Student Theses and Dissertations
Date of Award
2024
Document Type
Thesis
Degree Name
Doctor of Philosophy (PhD)
RU Laboratory
Freiwald Laboratory
Abstract
Facial movements are the primary medium for non-verbal communication and involve a complex orchestration of muscles controlled by the brain. The ability to interpret and produce these movements enables the expression of a wide range of emotions and social cues, all essential for social interactions. Despite their significance, the neural mechanisms governing facial movements remain poorly understood, hindered by the complexity of muscle coordination and the limitations of traditional, subjective, and labor-intensive analysis methods. To objectively understand facial motor control, this research adopts a three-pronged approach: 1) Developing and interpreting computational models within a novel multi-task training framework to simultaneously distinguish between facial expression and identity recognition, 2) Introducing a novel self-supervised Person-Specific Model (PSM) framework that extracts person-specific facial movements independently of other facial characteristics, enhancing facial muscle action characterization by leveraging individual differences, and 3) Utilizing data-driven computational models to analyze a unique dataset of single-cell recordings from sensorimotor cortex regions and behavioral video recordings of spontaneous, unconstrained, and naturalistic facial movements of macaques.
Recommended Citation
Tazi, Yanis, "Towards a Better Understanding of Facial Movements: Computational Models for Perception, Characterization, and Neural Production" (2024). Student Theses and Dissertations. 784.
https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/784
Comments
A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy