Dynamic Representations in Visual Face Processing

Open Access
Author:
Bittner, Jennifer Lee
Graduate Program:
Psychology
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
December 16, 2010
Committee Members:
  • Michael J. Wenger, Committee Chair
  • Rick O. Gilmore, Committee Chair
  • Reginal B. Adams, Committee Member
  • Frank E. Ritter, Committee Member
Keywords:
  • face
  • vision
  • learning
  • dynamic systems
  • general recognition theory
Abstract:
Work in facial perception has demonstrated improved levels of performance for identification of an anatomical feature when it is surrounded by a context consistent with that of a studied identity (Tanaka & Farah, 1993; Tanaka & Sengco, 1997). This was originally demonstrated using accuracy measures in three conditions—in isolation, in the original (studied) context, and in an augmented facial context (Tanaka & Farah, 1993; Tanaka & Sengco, 1997)—with these patterns interpreted as reflecting holistic or configural processing or representation (Farah, Wilson, Drain & Tanaka, 1998). The current research examines how learning may be functional in this phenomena, through the use of a dynamic systems model based on the structures of Ashby (1989).The original model of Ashby was adapted to represent configurality (e.g Tanaka & Farah, 1993; Tanaka & Sengco, 1997) by way of dimensional dependencies. Models at the level of channel interactions were created and empirically tested using both the traditional paradigm found in the literature as well as a complete identification task. Results from the experimental studies indicated a lack of dimensional dependencies at all GRT construct levels, conflicting with specific model predictions. A series of additional models were created to examine other possible representations of the system. Additionally, further theoretical exploration consisting of the evaluation and comparison of these models was developed though the search for distinctions in model predictions. Taken together, this work provides the capability for learning representations to be considered within facial perception while providing a solid foundation for future work.