Towards new model of neuronal growth: Comparison of models and tools for neuronal growth in vitro

Event Abstract Back to Event Towards new model of neuronal growth: Comparison of models and tools for neuronal growth in vitro Riikka Havela1*, Jugoslava Actimovic1, Tuomo Maki-Marttunen1 and Marja-Leena Linne1 1 Department of Signal Processing, Tampere University of Technology, Finland The structural organization of a neuronal network partly defines its functional capabilities. Thus, understanding how neurons self-organize and form networks is an important step towards understanding the structure-function relationship in neuronal networks. The simplified in vitro setup allows convenient control of parameters and observation of a growing neuronal network. It provides an ideal system for modeling [1] and, consequently, for studies of structure-function relationship. Previously, we compared two tools, Netmorph [2] and Cx3D [3], for modeling growth and structural changes in neuronal networks in vitro [4]. We concluded that both simulators can reproduce typical experimental values for network growth when phenomenological model of growth and graph theoretic analysis measures are used. The main difference between the tools is that NETMORPH implements computationally inexpensive models and is therefore more useful in theoretical studies. The advantage of Cx3D simulator is its flexibility. Cx3D is valuable when modeling a small number of neurons equipped with intracellular and extracellular chemical species. It may as well be useful for constructing multilevel models that incorporate cellular and network levels. In this work, we propose a slightly modified model of neuronal growth with carefully assessed morphologies. The effects of different model components and parameters will be assessed using Sholl analysis to characterize the growth of axons and dendrites. The model is simulated using both Cx3D and its recently published parallelized version, Cx3Dp. We apply standard graph theoretic measures and Sholl analysis (see Fig. 1) to analyze and quantitatively compare the obtained morphologies and network structures. We also use analysis methods for weighted networks to assess the effects of synapse numbers. Our future aim is to present generic models of neuronal growth with relevant features of both in vitro and in vivo experiments. Such models, when incorporated with neuronal activity and known homeostatic mechanisms such as those provided by astrocytes, will help to decipher the role of network structure in the development of activity. References: [1] Maheswaranathan N et al. Front Comput Neurosci. 2012, 6: 15. [2] Koene RA et al. Neuroinformatics. 2009, 7(3): 195-210. [3] Zubler F and Douglas R. Front Comput Neurosci. 2009, 3: 25 [4] Acimovic J et al. EURASIP J Bioinform Syst Biol. 2011, 2011: 616382 Keywords: computational neuroscience, neuronal growth, neuronal growth model, neuronal networks, morphology Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012. Presentation Type: Poster Topic: Neuroinformatics Citation: Havela R, Actimovic J, Maki-Marttunen T and Linne M (2014). Towards new model of neuronal growth: Comparison of models and tools for neuronal growth in vitro. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00118 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2013; Published Online: 27 Feb 2014. * Correspondence: Dr. Riikka Havela, Department of Signal Processing, Tampere University of Technology, Tampere, Finland, riikka.havela@tut.fi Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Riikka Havela Jugoslava Actimovic Tuomo Maki-Marttunen Marja-Leena Linne Google Riikka Havela Jugoslava Actimovic Tuomo Maki-Marttunen Marja-Leena Linne Google Scholar Riikka Havela Jugoslava Actimovic Tuomo Maki-Marttunen Marja-Leena Linne PubMed Riikka Havela Jugoslava Actimovic Tuomo Maki-Marttunen Marja-Leena Linne Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.