Abstract
This paper presents a model for the development of primitive nervous systems in a hydra-like animat controlled by a gene regulatory network. The gene regulatory network consists of structural genes that simulate the main cellular events during neural development at an abstract level, namely, cell division, cell migration, and axon growth, and regulatory genes that control the expression of the structural genes. The developmental model is evolved with an evolutionary algorithm to achieve the correct developmental order. After the genetically controlled neural development is completed, the connectivity and weights of the neural networks are further adapted to allow the animat for performing simple behaviors such as the food catching behavior of a hydra. Our preliminary results suggest that the proposed developmental model is promising for computational simulation of the evolution of neural development for understanding neural organization in biological organisms.
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References
Dellaert, D., Beer, R.D.: Toward an evolvable model of development for autonomous agent synthesis. In: Artificial Life IV, pp. 246–257 (1994)
Cangelosi, A., Nolfi, S., Parrisi, D.: Cell division and migration in a ’genotype’ for neural networks. Networks - Computational in Neural Systems 5, 479–515 (1994)
Dayan, P., Abbott, L.F.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge (2001)
Downing, K.L.: Supplementing evolutionary developmental systems with abstract models of neurogenesis. In: Genetic and Evolutionary Computation Conference, pp. 990–996 (2007)
Federici, D.: Evolving developing spiking neural networks. In: Congress on Evolutionary Computation, vol. 1, pp. 543–550 (2005)
Gewaltig, M.-O., Diesmann, M.: NEST (Neural Simulation Tool). Scholarpedia 2(4), 1430 (2007), http://www.nest-initiative.org/
Jones, B.H., Jin, Y., Sendhoff, B., Yao, X.: Evolving functional symmetry in a three dimensional model of an elongated organism. In: Artificial Life XI, pp. 305–312 (2008)
Kitano, H.: A simple model of neurogenesis and cell differentiation based on evolutionary large-scale chaos. Artificial Life 2(1), 79–99 (1995)
Psujek, S., Beer, R.D.: Developmental bias in evolution: Evolutionary accessibility of phenotypes in a model of evo-devo systems. Evolution and Development 10(3), 375–390 (2008)
Sanes, D.H., Reh, T., Harris, W.A.: Development of the Nervous System. Academic Press, Amsterdam (2006)
Schramm, L.: A model for nervous systems development controlled by a gene regulatory network. Diploma thesis, Technische Universität Darmstadt (2007)
Schwefel, H.-P.: Evolution and Optimum Search. John Wiley, Chichester (1994)
Steiner, T., Schramm, L., Jin, Y., Sendhoff, B.: Emergence of feedback in artificial gene regulatory networks. In: Congress on Evolutionary Computation, pp. 867–874. IEEE, Los Alamitos (2007)
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Jin, Y., Schramm, L., Sendhoff, B. (2009). A Gene Regulatory Model for the Development of Primitive Nervous Systems. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_6
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DOI: https://doi.org/10.1007/978-3-642-02490-0_6
Publisher Name: Springer, Berlin, Heidelberg
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