Literature DB >> 19814904

Representation of space: image-like or sensorimotor?

Christoph Zetzsche1, Johannes Wolter, Christopher Galbraith, Kerstin Schill.   

Abstract

We investigate the relation between the physical world and its mental representation in the 'cognitive map', and test if this representation is image-like and complies with the laws of Euclidean geometry. We have developed a new experimental technique using 'impossible' virtual environments (VE) to directly influence the representational development. Subjects explore a number of VEs -- some 'normal', others with severe violations of Euclidean metrics or planar topology. We check if these manipulated properties cause problems in navigation performance. A consistent VE should be easily represented mentally in a map-like fashion, while a VE with severe violations should prove difficult. Surprisingly, we found no substantial influence of the impossible VEs on navigation performance, and forced-choice tests showed little evidence that subjects were aware of manipulations. This suggests that the representation does not resemble a two-dimensional image-like map. Alternatives to consider are sensorimotor and graph-like representations.

Mesh:

Year:  2009        PMID: 19814904     DOI: 10.1163/156856809789476074

Source DB:  PubMed          Journal:  Spat Vis        ISSN: 0169-1015


  5 in total

1.  Representation of impossible worlds in the cognitive map.

Authors:  Thorsten Kluss; William E Marsh; Christoph Zetzsche; Kerstin Schill
Journal:  Cogn Process       Date:  2015-09

2.  Spatial abstraction for autonomous robot navigation.

Authors:  Susan L Epstein; Anoop Aroor; Matthew Evanusa; Elizabeth I Sklar; Simon Parsons
Journal:  Cogn Process       Date:  2015-09

3.  Gaze behaviour during space perception and spatial decision making.

Authors:  Jan M Wiener; Christoph Hölscher; Simon Büchner; Lars Konieczny
Journal:  Psychol Res       Date:  2011-12-03

Review 4.  Structuring Knowledge with Cognitive Maps and Cognitive Graphs.

Authors:  Michael Peer; Iva K Brunec; Nora S Newcombe; Russell A Epstein
Journal:  Trends Cogn Sci       Date:  2020-11-26       Impact factor: 20.229

5.  Learning indoor robot navigation using visual and sensorimotor map information.

Authors:  Wenjie Yan; Cornelius Weber; Stefan Wermter
Journal:  Front Neurorobot       Date:  2013-10-07       Impact factor: 2.650

  5 in total

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