Computational modeling of neuron-astrocyte interactions: Evolution, reproducibility, comparability and future development of models

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    Astrocyte research has turned out to be a fascinating and popular research field with two groups of researchers having opposite opinions about the importance of astrocytes in brain information processing and plasticity [1–3]. We believe that computational modeling of the biophysics of neuron-astrocyte interactions can greatly help address the dilemma.We have therefore, as the first ones, characterized, categorized, and evaluated in detail more than a hundred published computational models of single astrocytes, astrocyte networks, neuron-astrocyte synapses, and neuron-astrocyte networks [4] as well as studied the reproducibility and comparability of some of the models [5]. Based on this knowledge and additional experimental findings, we have constructed and implemented new neuron-astrocyte synapse models [6]. In this study, we propose to gather the state-of-the-art experimental and computational knowledge to help guide the future astrocyte research. Two of the most important challenges in experimental work on astrocytes are the lack of selective pharmacological tools and the partially contradictory results obtained in in vivo and in vitro studies [1–3]. In computational studies on astrocyte, the most important challenges are the creationof new models without clear explanation how they differ from the previously published models and what new predictions the models make [4]. Furthermore, combining unclearly given model details in the publications with nonexistent online model implementations make the reproducibility and comparability studies as well as the development of previously published models impossible, or at least difficult [4, 5]. We want to emphasize the importance of using common description formats for defining the models in the publications and description languages for exchanging the models through online repositories. Our overall goal is to develop both detailed and reduced models of neuron-astrocyte interactions for different brain areas, allowing additional testing and clarification of the controversies observed in experimental wet-lab studies [1–3]. Only through systematic integration of in vivo, in vitro, and in silicodata, using reproducible science approach, are we be able to understand how astrocytes may contribute to brain information processing and plasticity.

    1. Bazargani N, Attwell D. Astrocyte calcium signaling: the third wave. Nat Neurosci 2016, 19(2), 182–189.

    2. Fiacco TA, McCarthy KD. Multiple lines of evidence indicate that gliotransmission does not occur under physiological conditions. J Neurosci 2018, 38(1), 3–13.

    3. Savtchouk I, Volterra A. Gliotransmission: beyond black-and-white. J Neurosci 2018, 38(1), 14–25.

    4. Manninen T, Havela R, Linne ML. Computational models for calcium-mediated astrocyte functions. Front Comput Neurosci 2018, 12, 14.

    5. Manninen T, Havela R, Linne ML. Reproducibility and comparability of computational models for astrocyte calcium excitability.Front Neuroinform 2017, 11, 11.

    6. Havela R, Manninen T, Saudargiene A, Linne ML. Modeling neuron-astrocyte interactions: towards understanding synaptic plasticity and learning in the brain.13th International Conference on Intelligent Computing (ICIC 2017) published in Intelligent Computing Theories and Application, Part II, Lecture Notes in Computer Science 10362, eds. D.-S. Huang et al., 157–168, Liverpool, UK, 07.-10.08.2017.
    Original languageEnglish
    Pages (from-to)68-68
    JournalBMC Neuroscience
    Issue numberSuppl 2
    Publication statusPublished - 2018
    Event27th Annual Computational Neuroscience Meeting (CNS*2018) - Seattle, United States
    Duration: 13 Jul 201818 Jul 2018


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