Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …

Biomechanically Inspired Assistive Technology To Restore Movement Of The Upper Limbs After Stroke, Ariel Thomas

Graduate Theses, Dissertations, and Problem Reports

A stroke often damages the neural structures responsible for movement. Stroke is a heterogeneous disease, affecting each survivor differently. There are common motor features of a stroke, but even these features vary across time as an individual proceeds through different stages of recovery. The different ways in which stroke motor impairment can present itself are often overlooked, but these differences are fundamental to the understanding of the disease and its recovery. When motor assessments are capable of acquiring information necessary to parse out a detailed profile of each stroke case, this will lead to an improved neuromechanical understanding of the …

Automated And Standardized Tools For Realistic, Generic Musculoskeletal Model Development, Trevor Rees Moon

Graduate Theses, Dissertations, and Problem Reports

Human movement is an instinctive yet challenging task that involves complex interactions between the neuromusculoskeletal system and its interaction with the surrounding environment. One key obstacle in the understanding of human locomotion is the availability and validity of experimental data or computational models. Corresponding measurements describing the relationships of the nervous and musculoskeletal systems and their dynamics are highly variable. Likewise, computational models and musculoskeletal models in particular are vitally dependent on these measurements to define model behavior and mechanics. These measurements are often sparse and disparate due to unsystematic data collection containing variable methodologies and reporting conventions. To date, …

Aptamer Functionalized Zinc Oxide Field Effect Transistors For Odor Detection, Michael D. Aldridge

Graduate Theses, Dissertations, and Problem Reports

Odor detection and identification are complex processes, and tasks that currently only animals do well. There is a pressing need for an electronic nose, or eNose, with good sensitivity, selectivity, and speed that mimics that ability. Food quality control operations, environmental sensing, occupational safety, and the defense sectors all require systems that can rapidly and reliably detect trace levels of volatile organic compounds. The goal of this work is to create a biologically inspired device which can accurately detect and identify odors at concentrations consistent with the most sensitive biological systems.

In order to mimic a natural olfactory system, we …

Analytical Cpg Model Driven By Limb Velocity Input Generates Accurate Temporal Locomotor Dynamics, Sergiy Yakovenko, Anton Sobinov, Valeriya Gritsenko

Faculty & Staff Scholarship

The ability of vertebrates to generate rhythm within their spinal neural networks is essential for walking, running, and other rhythmic behaviors. The central pattern generator (CPG) network responsible for these behaviors is well-characterized with experimental and theoretical studies, and it can be formulated as a nonlinear dynam- ical system. The underlying mechanism responsible for locomotor behavior can be expressed as the process of leaky integration with resetting states generating appropriate phases for changing body velocity. The low-dimensional input to the CPG model generates the bilateral pattern of swing and stance modulation for each limb and is consistent with the desired …