Abstract
Astrocytes cover a plethora of roles supporting neurons in their maturation and regulating the concentrations of several ions and neurotransmitters. Moreover, astrocytes dysfunctions are, nowadays, suspected to have important implication in several brain diseases, as for example in epilepsy and Alzheimer’s disease. The astrocytes themselves are forming a network mediated by gap junctions. A loss of gap junctions between astrocytes has been connected with epilepsy. The aim of this study is to computationally test the influence of astrocytes connectivity in regulating activity in the neuronal network. To conduct the study, it has been used an in silico neuron-astrocyte model developed in our group. The model simulates the processes governing the communications between an astrocyte and a pre- and a postsynaptic neuron in the tripartite synapse, as well as between astrocytes through gap junction coupling. The modeled network comprises 250 neurons and 107 astrocytes. Three different astrocytic connectivity levels have been studied – representing 0, 2 and 4 gap junctions on average per astrocyte. Additionally, three different noise levels have been applied to the presynaptic terminal to simulate low, high and hyperactivity. Since the activation of astrocytes is driven by the activity of the neuronal network, the results showed that in case of low activity astrocytes were not activated and did not regulate neuronal activity. In case of high neuronal activity and hyperactivity, astrocytes showed an increased capability of downregulating neuronal activity when increasing the astrocytic connectivity. These results are in accordance with several in vivo experiments from different laboratories.
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Acknowledgment
This research has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713645. K. L. is funded by the Academy of Finland (decision no. 314647).
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Genocchi, B., Lenk, K., Hyttinen, J. (2020). Influence of Astrocytic Gap Junction Coupling on in Silico Neuronal Network Activity. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_58
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DOI: https://doi.org/10.1007/978-3-030-31635-8_58
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