English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Meeting Abstract

How much path integration is in the cognitive map?

MPS-Authors
/persons/resource/persons84081

Meilinger,  Tobias
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83963

Henson,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  Heinrich H
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Meilinger, T., Henson, A., Bülthoff, H. H., & Mallot, H. (2014). How much path integration is in the cognitive map? In 2014 European Mathematical Psychology Group Meeting (EMPG) (pp. 21).


Cite as: http://hdl.handle.net/21.11116/0000-0001-338A-A
Abstract
Path integration is the ability to keep track of ones movement through space. It is used, for example, to update locations within short-term memory while moving with eyes closed. The question asked here is how much path integration contributes to the long-term storage of an environment learned by walking and if this contribution changes over the course of learning. Twenty-five participants walked through a virtual environment displayed via a head mounted display and which consisted of a row of eight corridors connected by 90 grad turns. Participants walked at a constant speed from one end of the environment to the other end and back again. After every four learning trials (= walking the route forwards and backwards twice) their acquired knowledge was tested and this procedure was repeated five times until they had walked through the environment 20 times. For testing, participants were teleported to a test location within the environment located at the start or the end of a corridor, self-localized, and pointed to all other test locations within the environment by turning around and aligning a vertical line with the assumed straight line direction to the target. We estimated a participant's individual path integration error from pointing to locations in adjacent corridors. Pointing errors were fully attributed to a distance error of the length of the adjacent corridor and not to distance errors in the current corridor which was visible during pointing or to angular errors of the turn as the turn was visible and turns are known to be recalled preferably as 90 grad turns. The average distance error in percent from all adjacent corridor pointings was extrapolated to target locations further away resulting in a two dimensional normal distribution of expected locations for each target location and participant. We estimated if pointings were sampled from such distributions for each participant and familiarity level. Pointings of 3 4 of the participants significantly deviated from such a distribution. This proportion was roughly constant throughout learning. We conclude that for the majority of participants pointing cannot be explained by quantitative path integration errors only and this does not change fundamentally with familiarity. Participants' cognitive maps seem to rely not only on quantitative path integration errors, but also incorporate qualitative errors such as mixing up directions or order.