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Articles 31 - 38 of 38
Full-Text Articles in Computational Neuroscience
Age- And Sex-Dependent Alterations In Primary Somatosensory Neuronal Calcium Network Dynamics During Locomotion, Sami L. Case
Age- And Sex-Dependent Alterations In Primary Somatosensory Neuronal Calcium Network Dynamics During Locomotion, Sami L. Case
Theses and Dissertations--Pharmacology and Nutritional Sciences
Over the past 30 years, the calcium (Ca2+) hypothesis of brain aging has provided clear evidence that hippocampal neuronal Ca2+ dysregulation is a key biomarker of aging. Indeed, age-dependent Ca2+-mediated changes in intrinsic excitability, synaptic plasticity, and activity have helped identify some of the mechanisms engaged in memory and cognitive decline. However, much of this work has been done at the single-cell level, mostly in slice preparations, and in restricted structures of the brain. Recently, our lab identified age- and Ca2+-related neuronal network dysregulation in the cortex of the anesthetized animal. Still, investigations in the awake animal are needed to …
Artificial Light At Night Disrupts Pain Behavior And Cerebrovascular Structure In Mice, Jacob Raymond Bumgarner
Artificial Light At Night Disrupts Pain Behavior And Cerebrovascular Structure In Mice, Jacob Raymond Bumgarner
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
Sense And Sensitivity: Spatial Structure Of Conspecific Signals During Social Interaction, Keshav Ramachandra
Sense And Sensitivity: Spatial Structure Of Conspecific Signals During Social Interaction, Keshav Ramachandra
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
Spatial Processing Of Conspecific Signals In Weakly Electric Fish: From Sensory Image To Neural Population Coding, Oak Everette Milam
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 (ETD)
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 …
Spiking Neural Network That Maps From Generalized Coordinates To Cartesian Coordinates, Chloe K. Guie
Spiking Neural Network That Maps From Generalized Coordinates To Cartesian Coordinates, Chloe K. Guie
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
Multimodal Neuron Classification Based On Morphology And Electrophysiology, Aqib Ahmad
Multimodal Neuron Classification Based On Morphology And Electrophysiology, Aqib Ahmad
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
Computational Mechanisms Of Face Perception, Jinge Wang
Computational Mechanisms Of Face Perception, Jinge Wang
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
Accelerated Forgetting In People With Epilepsy: Pathologic Memory Loss, Its Neural Basis, And Potential Therapies, Sarah Ashley Steimel Phd
Accelerated Forgetting In People With Epilepsy: Pathologic Memory Loss, Its Neural Basis, And Potential Therapies, Sarah Ashley Steimel Phd
Dartmouth College Ph.D Dissertations
While forgetting is vital to human functioning, delineating between normative and disordered forgetting can become incredibly complex. This thesis characterizes a pathologic form of forgetting in epilepsy, identifies a neural basis, and investigates the potential of stimulation as a therapeutic tool. Chapter 2 presents a behavioral characterization of the time course of Accelerated Long-Term Forgetting (ALF) in people with epilepsy (PWE). This chapter shows evidence of ALF on a shorter time scale than previous studies, with a differential impact on recall and recognition. Chapter 3 builds upon the work in Chapter 2 by extending ALF time points and investigating the …