Towards An Emergent Computational Model Of Axon Guidance
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1
University of Coimbra, Centre for Informatics and Systems, Portugal
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2
University of Coimbra, Center for Neuroscience and Cell Biology, Portugal
Axon guidance (AG) towards their target during embryogenesis or after injury is an important issue in the development of neuronal networks. During their growth, axons often face complex decisions that are difficult to understand when observing just a small part of the problem. In this work we propose a computational model of axon guidance based on activity-independent mechanisms that takes into account the most important aspects of axon guidance. This model may lead to a better understanding of the axon guidance problem in several systems (e.g. midline, optic pathway, olfactory system) as well as the general mechanisms involved.
The computational model that we propose is strongly based on the experimental evidences available from Neuroscience studies, and has a three-dimensional representation. The model includes the main elements (neurons, with soma, axon and growth cone; glial cells acting as guideposts) and mechanisms (attraction/repulsion guidance cues, growth cone adaptation, tissue-gradient intersections, axonal transport, changes in the growth cone complexity and a range of responses for each receptor).
The growth cone guidance is defined as a function that maps the receptor activation by ligands into a repulsive or attractive force. This force is then converted into a turning angle using spherical coordinates. A regulatory network between the receptors and the intracellular proteins is considered, leading to more complex and realistic behaviors. The ligand diffusion through the extracellular environment is modeled with linear or exponential functions. Furthermore, we include an optimization module based on a genetic algorithm that helps to optimize the model of a specific AG system. As a fitness function we consider the euclidean distance to the path observed in the native biological system.
Concerning experimentation, we have been studying one of the best characterized systems, the midline crossing of Drosophila commissural neuron axons. The computational model created allows describing to a great extent the behaviors that have been reported in the literature, both graphically and numerically, before and after midline crossing. In the future we plan to study how the developed model can help to understand the decisions performed by retinal axons at the optic chiasm. As evaluation measures the following parameters are considered: (i) the turning angles of the growth cone, (ii) the euclidean distance to what is observed in the native tissue and (iii) the importance of each guidance complex (pair receptor-ligand).
In conclusion, in our approach AG is an emergent behavior of the system as a whole, with realistic rules and elements that together could lead to the behaviors observed in Neurobiology experimental studies. A simulator based on this model is being developed, which can be used in the future by neuroscientists interested in a better comprehension of the axon guidance phenomenon.
Conference:
Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, 30 Sep - 2 Oct, 2009.
Presentation Type:
Poster Presentation
Topic:
Learning and plasticity
Citation:
Costa
RP,
Macedo
L,
Costa
E,
Malva
J and
Duarte
C
(2009). Towards An Emergent Computational Model Of Axon Guidance.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.neuro.10.2009.14.097
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Received:
27 Aug 2009;
Published Online:
27 Aug 2009.
*
Correspondence:
Rui P Costa, University of Coimbra, Centre for Informatics and Systems, Coimbra, Portugal, racosta@student.dei.uc.pt