Abstract
The hypothesis of multiple memory systems involved in different learning of navigation strategies has gained strong arguments through biological experiments. However, it remains difficult for experimentalists to understand how these systems interact. We propose a new computational model of selection between parallel systems involving cue-guided and place-based navigation strategies that allows analyses of selection switches between both control systems, while providing information that is not directly accessible in experiments with animals. Contrary to existing models of navigation, its module of selection is adaptive and uses a criterion which allows the comparison of strategies having different learning processes. Moreover, the spatial representation used by the place-based strategy is based on a recent hippocampus model. We illustrate the ability of this navigation model to analyze animal behavior in experiments in which the availability of sensory cues, together with the amount of training, influence the competitive or cooperative nature of their interactions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
White, N., McDonald, R.: Multiple parallel memory systems in the brain of the rat. Neurobiol. Learn Mem. 77, 125–184 (2002)
Doeller, C.F., King, J.A., Burgess, N.: Parallel striatal and hippocampal systems for landmarks and boundaries in spatial memory. Proc. Natl. Acad. Sci. USA 105(15), 5915–5920 (2008)
O’Keefe, J., Nadel, L.: The hippocampus as a cognitive map. Oxford University Press, Oxford (1978)
Hartley, T., Burgess, N.: Complementary memory systems: competition, cooperation and compensation. Trends Neurosci. 28(4), 169–170 (2005)
Carrillo-Mora, P., Magda, G., Abel, S.: Spatial memory: Theoretical basis and comparative review on experimental methods in rodents. Behav. Brain Res. 203(2), 151–164 (2009)
Rich, E., Shapiro, M.: Rat Prefrontal Cortical Neurons Selectively Code Strategy Switches. J. Neurosci. 29(22), 7208–7219 (2009)
Pearce, J., Roberts, A., Good, M.: Hippocampal lesions disrupt navigation based on cognitive maps but not heading vectors. Nature 396(6706), 75–77 (1998)
Dolle, L., Khamassi, M., Girard, B., Guillot, A., Chavarriaga, R.: Analyzing interactions between navigation strategies using a computational model of action selection. In: Freksa, C., Newcombe, N.S., Gärdenfors, P., Wölfl, S. (eds.) Spatial Cognition VI. LNCS (LNAI), vol. 5248, pp. 71–86. Springer, Heidelberg (2008)
Chavarriaga, R., Strosslin, T., Sheynikhovich, D., Gerstner, W.: A computational model of parallel navigation systems in rodents. Neuroinformatics 3(3), 223–242 (2005)
Uchibe, E., Doya, K.: Reinforcement learning with multiple heterogeneous modules: A framework for developmental robot learning. In: The 4th International Conference on Development and Learning, pp. 87–92 (2005)
Ujfalussy, B., Eros, P., Somogyvari, Z., Kiss, T.: Episodes in space: A modelling study of hippocampal place representation. In: Asada, M., Hallam, J.C.T., Meyer, J.-A., Tani, J. (eds.) SAB 2008. LNCS (LNAI), vol. 5040, pp. 123–136. Springer, Heidelberg (2008)
Stroesslin, T., Sheynikhovich, D., Chavarriaga, R., Gerstner, W.: Robust self-localisation and navigation based on hippocampal place cells. Neural. Net. 18(9), 1125–1140 (2005)
Martinet, L.E., Passot, J.B., Fouque, B., Meyer, J.A., Arleo, A.: Map-based spatial navigation: A cortical column model for action planning. In: Freksa, C., Newcombe, N.S., Gärdenfors, P., Wölfl, S. (eds.) Spatial Cognition VI. LNCS (LNAI), vol. 5248, pp. 39–55. Springer, Heidelberg (2008)
Burnod, Y.: Organizational levels of the cerebral cortex: an integrated model. Acta Biotheor. 39(3-4), 351–361 (1991)
Dijkstra, E.: A note on two problems in connection with graphs. Numer. Math. 1, 269–271, 269-270 (1959)
Girard, B., Filliat, D., Meyer, J., Berthoz, A., Guillot, A.: Integration of navigation and action selection functionalities in a computational model of cortico-basal-thalamo-cortical loops. Adapt. Behav. 13(2), 115–130 (2005)
Guazzelli, A., Corbacho, F., Bota, M., Arbib, M.: Affordances, motivation, and the world graph theory. Adapt. Behav. 6(3), 435–471 (1998)
Leising, K., Blaisdell, A.: Associative basis of landmark learning and integration in vertebrates. Comp. Cogn. Behav. Rev. 4, 80–102 (2009)
Martel, G., Blanchard, J., Mons, N., Gastambide, F., Micheau, J., Guillou, J.: Dynamic interplays between memory systems depend on practice: The hippocampus is not always the first to provide solution. Neuroscience 150(4), 743–753 (2007)
Chang, Q., Gold, P.E.: Switching memory systems during learning: changes in patterns of brain acetylcholine release in the hippocampus and striatum in rats. J. Neurosci. 23(7), 3001 (2003)
Botreau, F., Gisquet-Verrier, P.: Re-thinking the role of the dorsal striatum in egocentric/response strategy. Front. Behav. Neurosci. 4, 1–12 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dollé, L., Sheynikhovich, D., Girard, B., Ujfalussy, B., Chavarriaga, R., Guillot, A. (2010). Analyzing Interactions between Cue-Guided and Place-Based Navigation with a Computational Model of Action Selection: Influence of Sensory Cues and Training. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, JA., Mouret, JB. (eds) From Animals to Animats 11. SAB 2010. Lecture Notes in Computer Science(), vol 6226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15193-4_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-15193-4_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15192-7
Online ISBN: 978-3-642-15193-4
eBook Packages: Computer ScienceComputer Science (R0)