Evolution of primate cuboid form and the application of learning methods to the analysis of morphological and behavioral phenotypes

Thomas, Oshane Odane

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https://hdl.handle.net/2142/121919 Copy

Description

Title

Evolution of primate cuboid form and the application of learning methods to the analysis of morphological and behavioral phenotypes

Author(s)

Thomas, Oshane Odane

Issue Date

2023-08-17

Director of Research (if dissertation) or Advisor (if thesis)

Hasegawa-Johnson, Mark

Doctoral Committee Chair(s)

Polk, John D

Committee Member(s)

• Hughes, Cris
• Konigsberg, Lyle W
• Moulin, Pierre

Department of Study

Anthropology

Discipline

Anthropology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• phylogenetic comparative methods
• cuboid
• functional morphology
• gait analysis
• machine learning
• transformer
• AI
• morphological phenotyping
• geometry processing
• functional maps

Abstract

This dissertation makes several significant contributions to the field of functional and evolutionary morphology, with a particular focus on primate (including human) locomotor adaptations. It is composed of three distinct, yet interconnected studies. The first study underscores the necessity of evaluating models of morphological evolution within a phylogenetic context. It delves into the morphological diversity of anthropoid cuboids, exploring the interplay between random and adaptive evolutionary processes. By employing geometric morphometric techniques and modern phylogenetic comparative methods, the research uncovers that both types of evolutionary processes have significantly shaped the cuboid morphology of anthropoid primates. This discovery emphasizes the importance of considering phylogeny in primate studies and has far-reaching implications for our understanding of primate evolution. The second study introduces Explainable GaitViT, a revolutionary transformer-based model designed to improve the accuracy and interpretability of human joint kinematic data classification. The model's superior performance in classifying different lower limb joint kinematics, coupled with its enhanced interpretability due to modern explainable AI techniques, suggests promising clinical applications. These include the potential to discern movement pattern differences between treatment groups based on a limited set of sequential gait variables. The third and final study presents the Morphological Variation Quantifier (morphVQ), a novel shape analysis pipeline for quantifying and analyzing shape variation within the functional domain. The pipeline's effectiveness in characterizing shape variation, and its superiority over manual digitization and the existing automated morphological phenotyping approach (auto3DGM), indicate potential applications across various fields such as biology, anthropology, and medicine. This dissertation significantly advances our understanding of primate and human evolution, gait analysis, and morphological phenotyping. It challenges existing theories, uncovers new avenues for research, and has profound implications for our understanding of primate and human evolution, gait pathologies, and the relationship between form and function. The innovative methodologies and findings presented in this work contribute to the existing body of knowledge and pave the way for future research in these fields.

Graduation Semester

2023-12

Type of Resource

Thesis

Copyright and License Information

Copyright 2023 Oshane O. Thomas

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