Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. © 2011 Elsevier Ltd.

A neuron-astrocyte transistor-like model for neuromorphic dressed neurons

Pioggia G.;Ferro M.;
2011

Abstract

Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. © 2011 Elsevier Ltd.
Campo DC Valore Lingua
dc.authority.ancejournal NEURAL NETWORKS en
dc.authority.orgunit Istituto di Fisiologia Clinica - IFC en
dc.authority.people Valenza G. en
dc.authority.people Pioggia G. en
dc.authority.people Armato A. en
dc.authority.people Ferro M. en
dc.authority.people Scilingo E. P. en
dc.authority.people De Rossi D. en
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dc.contributor.appartenenza Istituto per la Ricerca e l'Innovazione Biomedica - IRIB - Sede Secondaria Messina *
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dc.date.firstsubmission 2025/12/04 11:30:50 *
dc.date.issued 2011 -
dc.date.submission 2025/12/04 11:30:50 *
dc.description.abstracteng Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. © 2011 Elsevier Ltd. -
dc.description.allpeople Valenza, G.; Pioggia, G.; Armato, A.; Ferro, M.; Scilingo, E. P.; De Rossi, D. -
dc.description.allpeopleoriginal Valenza G.; Pioggia G.; Armato A.; Ferro M.; Scilingo E.P.; De Rossi D. en
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dc.identifier.doi 10.1016/j.neunet.2011.03.013 en
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dc.subject.keywords Astrocyte -
dc.subject.keywords Neuron -
dc.subject.keywords Neuron-astrocyte interaction model -
dc.subject.keywords Synapse -
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dc.subject.singlekeyword Neuron *
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dc.title A neuron-astrocyte transistor-like model for neuromorphic dressed neurons en
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isi.description.abstracteng Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. (C) 2011 Elsevier Ltd. All rights reserved. *
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