Abstract
Among the different capabilities of animals, the formation of spatial memories is crucial for their life. Living beings able to move, constantly need to orient themselves in the environment to reach a target that might be not always visible. This chapter investigates the process of spatial memory formation as an essential ingredient for orientation in open and unstructured environments. Neural centres devoted to spatial memory and path integration were deeply investigated both in rats and different insect species like ants, bees and fruit flies. In this chapter a neural-inspired model for the formation of a spatial working memory is discussed considering some key elements of the insect neural centres involved, in particular the ellipsoid body of the central complex.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aradi, I., Barna, G., Erdi, P.: Chaos and learning in the olfactory bulb. Int. J. Intell. Syst. 10(1), 89–117 (1995)
Arena, P., Maceo, S., Patanè, L., Strauss, R.: A spiking network for spatial memory formation: towards a fly-inspired ellipsoid body model. In: The 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, USA, pp. 1–6, 4–9 Aug 2013. https://doi.org/10.1109/IJCNN2013.6706882
Arena, P., Mauro, G.D., Krause, T., Patanè, L., Strauss, R.: A spiking network for body size learning inspired by the fruit fly. In: The 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, USA, pp. 1–7, 4–9 Aug 2013. https://doi.org/10.1109/IJCNN.2013.6706883
Arena, P., Patanè, L., Strauss, R.: Motor learning and body size within an insect brain computational model. In: Proceedings of the Biomimetic and Biohybrid Systems—Third International Conference, Living Machines 2014, Milan, Italy, July 30–Aug 1 2014, pp. 367–369 (2014)
Bisch-Knaden, S., Wehner, R.: Local vectors in desert ants: context-dependent landmark learning during outbound and homebound runs. J. Comp. Physiol. 189, 181–187 (2003)
Borenstein, J., Everett, H., Feng, L.: Where am I? systems and methods for mobile robot positioning. Technical Report (1996). http://www-personal.umich.edu/johannb/Papers/pos96rep.pdf
Collett, M., Collett, T., Srinivasan, M.: Insect navigation: measuring travel distance across ground and through air. Curr. Biol. 16, R887–R890 (2006)
Cruse, H., Wehner, R.: No need for a cognitive map: decentralized memory for insect navigation. PLoS Comput. Biol. 7(3), 1–10 (2011)
Haferlach, T., Wessnitzer, J., Mangan, M., Webb, B.: Evolving a neural model of insect path integration. Adapt. Behav. 15, 273–287 (2007)
Hartmann, G., Wehner, R.: The ant’s path integration system: a neural architecture. Biol. Cybern. 73, 483–497 (1995)
Kahsai, L., Carlsson, M., Winther, A., Nassel, D.: Distribution of metabotropic receptors of serotonin, dopamine, GABA, glutamate, and short neuropeptide F in the central complex of Drosophila. Neuroscience 208, 11–26 (2012)
Kuntz, S., Poeck, B., Strauss, R.: Visual working memory requires permissive and instructive NO/cGMP signaling at presynapses in the Drosophila central brain. Curr. Biol. 27(5), 613–623 (2017)
Neuser, K., Triphan, T., Mronz, M., Poeck, B., Strauss, R.: Analysis of a spatial orientation memory in Drosophila. Nature 453, 1244–1247 (2008)
Ofstad, T.A., Zuker, C.S., Reiser, M.B.: Visual place learning in Drosophila melanogaster. Nature 474, 204–209 (2011)
Redish, A., Elga, A., Touretzky, D.: A coupled attractor model of the rodent head direction system. Netw. Comput. Neural Syst. 7(4), 671–685 (1996)
Seelig, J.D., Jayaraman, V.: Neural dynamics for landmark orientation and angular path integration. Nature 521(7551), 186–191 (2015). https://doi.org/10.1038/nature14446
Song, P., Wang, X.: Angular path integration by moving hill of activity: a spiking neuron model without recurrent excitation of the head-direction system. J. Neurosci. 25(4), 1002–1014 (2005)
Wehner, R.: Desert ant navigation: how miniature brains solve complex tasks. J. Comp. Physiol. A. 189, 579–588 (2003)
Wittmann, T., Schwegler, H.: Path integration—a network model. Biol. Cybern. 73, 569–575 (1995)
Wu, C., Xia, S., Fu, T., Wang, H., Chen, Y., Leong, D., Chiang, A., Tully, T.: Specific requirement of NMDA receptors for long-term memory consolidation in Drosophila ellipsoid body. Nat. Neurosci. 10, 1578–1586 (2007)
Young, J., Armstrong, J.: Structure of the adult central complex in Drosophila: organization of distinct neuronal subsets. J. Comp. Neurol. 518, 1500–1524 (2010)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 The Author(s)
About this chapter
Cite this chapter
Patanè, L., Strauss, R., Arena, P. (2018). Modelling Spatial Memory. In: Nonlinear Circuits and Systems for Neuro-inspired Robot Control. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-73347-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-73347-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73346-3
Online ISBN: 978-3-319-73347-0
eBook Packages: EngineeringEngineering (R0)