Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Combining egoformative and alloformative cues in a novel tabletop navigation task.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • المصدر:
      Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 0435062 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1430-2772 (Electronic) Linking ISSN: 03400727 NLM ISO Abbreviation: Psychol Res Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: Berlin, New York, Springer-Verlag.
    • الموضوع:
    • نبذة مختصرة :
      Previous work has shown how different interfaces (i.e., route navigation, maps, or a combination of the two) influence spatial knowledge and recollection. To test for the existence of intermediate representations along an egocentric-to-allocentric continuum, we developed a novel task, tabletop navigation, to provide a mixture of cues that inform the emergence of egocentric and allocentric representations or strategies. In this novel tabletop task, participants navigated a remote-controlled avatar through a tabletop scale model of the virtual city. Participants learned virtual cities from either navigating routes, studying maps, or our new tabletop navigation task. We interleaved these learning tasks with either an in situ pointing task (the scene- and orientation-dependent pointing [SOP] task) or imagined judgements of relative direction (JRD) pointing. In Experiment 1, performance on each memory task was similar across learning tasks and performance on the route and map learning tasks correlated with more precise spatial recall on both the JRD and SOP tasks. Tabletop learning performance correlated with SOP performance only, suggesting a reliance on egocentric strategies, although increased utilization of the affordances of the tabletop task were related to JRD performance. In Experiment 2, using a modified criterion map learning task, participants who learned using maps provided more precise responses on the JRD compared to route or tabletop learning. Together, these findings provide mixed evidence for both optimization and egocentric predominance after learning from the novel tabletop navigation task.
      (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
    • References:
      Aguinis, H., Villamor, I., & Ramani, R. S. (2020). MTurk research: Review and recommendations. Journal of Management. https://doi.org/10.1177/0149206320969787. (PMID: 10.1177/0149206320969787)
      Aruguete, M. S. (2019). How serious is the ‘carelessness’ problem on Mechanical Turk? International Journal of Social Research Methodology, 22(5), 10. (PMID: 10.1080/13645579.2018.1563966)
      Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01. (PMID: 10.18637/jss.v067.i01)
      Ben-Shachar, M., Lüdecke, D., & Makowski, D. (2020). effectsize: Estimation of effect size indices and standardized parameters. Journal of Open Source Software, 5(56), 2815. https://doi.org/10.21105/joss.02815. (PMID: 10.21105/joss.02815)
      Burgess, N. (2006). Spatial memory: How egocentric and allocentric combine. Trends in Cognitive Sciences, 10(12), 551–557. https://doi.org/10.1016/j.tics.2006.10.005. (PMID: 10.1016/j.tics.2006.10.00517071127)
      Chrastil, E. R. (2018). Heterogeneity in human retrosplenial cortex: A review of function and connectivity. Behavioral Neuroscience, 132(5), 317–338. https://doi.org/10.1037/bne0000261. (PMID: 10.1037/bne000026130160506)
      Chrastil, E. R., & Warren, W. H. (2012). Active and passive contributions to spatial learning. Psychonomic Bulletin & Review, 19(1), 1–23. https://doi.org/10.3758/s13423-011-0182-x. (PMID: 10.3758/s13423-011-0182-x)
      Chrastil, E. R., & Warren, W. H. (2013). Active and passive spatial learning in human navigation: Acquisition of survey knowledge. Journal of Experimental Psychology. Learning, Memory, and Cognition, 39(5), 1520–1537. https://doi.org/10.1037/a0032382. (PMID: 10.1037/a003238223565781)
      Chrastil, E. R., & Warren, W. H. (2015). Active and passive spatial learning in human navigation: Acquisition of graph knowledge. Journal of Experimental Psychology. Learning, Memory, and Cognition, 41(4), 1162–1178. https://doi.org/10.1037/xlm0000082. (PMID: 10.1037/xlm000008225419818)
      Dixon, P. (2008). Models of accuracy in repeated-measures designs. Journal of Memory and Language, 59(4), 447–456. https://doi.org/10.1016/j.jml.2007.11.004. (PMID: 10.1016/j.jml.2007.11.004)
      Ekstrom, A. D., Arnold, A. E. G. F., & Iaria, G. (2014). A critical review of the allocentric spatial representation and its neural underpinnings: Toward a network-based perspective. Frontiers in Human Neuroscience, 8(OCT), 803. https://doi.org/10.3389/fnhum.2014.00803. (PMID: 10.3389/fnhum.2014.00803253466794193251)
      Ekstrom, A. D., Huffman, D. J., & Starrett, M. (2017). Interacting networks of brain regions underlie human spatial navigation: A review and novel synthesis of the literature. Journal of Neurophysiology, 118(6), 3328–3344. https://doi.org/10.1152/jn.00531.2017. (PMID: 10.1152/jn.00531.2017289316135814720)
      FC, M. (2020). Ggpattern (0.1.2) [R]. coolbutuseless. https://coolbutuseless.github.io/package/ggpattern/index.html.
      Filimon, F. (2015). Are all spatial reference frames egocentric? Reinterpreting evidence for allocentric, object-centered, or world-centered reference frames. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2015.00648. (PMID: 10.3389/fnhum.2015.00648266968614673307)
      Fletcher, T. D. (2012). QuantPsyc: Quantitative Psychology Tools. https://CRAN.R-project.org/package=QuantPsyc.
      Gardony, A. L., Brunyé, T. T., Mahoney, C. R., & Taylor, H. A. (2013). How navigational aids impair spatial memory: Evidence for divided attention. Spatial Cognition & Computation, 13(4), 319–350. https://doi.org/10.1080/13875868.2013.792821. (PMID: 10.1080/13875868.2013.792821)
      Green-Armytage, P. (2010). A colour alphabet and the limits of colour coding. JAIC-Journal of the International Colour Association, 5.
      Hester, J., Csárdi, G., Wickham, H., Chang, W., Morgan, M., & Tenenbaum, D. (2021). remotes: R Package Installation from Remote Repositories, Including “GitHub.” https://CRAN.R-project.org/package=remotes.
      Holmes, C. A., Newcombe, N. S., & Shipley, T. F. (2018). Move to learn: Integrating spatial information from multiple viewpoints. Cognition, 178, 7–25. https://doi.org/10.1016/j.cognition.2018.05.003. (PMID: 10.1016/j.cognition.2018.05.00329758479)
      Huffman, D. J., & Ekstrom, A. D. (2019). Which way is the bookstore? A closer look at the judgments of relative directions task. Spatial Cognition & Computation, 19(2), 93–129. https://doi.org/10.1080/13875868.2018.1531869. (PMID: 10.1080/13875868.2018.1531869)
      Kassambara, A. (2020). ggpubr: “ggplot2” Based Publication Ready Plots. https://CRAN.R-project.org/package=ggpubr.
      Kassambara, A. (2021). rstatix: Pipe-Friendly Framework for Basic Statistical Tests. https://CRAN.R-project.org/package=rstatix.
      Kay, M., Elkin, L. A., Higgins, J. J., & Wobbrock, J. O. (2021). ARTool: Aligned Rank Transform for Nonparametric Factorial ANOVAs. https://doi.org/10.5281/zenodo.594511.
      Khan, N., & Rahman, A. U. (2018). Rethinking the mini-map: A navigational aid to support spatial learning in urban game environments. International Journal of Human-Computer Interaction, 34(12), 1135–1147. https://doi.org/10.1080/10447318.2017.1418804. (PMID: 10.1080/10447318.2017.1418804)
      Kim, S. (2015). ppcor: An R package for a fast calculation to semi-partial correlation coefficients. Communications for Statistical Applications and Methods, 22(6), 665–674. https://doi.org/10.5351/CSAM.2015.22.6.665. (PMID: 10.5351/CSAM.2015.22.6.665266888024681537)
      Kreidler, S. M., Muller, K. E., Grunwald, G. K., Ringham, B. M., Coker-Dukowitz, Z., Sakhadeo, U. R., Baron, A. E., & Glueck, D. H. (2013). GLIMMPSE: Online power computation for linear models with and without a baseline covariate. Journal of Statistical Software. https://doi.org/10.18637/jss.v054.i10. (PMID: 10.18637/jss.v054.i10244038683882200)
      Lenth, R. V. (2021). emmeans: Estimated Marginal Means, aka Least-Squares Means. https://CRAN.R-project.org/package=emmeans.
      Marchette, S. A., Vass, L. K., Ryan, J., & Epstein, R. A. (2014). Anchoring the neural compass: Coding of local spatial reference frames in human medial parietal lobe. Nature Neuroscience, 17(11), 1598–1606. https://doi.org/10.1038/nn.3834. (PMID: 10.1038/nn.3834252826164309016)
      Meilinger, T., Frankenstein, J., & Bulthoff, H. H. (2013). Learning to navigate: Experience versus maps. Cognition, 129(1), 24–30. https://doi.org/10.1016/j.cognition.2013.05.013. (PMID: 10.1016/j.cognition.2013.05.01323820180)
      Mou, W., McNamara, T. P., Rump, B., & Xiao, C. (2006). Roles of egocentric and allocentric spatial representations in locomotion and reorientation. Journal of Experimental Psychology. Learning, Memory, and Cognition, 32(6), 1274–1290. https://doi.org/10.1037/0278-7393.32.6.1274. (PMID: 10.1037/0278-7393.32.6.127417087583)
      Mou, W., McNamara, T. P., Valiquette, C. M., & Rump, B. (2004). Allocentric and egocentric updating of spatial memories. Journal of Experimental Psychology. Learning, Memory, and Cognition, 30(1), 142–157. https://doi.org/10.1037/0278-7393.30.1.142. (PMID: 10.1037/0278-7393.30.1.14214736303)
      Newman, E. L., Caplan, J. B., Kirschen, M. P., Korolev, I. O., Sekuler, R., & Kahana, M. J. (2007). Learning your way around town: How virtual taxicab drivers learn to use both layout and landmark information. Cognition, 104(2), 231–253. https://doi.org/10.1016/j.cognition.2006.05.013. (PMID: 10.1016/j.cognition.2006.05.01316879816)
      R Core Team. (2021). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.R-project.org/.
      Richardson, A. E., Montello, D. R., & Hegarty, M. (1999). Spatial knowledge acquisition from maps and from navigation in real and virtual environments. Memory & Cognition, 27(4 LB-ref1), 741–750. https://doi.org/10.3758/bf03211566. (PMID: 10.3758/bf03211566)
      RStudio Team. (2020). RStudio: Integrated Development Environment for R. RStudio, PBC. http://www.rstudio.com/.
      Ruddle, R. A., & Lessels, S. (2006). For efficient navigational search, humans require full physical movement, but not a rich visual scene. Psychological Science, 17(6), 460–465. https://doi.org/10.1111/j.1467-9280.2006.01728.x. (PMID: 10.1111/j.1467-9280.2006.01728.x16771793)
      Ruddle, R. A., & Lessels, S. (2009). The benefits of using a walking interface to navigate virtual environments. Acm Transactions on Computer-Human Interaction. https://doi.org/10.1145/1502800.1502805. (PMID: 10.1145/1502800.1502805)
      Singmann, H., Bolker, B., Westfall, J., Aust, F., & Ben-Shachar, M. S. (2021). afex: Analysis of Factorial Experiments. https://CRAN.R-project.org/package=afex.
      Sprouse, J. (2011). A validation of Amazon Mechanical Turk for the collection of acceptability judgments in linguistic theory. Behavior Research Methods, 43(1), 155–167. https://doi.org/10.3758/s13428-010-0039-7. (PMID: 10.3758/s13428-010-0039-721287108)
      Starrett, M. J., & Ekstrom, A. D. (2018). Perspective: Assessing the flexible acquisition, integration, and deployment of human spatial representations and information. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2018.00281. (PMID: 10.3389/fnhum.2018.00281300504226050378)
      Starrett, M. J., McAvan, A. S., Huffman, D. J., Stokes, J. D., Kyle, C. T., Smuda, D. N., Kolarik, B. S., Laczko, J., & Ekstrom, A. D. (2021). Landmarks: A solution for spatial navigation and memory experiments in virtual reality. Behavior Research Methods, 53(3), 1046–1059. https://doi.org/10.3758/s13428-020-01481-6. (PMID: 10.3758/s13428-020-01481-632939682)
      Starrett, M. J., Stokes, J. D., Huffman, D. J., Ferrer, E., & Ekstrom, A. D. (2019). Learning-dependent evolution of spatial representations in large-scale virtual environments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(3), 497–514. https://doi.org/10.1037/xlm0000597. (PMID: 10.1037/xlm000059729985031)
      Taylor, H. A., & Tversky, B. (1992). Spatial mental models derived from survey and route descriptions. Journal of Memory and Language, 31(2), 261–292. https://doi.org/10.1016/0749-596X(92)90014-O. (PMID: 10.1016/0749-596X(92)90014-O)
      Waller, D., & Hodgson, E. (2006). Transient and enduring spatial representations under disorientation and self-rotation. Journal of Experimental Psychology-Learning Memory and Cognition, 32(4), 867–882. https://doi.org/10.1037/0278-7393.32.4.867. (PMID: 10.1037/0278-7393.32.4.86716822154)
      Wang, R. F. (2017). Spatial updating and common misinterpretations of spatial reference frames. Spatial Cognition & Computation. https://doi.org/10.1080/13875868.2017.1304394. (PMID: 10.1080/13875868.2017.1304394)
      Wang, R. F., & Spelke, E. S. (2000). Updating egocentric representations in human navigation. Cognition, 77(3), 215–250. https://doi.org/10.1016/s0010-0277(00)00105-0. (PMID: 10.1016/s0010-0277(00)00105-011018510)
      Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686. (PMID: 10.21105/joss.01686)
      Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J. (2011). The aligned rank transform for nonparametric factorial analyses using only anova procedures. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/1978942.1978963. (PMID: 10.1145/1978942.1978963)
      Zhang, H., Copara, M., & Ekstrom, A. D. (2012). Differential recruitment of brain networks following route and cartographic map learning of spatial environments. PLoS ONE, 7(9), e44886. https://doi.org/10.1371/journal.pone.0044886. (PMID: 10.1371/journal.pone.0044886230286613445610)
      Zhang, H., & Ekstrom, A. (2013). Human neural systems underlying rigid and flexible forms of allocentric spatial representation. Human Brain Mapping, 34(5), 1070–1087. https://doi.org/10.1002/hbm.21494. (PMID: 10.1002/hbm.2149422786703)
      Zhang, H., Zherdeva, K., & Ekstrom, A. D. (2014). Different “routes” to a cognitive map: Dissociable forms of spatial knowledge derived from route and cartographic map learning. Memory and Cognition, 42(7), 1106–1117. https://doi.org/10.3758/s13421-014-0418-x. (PMID: 10.3758/s13421-014-0418-x24845757)
    • Grant Information:
      BCS-1630296 National Science Foundation
    • الموضوع:
      Date Created: 20221001 Date Completed: 20230531 Latest Revision: 20230531
    • الموضوع:
      20231215
    • الرقم المعرف:
      PMC9526213
    • الرقم المعرف:
      10.1007/s00426-022-01739-y
    • الرقم المعرف:
      36181560