An instruction language for self-construction in the context of neural networks

Frontiers in Computational Neuroscience

Volumn 5, Issue , 2011, Pages

  Zubler, Frederic ^a   Hauri, Andreas ^a   Pfister, Sabina ^a   Whatley, Adrian M ^a   Cook, Matthew ^a   Douglas, Rodney ^a  

^a Institute of Neuroinformatics Zurich   (Switzerland)

Author keywords

Cortex; Development; Neural growth; Self construction; Self organization; Simulation

Indexed keywords

CODES (SYMBOLS);

CORTEX; DEVELOPMENT; NEURAL GROWTH; SELF ORGANIZATIONS; SIMULATION;

COMPLEX NETWORKS;

CELL MATURATION; DIFFERENTIATION; HUMAN; HUMAN EXPERIMENT; LANGUAGE; NERVOUS SYSTEM; NERVOUS SYSTEM DEVELOPMENT; PRECURSOR;

EID: 84959570590     PISSN: None     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2011.00057     Document Type: Article

References (58)

1. Alon, U. (2006). An Introduction to Systems Biology: Design Principles of Biological Circuits. Boca Raton, FL: Chapman & Hall/CRC.
2. Berg, J. M., Tymoczko, J. L., and Stryer, L. (2011). Biochemistry, 7th Edn. New York, NY: W. H. Freeman Publishers.
3. Binzegger, T., Douglas, R. J., and Martin, K. A. C. (2007). Stereotypical bouton clustering of individual neurons in cat primary visual cortex. J. Neurosci. 27, 12242-12254.
4. Bock, D. D., Lee, W.-C. A., Kerlin, A. M., Andermann, M. L., Hood, G., Wetzel, A. W., Yurgenson, S., Soucy, E. R., Kim, H. S., and Reid, R. C. (2011). Network anatomy and in vivo physiology of visual cortical neurons. Nature 471, 177-182.
5. Boers, E., Kuiper, H., Happel, B., and Sprinkhuizen-Kuyper, I. (1993). "Designing modular artificial neural networks," in Proceedings of Computing Science in the Netherlands ed. H. A. Wijshoff (Amsterdam: Stichting Mathematisch Centrum), 87-96.
6. Butler, Z., Kotay, K., Rus, D., and Tomita, K. (2002). "Generic decentralized control for a class of selfreconfigurable robots," in Proceedings of the 2002 IEEE International Conference on Robotics and Automation, ICRA 2002, Washington, DC
7. Campbell, D. S., and Holt, C. E. (2001). Chemotropic responses of retinal growth cones mediated by rapid local protein synthesis and degradation. Neuron 32, 1013-1026.
8. Cangelosi, A., Nolfi, S., and Parisi, D. (1994). Cell division and migration in a ‘genotype’ for neural networks. Netw. Comput. Neural Syst. 5, 497-515.
9. Cook, M., Rothemund, P. W., and Winfree, E. (2004). "Self-assembled circuit patterns," in DNA Computing, 9th International Workshop on DNA Based Computers, Vol. 2943, eds, J. Chen and J. H. Reif (Madison, WI: Springer-Verlag), 91-107.
10. Davis, L., Dou, P., DeWit, M., and Kater, S. B. (1992). Protein synthesis within neuronal growth cones. J. Neurosci. 12, 4867-4877.
11. Doursat, R. (2008). "Organically grown architectures: creating decentralized, autonomous systems by embryomorphic engineering," in Organic computing, Chapter 8, ed. R. P. Würtz, (Springer-Verlag), 167-200
12. Eggenberger, P. (2001). Axonal growth in evolutionary neurogenesis. Artif. Life Robot. 5, 137-141.
13. Freitas, Jr, R. A., and Merkle, R. C. (2004). Kinematic Self-Replicating Machines. Landes Bioscience. Cambridge, MA: MIT Press.
14. Fuss, H., Dubitzky, W., Downes, C. S., and Kurth, M. J. (2005). Mathematical models of cell cycle regulation. Brief. Bioinformatics 6, 163-177.
15. Graham, T. G. W., Tabei, S. M. A., Dinner, A. R., and Rebay, I. (2010). Modeling bistable cell-fate choices in the drosophila eye: qualitative and quantitative perspectives. Development 137, 2265-2278.
16. Gruau, F., Ratajszczak, J.-Y., and Wiber, G. (1995). A neural compiler. Theor. Comput. Sci. 141, 1-52.
17. Grueber, W. B., Yang, C.-H., Ye, B., and Jan, Y.-N. (2005). The development of neuronal morphology in insects. Curr. Biol. 15, R730-R738.
18. Halley, J. D., and Winkler, D. A. (2008). Consistent concepts of self-organization and self-assembly. Complexity 14, 10-17.
19. Hinchey, M. G., Dai, Y.-S., Rouff, C. A., Rash, J. L., and Qi, M. (2007). "Modeling for NASA autonomous nano-technology swarm missions and model-driven autonomic computing," in Advanced Information Networking and Applications (AINA07) Niagara Falls: IEEE Computer Society, 250-257.
20. Huang, S., Guo, Y.-P., May, G., and Enver, T. (2007). Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Dev. Biol. 305, 695-713.
21. Jian, F., and Yugeng, X. (1997). Neural network design based on evolutionary programming. Artif. Intell. Eng. 11, 155-161.
22. Karlebach, G., and Shamir, R. (2008). Modelling and analysis of gene regulatory networks. Nat. Rev. Mol. Cell Biol. 9, 770-780.
23. Kiddie, G., McLean, D., Ooyen, A. V., and Graham, B. (2005). Biologically plausible models of neurite outgrowth. Prog. Brain Res. 147, 67-80.
24. Kitano, H. (1990). Designing neural networks using genetic algorithms with graph generation system. Complex Syst. J. 4, 461-476.
25. Kitano, H. (1995). A simple model of neurogenesis and cell differentiation based on evolutionary large-scale chaos. Artif. Life 2, 79-99.
26. Koene, R. A., Tijms, B., van Hees, P., Postma, F., de Ridder, A., Ramakers, G. J. A., van Pelt, J., and van Ooyen, A. (2009). NETMORPH: a framework for the stochastic generation of large scale neuronal networks with realistic neuron morphologies. Neuroinformatics 7, 195-210.
27. Kolch, W. (2005). Coordinating ERK/MAPK signalling through scaffolds and inhibitors. Nat. Rev. Mol. Cell Biol. 6, 827-837.
28. Levine, M., and Davidson, E. H. (2005). Gene regulatory networks for development. Proc. Natl. Acad. Sci. U.S.A. 102, 4936-4942.
29. Locasale, J. W., and Chakraborty, A. K. (2008). Regulation of signal duration and the statistical dynamics of kinase activation by scaffold proteins. PLoS Comput. Biol. 4, e1000099. doi:10.1371/journal.pcbi.1000099
30. Markram, H. (2006). The blue brain project. Nat. Rev. Neurosci. 7, 153-160.
31. Maskery, S., and Shinbrot, T. (2005). Deterministic and stochastic elements of axonal guidance. Annu. Rev. Biomed. Eng. 7, 187-221.
32. Montell, D. J. (2008). Morphogenetic cell movements: diversity from modular mechanical properties. Science 322, 1502-1505.
33. Nagpal, R. (2002). "Programmable selfassembly using biologically-inspired multiagent control," in Proceedings in 1st Intl Joint Conf. on Autonomous Agents and Multiagent Systems: Part 1, Bologna, 418-425.
34. Nolfi, S. (2003). "Evolution and learning in neural networks," in Hand-book of brain theory and neural networks, 2nd Edn, ed. M. A. Arbib (Cambridge, MA: MIT Press), 415-418.
35. Polleux, F., Morrow, T., and Ghosh, A. (2000). Semaphorin 3A is a chemoattractant for cortical apical dendrites. Nature 404, 567-573.
36. Pratt, S. C., Sumpter, D. J. T., Mallon, E. B., and Franks, N. R. (2005). An agent-based model of collective nest choice by the ant Temnothorax albipennis. Anim. Behav. 70, 1023-1036.
37. Rakic, P. (1988). Specification of cerebral cortical areas. Science 241, 170-176.
38. Rakic, P. (1995). A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution. Trends Neurosci. 18, 383-388.
39. Roth, F., Siegelmann, H., and Douglas, R. J. (2007). The self-construction and -repair of a foraging organism by explicitly specified development from a single cell. Artif. Life 13, 347-368.
40. Rothemund, P. W. K., Papadakis, N., and Winfree, E. (2004). Algorithmic self-assembly of DNA Sierpinski triangles. PLoS Biol. 2, e424. doi:10.1371/journal.pbio.0020424
41. Rust, A., Adams, R., George, S., and Bolouri, H. (1996). Artificial Evolution: Modeling the Development of the Retina. Technical report. Engineering Research and Development Centre, University of Hertfordshire, Hatfield.
42. Sanchez-Soriano, N., Tear, G., Whitington, P., and Prokop, A. (2007). Drosophila as a genetic and cellular model for studies on axonal growth. Neural Dev. 2, 9.
43. Schlitt, T., and Brazma, A. (2007). Current approaches to gene regulatory network modelling. BMC Bioinformatics 8(Suppl. 6), S9. doi:10.1186/1471-2105-8-S6-S9
44. Schramm, L., Jin, Y., and Sendhoff, B. (2011). "Emerged coupling of motor control and morphological development in evolution of multi-cellular animats," in Lecture Notes in Computer Science, Vol. 5777, Advances in Artificial Life. Darwin Meets von Neumann. 10th European Conference, ECAL 2009, eds G. Kampis, I. Karsai, and E. Szathmáry (Budapest: Springer), 27-34.
45. Seung, H. S. (2011). Neuroscience: towards functional connectomics. Nature 471, 170-172.
46. Sims, K. (1994). Evolving 3D morphology and behavior by competition. Artif. Life 1, 353-372.
47. Toffoli, T. (2000). What You Always Wanted to Know about Genetic Algorithms but were Afraid to Hear. Available at: arXiv:nlin/0007013v1 [nlin.AO].
48. Turing, A. M. (1952). The chemical basis of morphogenesis. Philos. Trans. R. Soc. B 237, 37-72.
49. Tyson, J. J. (1991). Modeling the cell division cycle: cdc2 and cyclin interactions. Proc. Natl. Acad. Sci. U.S.A. 88, 7328-7332.
50. Vaario, J., and Shimohara, K. (1997). "Synthesis of developmental and evolutionary modeling of adaptive autonomous agents," in ICANN ’97: Proceedings of the 7th International Conference on Artificial Neural Networks, eds W. Gerstner, A. Germond, M. Hasler, and J.-D. Nicoud, (London, Springer-Verlag), 721-726.
51. van Ooyen, A. (2011). Using theoretical models to analyse neural development. Nat. Rev. Neurosci. 12, 311-326.
52. Vohradsky, J. (2001). Neural network model of gene expression. FASEB J. 15, 846-854.
53. Von Neumann, J., and Burks, A. W. (1966). Theory of Self-Reproducing Automata. Urbana: University of Illinois Press.
54. Wen, Z., and Zheng, J. Q. (2006). Directional guidance of nerve growth cones. Curr. Opin. Neurobiol. 16, 52-58.
55. Whitesides, G. M., and Grzybowski, B. (2002). Self-assembly at all scales. Science 295, 2418-2421.
56. Yang, L., Garbe, D. S., and Bashaw, G. J. (2009). A frazzled/DCC-dependent transcriptional switch regulates midline axon guidance. Science 324, 944-947.
57. Zubler, F., and Douglas, R. (2009). A framework for modeling the growth and development of neurons and networks. Front. Comput. Neurosci. 3:25. doi: 10.3389/neuro.10.025.2009
58. Zubler, F., and Douglas, R. (2010). "An instruction language for the explicit programming of axonal growth patterns," in WCCI 2010 IEEE World Congress on Computational Intelligence, Barcelona.