Original Research ARTICLE
From global-to-local? Uncovering the temporal dynamics of the composite face illusion using distributional analyses
- 1Department of Psychology, Ariel University, Israel
It is widely believed that faces are processed holistically such that their facial features or parts are represented as global wholes rather than independent entities. But how does their holistic representation evolve in time? According to the global-to-local hypothesis, the initial representation of faces is holistic and coarse at the outset but is becoming progressively detailed and analytic. The current study set to test this global-to-local hypothesis by applying fine-grained methods of response time analyses to the composite face illusion – a traditional marker of holistic face processing. The analyses included the delta plots and conditional accuracy functions. These tools move beyond the mean RT and accuracy to provide detailed analysis of the temporal dynamics of the composite face effect. The methodologies converged on the conclusion that the composite effect is minimal for fast RTs but becomes progressively larger as RTs gets slower. This pattern is inconsistent with a global-to-local dynamics. The implications of these results to the study of face perception are discussed.
Keywords: face recognition, composite faces , delta plots, distributional analyses, Reaction Time, holistic processing
Received: 30 Jul 2019;
Accepted: 30 Sep 2019.
Copyright: © 2019 Fitousi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Daniel Fitousi, Department of Psychology, Ariel University, Ariel, Israel, firstname.lastname@example.org