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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Wormholes in virtual space: From cognitive maps to cognitive graphs.

William H Warren1, Daniel B Rothman1, Benjamin H Schnapp1

  • 1Department of Cognitive, Linguistic and Psychological Sciences, Brown University, Box 1821, 190 Thayer St., Providence, RI 02912, USA.

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Human spatial navigation relies on a

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Area of Science:

  • Cognitive psychology
  • Neuroscience
  • Spatial cognition

Background:

  • Humans and animals build spatial knowledge from visual cues and path integration.
  • Existing models include cognitive maps, topological graphs, and labelled graphs.

Purpose of the Study:

  • To compare three hypotheses on the geometric structure of spatial knowledge for navigation.
  • To investigate how non-Euclidean environments and teleportation affect spatial representations.

Main Methods:

  • Two experiments using a virtual hedge maze with 'wormholes' for teleportation.
  • Participants learned object locations and took novel shortcuts during testing.

Main Results:

  • Shortcuts favored shorter routes and were directional, contradicting topological graph models.
  • Spatial knowledge showed significant geometric inconsistencies, including 'rips', 'folds', and ordinal reversals.
  • Participants were unaware of these Euclidean structure violations.

Conclusions:

  • Spatial knowledge is best described by a labelled graph model, not a Euclidean cognitive map.
  • Local metric information is approximate and inconsistent, not part of a unified coordinate system.
  • Cognitive graph models explain route finding, detours, and shortcuts effectively.