The Geometry and Dynamics of Context

The notion of context is central to many areas in Psychology, especially memory. Mathematical models of memory employ context to cue contents of memory to retrieve specific events or items. Context effects are widespread. However, there have not been many attempts to specify what context in the real world is. We use techniques of nonlinear dynamics to characterize the properties of real world contexts. We show that people experience highly repetitive contexts. We compute the correlation dimension of the space of contexts and show that both visual and semantic context spaces exhibit a two-scaled and low dimensional structure. Finally, we use Takens' delay embedding theorem to show that the low dimension structure is directly related to the dynamics of how people move from one context to another. We discuss these results in the light of the rational analysis of memory (Anderson, 1990).

Name thesis:degree_name

Master of Arts

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Psychology

Grantor dc:publisher

The Ohio State University

Year dc:date

2012

Author dc:creator

• Sreekumar, Vishnu

Contributors dc:contributor

• Dennis, Simon

• Cognitive Psychology
• Language
• Physics
• Psychology
• Context
• Dynamics
• Correlation Dimension
• Memory

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=osu1355417852

OAI identifier oai:identifier

oai:etd.ohiolink.edu:osu1355417852