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 …

Artificial Light At Night Disrupts Pain Behavior And Cerebrovascular Structure In Mice, Jacob Raymond Bumgarner

Graduate Theses, Dissertations, and Problem Reports

Artificial Light at Night Disrupts Pain Behavior and Cerebrovascular Structure in Mice

Jacob R. Bumgarner

Circadian rhythms are intrinsic biological processes that fluctuate in function with a period of approximately 24 hours. These rhythms are precisely synchronized to the 24- hour day of the Earth by external rhythmic signaling cues. Solar light-dark cycles are the most potent environmental signaling cue for terrestrial organisms to align internal rhythms with the external day. Proper alignment and synchrony of internal circadian rhythms with external environmental rhythms are essential for health and optimal biological function.

The modern human environment on Earth is no longer …

Spatial Processing Of Conspecific Signals In Weakly Electric Fish: From Sensory Image To Neural Population Coding, Oak Everette Milam

Graduate Theses, Dissertations, and Problem Reports

In this dissertation, I examine how an animal’s nervous system encodes spatially realistic conspecific signals in their environment and how the encoding mechanisms support behavioral sensitivity. I begin by modeling changes in the electrosensory signals exchanged by weakly electric fish in a social context. During this behavior, I estimate how the spatial structure of conspecific stimuli influences sensory responses at the electroreceptive periphery. I then quantify how space is represented in the hindbrain, specifically in the primary sensory area called the electrosensory lateral line lobe. I show that behavioral sensitivity is influenced by the heterogeneous properties of the pyramidal cell …

Multimodal Neuron Classification Based On Morphology And Electrophysiology, Aqib Ahmad

Graduate Theses, Dissertations, and Problem Reports

Categorizing neurons into different types to understand neural circuits and ultimately brain function is a major challenge in neuroscience. While electrical properties are critical in defining a neuron, its morphology is equally important. Advancements in single-cell analysis methods have allowed neuroscientists to simultaneously capture multiple data modalities from a neuron. We propose a method to classify neurons using both morphological structure and electrophysiology. Current approaches are based on a limited analysis of morphological features. We propose to use a new graph neural network to learn representations that more comprehensively account for the complexity of the shape of neuronal structures. In …

Spiking Neural Network That Maps From Generalized Coordinates To Cartesian Coordinates, Chloe K. Guie

Graduate Theses, Dissertations, and Problem Reports

In this thesis, I look to understand how insects compute task-level quantities by integrating range-fractionated sensory signals to create a sparse-spatial coding of Cartesian positions. I created biologically plausible 2-D and 3-D models of one species of the stick insect (Carausius morosus) leg and encoded the foot position through a spiking neural network. This model used spiking afferents from three angles of an insect leg which are integrated by one non-spiking interneuron. This model contains many dendritic compartments and one somatic compartment that encode the foot’s position relative to the body. The Functional Subnetwork Approach (FSA) was used …

Sense And Sensitivity: Spatial Structure Of Conspecific Signals During Social Interaction, Keshav Ramachandra

Graduate Theses, Dissertations, and Problem Reports

Organisms rely on sensory systems to gather information about their environment. Localizing the source of a signal is key in guiding the behavior of the animal successfully. Localization mechanisms must cope with the challenges of representing the spatial information of weak, noisy signals. In this dissertation, I investigate the spatial dynamics of natural stimuli and explore how the electrosensory system of weakly electric fish encodes these realistic spatial signals. To do so In Chapter 2, I develop a model that examines the strength of the signal as it reaches the sensory array and simulates the responses of the receptors. The …