Abstract
This study examined how navigators of large-scale environmental spaces come up with survey estimates of distant targets. Participants learned a route through a virtual city by walking it multiple times in one direction on an omnidirectional treadmill. After learning, they were teleported to intersections along the route and pointed to multiple other locations. Locations were always queried in chunks of related trials relative to a participant’s current position, either to all locations route forwards or all locations route backwards. For their first pointing, participants took twice as long as for the later pointings and latency correlated with the number of intersections to the target, which was not the case for later pointings. These findings are inconsistent with reading out coordinates from a cognitive map but fit well with constructive theories which suggest that participants integrated locations between their current location and the target along the learned path. Later pointings to adjacent intersections within a chunk of trials continued this process using the previous estimation. Additionally, in first pointings participants’ estimates were quicker and more accurate when targets were located route forwards than route backwards. This route direction effect shows that the long-term memory employed in generating survey estimates must be directed – either in form of a directed graph or a combination of a directed route layer and an undirected survey layer.
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Notes
- 1.
When including target sequence (albeit not decisive on the introduced models) into the analysis all reported effects remained significant. There was no significant three-way-interaction which could have changed one of the reported effects, and no interaction with route direction. The analysis showed an effect of target sequence and its interaction with pointing number. Here participants were much quicker and accurate when their first pointing was away from their current location towards the visible neighbor intersection.
- 2.
If later estimates were based on estimates of previous targets, the route direction effect for later pointings should invert in the case of towards pointing (see examples in Fig. 2, right). Initially the most distant location must be constructed followed by closer targets, hence, moving along the graph structure in the opposite direction compared to the first target. This inversion for towards pointings is not reflected in participants performance (see footnote 1, no meaningful interactions with target sequence). Thus, the route direction effect does not seem to change in a meaningful way as a function of target sequence. Here participants might have also accessed previously constructed mental model parts still present in working memory. The role of route direction for later pointing thus is not yet fully clear.
- 3.
Note that the mental walk model faces similar inversion problems for later pointings. No such inversions are required when pointers construct a mental model of their non-visible surrounding based on a graph representation from their current location towards the target which then is mentally “visible” as an ego-centric vector.
References
Mou, W., McNamara, T.P., Valiquette, C.M., Rump, B.: Allocentric and egocentric updating of spatial memories. J. Exp. Psychol. Learn. Mem. Cogn. 30, 142–157 (2004)
O’Keefe, J.: An allocentric spatial model for the hippocampal cognitive map. Hippocampus 1, 230–235 (1991)
Gallistel, C.R.: The Organization of Learning. MIT Press, Cambridge (1990)
Byrne, P., Becker, S., Burgess, N.: Remembering the past and imagining the future: a neural model of spatial memory and imagery. Psychol. Rev. 114, 340–375 (2007)
Chrastil, E.R., Warren, W.H.: From cognitive maps to cognitive graphs. PLoS ONE 9, e112544 (2014)
Mallot, H.A., Basten, K.: Embodied spatial cognition: biological and artificial systems. Image Vis. Comput. 27, 1658–1670 (2009)
Meilinger, T.: The network of reference frames theory: a synthesis of graphs and cognitive maps. In: Freksa, C., Newcombe, N.S., Gärdenfors, P., Wölfl, S. (eds.) Spatial Cognition 2008. LNCS (LNAI), vol. 5248, pp. 344–360. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87601-4_25
Fujita, N., Klatzky, R.L., Loomis, J.M., Golledge, R.G.: The encoding-error model of pathway completion without vision. Geogr. Anal. 25, 295–314 (1993)
Meilinger, T., Riecke, B.E., Bülthoff, H.H.: Local and global reference frames for environmental spaces. Q. J. Exp. Psychol. 67, 542–569 (2014)
Werner, S., Schmidt, K.: Environmental reference systems for large-scale spaces. Spat. Cogn. Comput. 1, 447–473 (1999)
Strickrodt, M., Bülthoff, H.H., Meilinger, T.: Memory for navigable space is flexible and not restricted to exclusive local or global memory units. J. Exp. Psychol. Learn. Mem. Cogn. (in press)
Marchette, S.A., Ryan, J., Epstein, R.A.: Schematic representations of local environmental space guide goal-directed navigation. Cognition 158, 68–80 (2017)
Meilinger, T., Strickrodt, M., Bülthoff, H.H.: Qualitative differences between environmental and vista space memory are caused by the separation of space, not by movement or successive perception. Cognition 155, 77–95 (2016)
Meilinger, T., Henson, A., Rebane, J., Bülthoff, H.H., Mallot, H.A.: Humans construct survey estimates on the fly from a compartmentalised representation of the navigated environment. In: Creem-Regehr, S., et al. (eds.) Spatial Cognition XI. LNAI, vol. 11034, pp. 15–26 (2018)
Wilson, P.N., Wilson, D.A., Griffiths, L., Fox, S.: First-perspective spatial alignment effects from real-world exploration. Mem. Cognit. 35, 1432–1444 (2007)
Poucet, B.: Spatial cognitive maps in animals: new hypotheses on their structure and neural mechanisms. Psychol. Rev. 100, 163–182 (1993)
Stern, E., Leiser, D.: Levels of spatial knowledge and urban travel modeling. Geogr. Anal. 20, 140–155 (1988)
Schweizer, K., Herrmann, T., Janzen, G., Katz, S.: The route direction effect and its constraints. In: Freksa, C., Habel, C., Wender, K.F. (eds.) Spatial Cognition. LNCS (LNAI), vol. 1404, pp. 19–38. Springer, Heidelberg (1998). https://doi.org/10.1007/3-540-69342-4_2
Janzen, G.: Memory for object location and route direction in virtual large-scale space. Q. J. Exp. Psychol. 59, 493–508 (2006)
Schinazi, V.R., Epstein, R.A.: Neural correlates of real-world route learning. Neuroimage 53, 725–735 (2010)
McNaughton, B.L., Battaglia, F.P., Jensen, O., Moser, E.I., Moser, M.B.: Path integration and the neural basis of the “cognitive map”. Nat. Rev. Neurosci. 7, 663–678 (2006)
Skaggs, W.E., McNaughton, B.L.: Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience. Science 271, 1870–1873 (1996)
Pfeiffer, B.E., Foster, D.J.: Hippocampal place-cell sequences depict future paths to remembered goals. Nature 497, 74–79 (2013)
Wang, R.F.: Building a cognitive map by assembling multiple path integration systems. Psychon. Bull. Rev. 23, 692–702 (2016)
Gillner, S., Weiss, A.M., Mallot, H.A.: Visual homing in the absence of feature-based landmark information. Cognition 109, 105–122 (2008)
Thorndyke, P.W., Hayes-Roth, B.: Differences in spatial knowledge acquired from maps and navigation. Cogn. Psychol. 14, 560–589 (1982)
Meilinger, T., Frankenstein, J., Watanabe, K., Bülthoff, H.H., Hölscher, C.: Reference frames in learning from maps and navigation. Psychol. Res. 79, 1000–1008 (2015)
Acknowledgments
This research was supported by the DFG grant ME 3476/2-1. We thank Jan Souman for help in planning the experiment and discussing the results, Nadine Simon for help in data collection, as well as Joachim Tesch, Michael Kerger, and Harald Teufel for intensive technical support.
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Meilinger, T., Strickrodt, M., Bülthoff, H.H. (2018). Spatial Survey Estimation Is Incremental and Relies on Directed Memory Structures. In: Creem-Regehr, S., Schöning, J., Klippel, A. (eds) Spatial Cognition XI. Spatial Cognition 2018. Lecture Notes in Computer Science(), vol 11034. Springer, Cham. https://doi.org/10.1007/978-3-319-96385-3_3
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