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How to find a shortcut within a city? Mental walk vs. mental model

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O'Malley,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Meilinger,  T
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

O'Malley, M., Bülthoff, H., & Meilinger, T. (2014). How to find a shortcut within a city? Mental walk vs. mental model. In A. Schütz, K. Drewing, & K. Gegenfurtner (Eds.), 56th Conference of Experimental Psychologists (TeaP 2014) (pp. 194). Lengerich, Germany: Pabst.


Cite as: http://hdl.handle.net/21.11116/0000-0001-341B-7
Abstract
Survey tasks such as finding novel shortcuts or pointing to distant, non-visible locations within cities or buildings seem to be limited to human navigators. We tested two conflicting explanations for survey tasks. In the mental walk hypothesis familiar routes are represented by hippocampal place cells. Each cell represents one route location and cells are successively activated while mentally travelling along this route. This process underlies location estimation of distant targets. Its duration depends on place cell number and therefore route length. Contrary, the mental model hypothesis assumes building a mental model of non-visible environment parts without mentally walking there. Model construction is piece-wise, one street after the other. Duration of distant location estimation depends on the number of streets, not their length. To test these predictions participants learned four unconnected routes through a virtual city by walking on an omnidirectional treadmill. We independently varied route length (120 vs. 360 virtual meters) and number of turns (2 vs. 6) and measured latency in pointing between route locations after learning. Both route length and number of turns increased pointing latency. Neither hypothesis can fully account for the data. Maybe multiple systems based on vision vs. bodily cues contributed independently.