Individual differences in face perception.
David Whitney, Professor
Psychology
Closed. This professor is continuing with Spring 2024 apprentices on this project; no new apprentices needed for Fall 2024.
The human perceptual system processes faces in an unique manner. Humans perceive faces holistically (i.e. as a whole) rather than as a set of separate features. The face inversion effect is one of the most compelling pieces of evidence for holistic processing of faces. Upright faces are
identified faster than inverted faces, and more interestingly, this difference is disproportionally larger in faces than in objects. The most supported explanation is that inverting a face disrupts holistic processing, which is key for face recognition. In contrast, non-face objects are not processed holistically, so inverting them does not affect recognition in such magnitude. Previous work demonstrates that some individuals are better at this holistic type of processing than others.
Ability to perceive faces as a whole has been shown to correlate with other individual measures such as face recognition abilities and impairments. Preliminary data from our lab suggests that there are not only individual differences in human holistic processing of faces, but that specific faces that were processed holistically by one observer were not by other observers. The aim of this project is then to investigate whether there are such unique individual differences in holistic processing of specific faces. For this purpose, we use Mooney faces as stimuli, which are two-tone images readily perceived as faces despite lacking clear separate face-specific features. Mooney faces are ideal for this project because 1) they can only be recognized holistically since they lack separate, identifiable face-like parts and 2) there seems to be anecdotal individual differences in the Mooney faces that people find easy or hard to recognize. In a set of tasks, we will calculate the inversion effect for each subject for each Mooney face. By measuring each subject’s ability to identify real versions of the Mooney faces, life-time experiences with sets of faces and other face recognition abilities, we expect to find a way to predict which faces will be most holistically
processed by each subject. Next phases of the project will involve analysis and categorization of the specific features of each Mooney face. We expect to explore whether one or multiple individual factors, such as face learning experiences or recognition biases, shape the set of faces that each subject processes holistically.
Role: The research apprentice will be involved in designing stimuli, running experiments, collecting data and analyzing data. Students will be trained in research methods and statistics. Students will be responsible of writing Matlab and Python code and apply statistical toolboxes to analyze the data. The research apprentice will be also expected to read the relevant literature and write reports on the ongoing results of the project. The student will also meet with the supervisor weekly to discuss preliminary data and background literature, in addition to the opportunity to attend weekly lab meetings.
Most tasks and meetings will be remote, but some in-person data collection will be required.
Qualifications: Required: High motivation, interest in visual perception, basic programming skills, ability to work independently on certain projects.
Desirable but not essential: basic knowledge of Adobe Photoshop; experience with programming languages Python and/or Matlab
Day-to-day supervisor for this project: Teresa Canas-Bajo, Graduate Student
Hours: to be negotiated
Related website: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.585921/full
Social Sciences Digital Humanities and Data Science Education, Cognition & Psychology