Robust spatial navigation in a robot inspired by chemotaxis in Caenorhabditis elegans

Adaptive Behavior

Volumn 6, Issue 3-4, 1998, Pages 393-410

  Morse, Thomas M ^a   Lockery, Shawn R ^a   Ferrée, Thomas C ^a  

^a UNIVERSITY OF OREGON   (United States)

Author keywords

Chemotaxis; Nematode; Neural network; Phototaxis; Robot; Robustness

Indexed keywords

EID: 0032325787     PISSN: 10597123     EISSN: None     Source Type: Journal    
DOI: 10.1177/105971239800600303     Document Type: Article

References (20)

1. Bargmann, C. I. (1993). Genetic and cellular analysis of behavior in C. elegans. Annual Review of Neuroscience, 16, 47-71.
2. Bargmann, C. I., Hartwieg, E., & Horvitz, H. R. (1993). Odorant-selective genes and neurons mediate olfaction in C. elegans. Cell, 74, 515-527.
3. Bargmann, C. I., & Horvitz, H. R. (1991). Chemosensory neurons with overlapping functions direct chemotaxis to multiple chemicals in C. elegans. Neuron, 7, 729-742.
4. Bell, W. J. (1991). Searching behavior: The behavioural ecology of finding resources. London: Chapman and Hall.
5. Berg, H. C., & Brown, D. A. (1972). Chemotaxis in Escherichia coli analyzed by three-dimensional tracking. Nature, 239, 500-504.
6. Coburn, C. M., & Bargmann, C. I. (1996). A putative cyclic nucleotide-gated channel is required for sensory development and function in C. elegans. Neuron, 17, 695-706.
7. Culotti, J. G., & Russell, R. L. (1978). Osmotic avoidance defective mutants of the nematode caenorhabditis elegans. Genetics, 90, 243-256.
8. Davis, R. E., & Stretton, A. O. W. (1989). Signaling properties of Ascaris motorneurons: Graded active responses, graded synaptic transmission, and tonic transmitter release. Journal of Neuroscience, 9, 415-425.
9. Ferrée, T. C., Marcotte, B. A., & Lockery, S. R. (1997). Neural network models of chemotaxis in the nematode Caenorhabditis elegans. Advances in Neural Information Processing Systems, 9, 55-61.
10. Ferrée, T. C., & Lockery, S. R. (1998). Computational rules for chemotaxis in the nematode C. elegans. Manuscript submitted for publication.
11. Goodman, M. B., Hall, D. H., Avery, L., & Lockery, S. R. (1998). Active currents regulate sensitivity and dynamic range in C. elegans neurons. Neurons, in press.
12. Gould, J. L. (1986). The local map of honeybees: Do insects have cognitive maps? Science, 232, 861-863.
13. Hirose, S. (1993). Biologically inspired robots: Snake-like locomotors and manipulators. Oxford: Oxford University Press.
14. Masters, T. (1995). Advanced algorithms for neural networks: A C++ sourcebook. New York: Wiley.
15. Rieke, F., Warland, D., de Ruyter van Steveninck, R., & Bialek, W. (1997). Spikes: Exploring the neural code. Cambridge, MA: MIT Press.
16. Schmidt-Koenig, K., & Schlichte, H. J. (1972). Homing in pigeons with impaired, vision. Proceedings of the National Academy of Sciences of the United States of America, 69, 2446-2447.
17. Schone, H. (1984). Spatial orientation: The spatïal control of behavior in animals and man. Princeton: Princeton University Press.
18. Ward, S. (1973). Chemotaxis by the nematode Caenorhabditis elegans: Identification of attractants and analysis of the response by use of mutants. Proceedings of the National Academy of Sciences of the United States of America, 70, 817-821.
19. White, J. G., Southgate, E., Thompson, J. N., & Brenner, S. (1986). The structure of the nervous system of C. elegans. Philosophical Transactions of the Royal Society of London, 314, 1-340.
20. Worst, R., & Linnemann, R. (1996). Construction and operation of a snake-like robot. In Proceedings of IEEE International Joint Symposia on Intelligence and Systems. Los Alamitos, CA: IEEE Computer Society Press. Thomas M. Morse Thomas M. Morse received a B.S. in physics from Oberlin College and an M.S. and Ph.D. in physics from the University of Colorado at Boulder. He is a research associate at the University of Oregon in the Institute of Neuroscience. Research interests include neural networks and their embodiment in organisms and robots. Thomas C. Ferrée Thomas C. Ferrée is a research associate in the Institute of Neuroscience at the University of Oregon. He received a B.S. in physics at the University of Florida and a Ph.D. in theoretical physics at the University of Colorado. Current research interests include dynamical properties of biological and artificial neural networks, rule extraction from optimized neural networks, and applications to robotics.