The Cognitive Science of Reorientation

• Author / Creator

  Dupuis, Brian A

• This work stands as an example of “synthetic methodology” in psychological research. Synthetic methodology involves building a model, seeing what it can and cannot do when placed in interesting environments, comparing this behaviour to real-world subjects for parallels and discrepancies, and then examining the model for insight and theoretical advancement. This methodology is employed here in the context of a common spatial-learning “reorientation task”. Motivated by the discovery of critical flaws in a popular model for this reorientation task, we develop a synthetic neural network model as an alternative, and explore its behaviour in novel tasks, as well as the mathematical consequences of adopting such a formalism. These behaviours lead us to question assumptions underlying normal reorientation research. We devise a new method of collecting human data in spatial tasks, and use this method to compare the neural network to human subjects, in the style of comparative cognition.

• Subjects / Keywords

  • Spatial Learning
  • Comparative Cognition
  • Synthetic Psychology
  • Reorientation
  • Neural Networks
  • Cognitive Science
  • Cognitive Modelling

• Graduation date

  Fall 2012

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3R72V

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.