHugh-Nagumo neurons under external electrical stimulation.Computational and mathematical methods in medicine · 2012Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.
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Registered trials
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