Event Abstract Back to Event Gradient based axon growth modelling of different cell types with specific growth features in the spinal cord of hatchling Xenopus tadpole Abul Kalam Al Azad1*, Roman Borisyuk1, Stephen R Soffe2 and Alan Roberts2 1 University of Plymouth, School of Computing and Mathematics, United Kingdom 2 University of Bristol, School of Biology, United Kingdom It is imperative to understand how simple basic mechanisms can allow primary functioning neuronal circuits to develop. To explore the 'functional connectome', we investigate anatomy and electrophysiology of young hatchling Xenopus tadpole's spinal cord. Our bottom-up approach to modelling of neuronal connectivity is based on developmental process of axon growth - we develop a gradient-based mathematical model for axon growth. It is known that in the developing developing vertebrate spinal cord, axons grow under influence of chemical morphogenes released from the dorsal roof plate ('BMP'), ventral floor plate ('Shh') and hindbrain region ('Wnt'). Distribution of these guidance molecules along the spinal cord set up a gradient field which steer the axons in appropriate locations and thus ensure formation of proper connections. The model of axon growth includes a fixed environment of the governing gradients and seven parameters describing the sensitivity of axon to different guidance molecules. Sensitivity parameters are specific for axons of each cell-type and also they are specific for the direction of axon growth (either to head or tail). A stochastic optimization programming technique is implemented to determine the values of these parameters for each cell-type and each direction of axon growth. The cost function provides a fitting of the model to the experimental measurements of axons and takes into account the projection of the axon to the Dorso-Ventral axis as well as the axon tortuisity. The model successfully generates axons of both commissural and non-commissural neurons which include stimulus receiving sensory neurons, sensory infomation processing interneurons and motorneurons. We model axons of seven types of spinal neurons believed to be involved in swimming and struggling behaviour of tadpole. Each neuron has a different axon growth feature, e.g., commissural neurons grow axons ventrally on the same side of the spinal cord at first and turn longitudinally on the other (contralateral) side of the spinal cord and non-commissural neurons grow their axons on the same (ipsilateral) side of spinal cord. This gradient based axon growth will in fact lead to bilogical reconstruction of the connectome of the tadpole's spinal cord. Keywords: computational neuroscience Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Computational neuroscience Citation: Azad A, Borisyuk R, Soffe S and Roberts A (2011). Gradient based axon growth modelling of different cell types with specific growth features in the spinal cord of hatchling Xenopus tadpole. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00064 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: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Abul Kalam Al Azad, University of Plymouth, School of Computing and Mathematics, Plymouth, United Kingdom, abul.azad@plymouth.ac.uk 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 Abul Kalam Al Azad Roman Borisyuk Stephen R Soffe Alan Roberts Google Abul Kalam Al Azad Roman Borisyuk Stephen R Soffe Alan Roberts Google Scholar Abul Kalam Al Azad Roman Borisyuk Stephen R Soffe Alan Roberts PubMed Abul Kalam Al Azad Roman Borisyuk Stephen R Soffe Alan Roberts 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.