Neural Mechanisms of Animal Navigation
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Animals navigate to specific destinations for survival and reproduction. Notable examples include birds, fishes, and insects that are driven by their inherited motivation and acquired memory to migrate thousands of kilometers. The navigational abilities of these animals depend on their small and imprecise sensory organs and brains. Thus, understanding the mechanisms underlying animal navigation may lead to the development of novel tools and algorithms that can be used for more effective human-computer interactions in self-driving cars, autonomous robots and/or human navigation. How are such navigational abilities implemented in the animal brain? Neurons (i.e., nerve cells) that respond to external signals related to the animal’s direction and/or travel distance have been found in insects, and neurons that encode the animal’s place, direction, or speed have been identified in rats and mice. Although the research findings accumulated to date are not sufficient for a complete understanding of the neural mechanisms underlying navigation in the animal brain, they do provide key insights. In this review, we discuss the importance of neurobiological studies of navigation for engineering and computer science researchers and briefly summarize the current knowledge of the neural bases of navigation in model animals, including insects, rodents, and worms. In addition, we describe how modern engineering and computer technologies, such as virtual reality and machine learning, can help advance navigation research in animals.
KeywordsNeural computation Spatial information Biologically-inspired engineering
This work was supported by KAKENHI JP 16H06545 (K.D.K), 17H05985 (M. Sato), and 17H05975 (M. Sakura).
- 1.Kanzaki, R., Sugi, N., Shibuya, T.: Self-generated zigzag turning of Bombyx mori males during pheromone-mediated upwind walking. Zool. Sci. 9, 515–527 (1992)Google Scholar
- 2.Brower, L.P.: Monarch butterfly orientation: missing pieces of a magnificent puzzle. J. Exp. Biol. 199, 93–103 (1996)Google Scholar
- 15.Wehner, R., Labhart, T.: Polarisation vision. In: Warrant, E., Nilsson, D.-E. (eds.) Invertebrate Vision, pp. 291–348. Cambridge University Press, Cambridge (2006)Google Scholar
- 28.O’Keefe, J., Conway, D.H.: Hippocampal place units in the freely moving rat: why they fire where they fire. Exp. Brain Res. 31, 573–590 (1978)Google Scholar
- 39.Tanimoto, Y., Yamazoe-Umemoto, A., Fujita, K., Kawazoe, Y., Miyanishi, Y., Yamazaki, S.J., Fei, X., Busch, K.E., Gengyo-Ando, K., Nakai, J., Iino, Y., Iwasaki, Y., Hashimoto, K., Kimura, K.D.: Calcium dynamics regulating the timing of decision-making in C. elegans. eLife 6, 13819 (2017)Google Scholar
- 44.Sato, M., Kawano, M., Mizuta, K., Islam, T., Lee, M.G., Hayashi, Y.: Hippocampus-dependent goal localization by head-fixed mice in virtual reality. eNeuro 4, ENURO.0369-16.2017 (2017)Google Scholar
- 55.Yamazaki, S.J., Ikejiri, Y., Hiramatsu, F., Fujita, K., Tanimoto, Y., Yamazoe-Umemoto, A., Yamada, Y., Hashimoto, K., Hiryu, S., Maekawa, T., Kimura, K.D.: Experience-dependent modulation of behavioral features in sensory navigation of nematodes and bats revealed by machine learning. bioRxiv, 198879 (2017)Google Scholar