Computational Neuroscience Commons^™

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury, Omeima Mutwali

Dissertations, Theses, and Capstone Projects

Traumatic brain injury (TBI) symptom prevention and remediation is an important area of research that would benefit vulnerable groups, including active-duty and veteran soldiers. These patients can sustain penetrative forces in fields of combat or in training, which result in focal lesions that trigger inflammatory and degenerative processes in the brain. Both primary and secondary injuries are associated with changes to cognition, behavior and affective state. This disease poses increased risk of epileptogenesis, as well. Given these outcomes, prior research has evaluated levetiracetam (LEV) as a prophylactic treatment for seizures, cognitive deficits and negative emotionality. LEV acts as a presynaptic …

Vergence Task-Based Neural Pathways With Binocularly Normal Vision And Comorbid Persistent Post-Concussive Symptoms -Convergence Insufficiency, Ayushi Sangoi

Dissertations

Binocular dysfunctions are more prevalent in the persistent post-concussive symptoms (PPCS) population than in the general population. The most prevalent binocular disorder is convergence insufficiency (CI), affecting 3-17% of the general population and up to 10 times as many people with PPCS. CI makes it difficult to fuse or maintain fusion on targets at near, and its symptoms include double or blurry vision and headaches when performing close-range tasks such as reading, which can exacerbate PPCS symptoms. Given controversy over the subjectivity and effectiveness of diagnostic tools and symptom surveys for both PPCS and CI, understanding why CI has high …

Transcranial Ac Modulation Of Cerebellar Nuclear Activity In Awake Animals, Nuran Kavakli

Dissertations

Entrainment of cerebellar nuclear (CN) cells via cerebellar transcranial alternating current stimulation (ctACS) has been reported in animals under ketamine/xylazine anesthesia. Our main objective was to demonstrate modulation of CN activity in unanesthetized, freely moving animals using ctACS. Multi-channel carbon-fiber electrodes were implanted into the interpositus nucleus for recording multi-unit (MU) activity, and thin-film electrodes were implanted subcutaneously over the posterior cerebellum for stimulation. A frequency-domain-based metric was developed to quantify modulation from MU signals. The results demonstrated modulation in a wide range of frequencies (4 Hz-300 Hz) as in anesthetized animals. In contrast, the amplitude of the peak in …

Somatosensory Cortex Responses To Illusory Touch In A Visual-Tactile Integration Task, Aditi Surendra Pawar

Dissertations, Theses, and Capstone Projects

Perceptual illusions arising from multisensory integration reveal how the brain constructs subjective experience from sensory input, and provide a powerful means of allowing the investigation of neural processes that track perceptual interpretation rather than physical stimulation alone. While visual illusions induced by auditory or tactile stimuli have been fairly well studied, the neural mechanisms underlying visually-induced illusory touch remain unclear. This study investigated whether illusory tactile perception engages the somatosensory cortex in a manner similar to veridical touch. Twenty healthy adults participated in an event-related functional magnetic resonance imaging (fMRI) study while performing a tactile numerosity judgment task. Each trial …

How To Search For The Engram: Optogenetics And Network Dynamics, Claudia Garcia Jou

Dissertations, Theses, and Capstone Projects

Memories are thought to be encoded by ensembles of neurons called "engram cells", because their artificial activation with optogenetics leads to the behavioral expression of a memory. However, the physiological mechanisms that mediate this process remain unknown. In this thesis, I investigate how optogenetic stimulation of memory-tagged cells changes neuronal firing, spatial coding, and the geometry of neural manifolds. I used an active place avoidance task and a foraging task to label engram cells in the dorsal hippocampus with Channelrhodopsin2 (ChR2). I then recorded the hippocampal activity response to optogenetic stimulation in mice under anesthesia, head-fixed, or freely moving. I …

A Generalized Framework For The “Core” Thalamocortical Circuit Computation, Charles Liu

Dartmouth College Ph.D Dissertations

This thesis explores a biologically inspired computational framework based on a common excitatory-inhibitory circuit in the superficial layers of the cortex. By varying the strength of local feedback inhibition, this single circuit gives rise to distinct unsupervised learning behaviors: strong inhibition leads to clustering and hierarchical clustering, while weak inhibition produces principal component-like representations. From this principle, we develop three algorithms: Lateral Inhibition Clustering (LI-C), Lateral Inhibition Hierarchical Clustering (LI-HC), and Antipodal Iterative Mean Estimation (AIME).

LI-C performs clustering without requiring a predefined number of clusters, using a competitive learning rule to extract dominant patterns from data. LI-HC extends this …

Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson

Honors Undergraduate Theses

This study investigates the relationship between electrical stimulus characteristics of shape and charge on evoked sensations and electroencephalogram (EEG) data during multi-waveform transcutaneous electrical nerve stimulation (TENS) of the median nerve. Neuromodulation methods have traditionally had little control over the location and quality of their associated evoked sensation (e.g., electric, vibration, touch). This experiment utilized five unique stimulus waveforms during TENS stimulation. EEG data were collected concurrently to provide an introductory objective measure of the neural responses underlying these sensory changes. Eleven participants completed three tasks (thresholding, super-threshold stimulation, two-alternative forced choice) using a two-electrode TENS approach. Stimulus waveforms were …

Towards Computational Methods In Medical Data Analysis: From Speech And Text To Imaging, Kristin Qi

Graduate Doctoral Dissertations

Early detection of cognitive decline and efficient medical image analysis remain critical challenges in healthcare. Traditional clinical assessments are infrequent and resource-intensive, while everyday speech data and unlabeled medical images remain largely unexploited. This dissertation develops computational methods integrating machine learning and artificial intelligence across speech, text, and imaging modalities to address challenges in medical data processing. For cognitive monitoring, this work first introduces methods using voice assistant systems to collect longitudinal speech data in home environments, demonstrating that incorporating historical session patterns significantly enhances detection of mild cognitive impairment. Building on this foundation, a framework combining large language model-driven …

Generating Predictive Gene Expression Signatures For Alzheimer's Disease Using Postmortem Brain Tissue, Ashley Duche

Pharmaceutical Sciences (PhD) Dissertations

Background: Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-beta (Aβ) plaques and tau protein aggregates. These pathological features develop in specific brain regions, but why some areas are more vulnerable to early AD-related changes remains unclear. To address this, predictive gene expression signatures were developed to explore the molecular mechanisms underlying regional susceptibility to AD pathology.

Methods: This was performed using postmortem brain (PMB) tissue from participants in the Religious Orders Study and Memory and Aging Project (ROSMAP), Mayo Clinic, and Mount Sinai Brain Bank (MSBB) to generate gene expression signatures from six brain …

Modeling And Analysis Of Electric Signal In Neurons, Kevin J. Roberts

All Graduate Reports and Creative Projects, Fall 2023 to Present

Neurons in humans and other species transmit information by sending electric signals via axons. This process relies on the generation and propagation of action potentials—rapid changes in the membrane potential of the axon. Understanding the mechanisms of action potentials, including how they are generated and influenced by the axon geometry and material parameters, is crucial for gaining insight into neurological diseases such as Alzheimer’s and Multiple Sclerosis (diseases highly correlated to demyelination). In this work, we review and summarize mathematical models for signal transmission–including the classical Hodgkin-Huxley model, the Single Cable (SC) model, and the Double Cable (DC) model. We …

Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher

Master's Theses

Neuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization …

Sliding Window Method For Simulating Action Potentials In Axons, Hayden Reed

Honors Theses

ABSTRACT Hodgkin and Huxley’s nonlinear partial differential equations model the excitation and propagation of action potentials in neurons, and there have been numerous attempts at finding the best numerical solution method. This thesis proposes a novel approach to solving these equations: the Sliding Window method, in which a fixed sub-interval is found through capturing the signal’s head and tail. The system is then solved on the sub-interval instead of the entire interval. Using the Sliding Window technique also involves implementing the backward and forward Euler methods and the finite difference method. It will be demonstrated that, in utilizing the Sliding …

Designing Accessible Ui/Ux For Epileptic Patients: A Scalable Solution For Music Therapy Delivery, Amethyst G.H. Mckenzie

Computer Science Senior Theses

How can we design an accessible, scalable UI/UX system tailored to the cognitive, visual, and motor impairments of epileptic patients, that ensures safe and effective interactions with music therapy applications? This research explores the intersection of accessibility, user-centred design, and digital health, using an iterative design process to develop and refine the SONATA app—a clinically deployable music therapy platform.

Through two prototype iterations, usability testing, and quantitative event logging, this study compares the effectiveness of structured versus flexible navigation in improving user experience. Key findings reveal that structured navigation reduces unintended detours, while progressive disclosure techniques enhance instructional clarity. Additionally, …

Constructing A Parameterized Stimuli Space Suitable To Induce Controlled Changes In Human And Machine Perceptual Systems, Andrew Frankel

Dissertations, Theses, and Capstone Projects

Traditional computer vision applications focus on objective tasks, such as object detection, classification, or segmentation. Much of human experience is inherently subjective, such as our personal response to artwork. Individualized experiences are challenging to replicate in a controlled laboratory environment, as those experiences depend on the unique history and internal models of the observer. This work presents a technique to construct a 2-dimensional parameterized stimuli space suitable to induce controlled changes in the perceptual systems of both human and machine observers. Our contributions are threefold:

1. Using a balanced dataset of 8,800 fine art images spanning 11 art movements and 88 …

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Vertex-Based Analysis Of Cerebral Blood Flow And Fractional Amplitude Of Low-Frequency Fluctuations (Cbf-Falff) Coupling In Moderate-To-Severe Traumatic Brain Injury During The First Year Post-Injury, Vaidehi Hemkumar Patel

Dissertations, Theses, and Capstone Projects

Traumatic brain injury (TBI) is known to involve damage in the neurovascular unit. TBI may disrupt the brain’s neurovascular coupling–the relationship between cerebral blood flow and neural activity–that can lead to cognitive and functional impairments. This study attempted to non-invasively investigate neurovascular coupling in patients with moderate to severe TBI (msTBI) during the first year post-injury using a combined metric of cerebral blood flow (CBF) and fractional amplitude of low-frequency fluctuations (fALFF), a proxy for spontaneous neural activity. Using arterial spin labeling (ASL) and functional MRI sequences, CBF and fALFF were measured in 29 msTBI patients 3-, 6- and 12-months …

Cgrp Modulation Of Intracellular Calcium Levels In Trigeminal Ganglion Neurons And Glia, Nicole M. Nalley

Graduate Theses/Dissertations

Elevated levels of calcitonin gene-related peptide (CGRP) are implicated in migraine and TMD pathology, but its effects on the excitability state of Aδ and C-fiber neurons and glia have not been investigated. The goal of this study was to determine changes mediated by CGRP on intracellular calcium levels in trigeminal ganglion neurons and glia in response to depolarizing stimulation. Intracellular calcium levels were determined in Aδ and C-fiber neurons of primary trigeminal ganglion cultures obtained from neonatal Sprague Dawley rats using Fura-2 and fluorescent microscopy. Cells were left untreated or preincubated for 2 hours with CGRP, then incubated with the …

Theoretical Analysis Of Cnns For Automatic Seizure Detection In Eeg Signals, Jackson T. Small

Honors Undergraduate Theses

Epilepsy is a common brain disorder where neurons in the brain rapidly fire, causing recurring seizures. The brain activity during a seizure can be detected by electroencephalogram (EEG) signals; however, this process is not only labor-intensive and time-consuming but is also subject to inter-rater variability, with a study showing only moderate agreement when diagnosing patients, even among experts. Convolutional Neural Networks (CNNs) are often proposed to detect seizures automatically, achieving high performance. The focus on performance comes at a cost of losing interpretability, leaving the model as effective but seen as a ’black box’. This thesis confronts the interpretability knowledge …

The Effect Of Cerebellar Feedback On The Spatial Processing Of Conspecific Signals In The Electrosensory System, Dakota Ray Miller

Graduate Theses, Dissertations, and Problem Reports (ETD)

Animals have evolved sensory systems to help decipher important environmental signals that are vital for their survival. Feedback pathways are necessary to allow these signals to stand out in a noisy background, enabling the animal to focus on them more effectively. The electrosensory system of Apteronotus leptorhynchus allows the fish to sense the modulations caused by other conspecifics to allow for proper responses during social interactions. Electroreceptors detect these EODs, and afferent nerves project these signals to the ELL, where electrosensory information is projected to other parts of the brain. Cerebellar feedback to the ELL allows the suppression of lower …

Individual And Collective Properties Of Tunable Photochemical Belousov-Zhabotinsky Micro-Reactors, Kudakwashe Benedict Shumba

Graduate Theses, Dissertations, and Problem Reports (ETD)

Cell-like model chemical systems are powerful tools that can be used to explore the role of intercellular coupling on population level behaviors in communities of biological cells. Firstly, we present a new method for fabricating such micro-reactors using the photosensitive Belousov–Zhabotinsky (BZ) reaction system employed in silica microparticles. These BZ micro-reactors have a tunable response to photochemical coupling, varying from a fully excitatory response to a fully inhibitory response. Their response can be tuned through variations in either the reactive mixture or, on an individual micro-reactor level, by changes in the synthesis temperature used during the fabrication of the silica …

Computational Approaches For Diagnosing Neurological Impairments And Restoring Functional Movement, Serhii Bahdasariants

Graduate Theses, Dissertations, and Problem Reports (ETD)

Movement is the primary means by which the nervous system converts intention into interaction with the environment. Voluntary limb motion enables standing, walking, reaching, and grasping—actions that underpin self‑care, communication, and economic participation. When diseases or injuries disrupt the pathways that couple neural commands to muscle forces—whether through cortical stroke, spinal cord injury, or peripheral nerve damage—mechanical outcomes such as weakness, loss of coordination, and ultimately reduced mobility emerge. These impairments cascade into secondary complications, increased dependence on caregivers, and diminished quality of life. Quantifying how the lesion alters the mechanics of movement is therefore essential for designing targeted interventions …

A Framework For Biomimetic Robot Design Applied To The Development Of A Robotic Model Of Drosophila Melanogaster, Clarissa A. Goldsmith

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, “biomimetic” robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. Much of this work involves biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which necessitate …

Behavioral And Neural Evidence For Perceptual Inference Of Position, Sharif Saleki

Dartmouth College Ph.D Dissertations

Extensive neuroscientific research has advanced our knowledge of the mechanisms involved in the detection and recognition of visual stimuli. However, to guide flexible behavior in a changing world, the brain must also construct stable and coherent perceptual representations from retinal images that are often ambiguous. To resolve ambiguities and uncertainties, the visual system combines its input with other sources of information such as context and prior knowledge to infer the most likely interpretation of a scene. Thus, perception is inherently an inferential process that goes beyond simple detection or recognition of stimuli. Although inference has been studied in many areas …

Robust And Generalizable Representations In The Hippocampus, Hung-Tu Chen

Dartmouth College Ph.D Dissertations

An intelligent system must balance generalizing across similar experiences with maintaining the distinctiveness of each experience. This thesis explores how the hippocampus manages this balance through its neural representations to support adaptive behavior. In Chapter 1, I provide an overview of key hippocampal phenomena that contribute to this process, including remapping, splitter signal, and replay. In Chapter 2, I challenge the concept of random remapping by showing that it is possible to predict, better than chance, how a given experience will be encoded in the hippocampus across different subjects. This suggests that encoding of related experiences, which was previously thought …

Early Onset Alzheimer’S Disease Markers In Mouse Hippocampus Unveiled By Single-Cell Transcriptomic Analysis Following Cranial Radiotherapy, Tuba Aksoy

Dissertations and Theses (Open Access)

Cranial radiation therapy plays an integral role in the treatment of brain tumors but can lead to progressive cognitive deficits in survivors by mechanisms that are poorly understood. To develop preventive or mitigative strategies, it is crucial to better understand the underlying pathogenesis of radiation-induced cognitive impairments. The study investigated single-cell transcriptomics and DNA methylation changes as potential drivers of persistent cellular dysfunction after radiation exposure, specifically concentrating on the CA1-3 regions of the hippocampus and the prefrontal cortex due to their role in cognitive functions. Thirteen-week-old mice underwent whole-brain radiation at clinically relevant doses. Following whole-brain radiation, an assessment …

Genomic Data Science Approaches For Understanding Human Diseases, Snehal Shah

All Dissertations

The intricate interplay of genetic predisposition, environmental influences, and lifestyle acts as the multifactorial landscape of diseases. Understanding this complexity presents a significant challenge. Molecular insights into disease mechanisms, particularly the interactions of DNA, RNA, and proteins with environmental and lifestyle factors, have revolutionized disease diagnosis, prognosis, and treatment. High-throughput technologies, such as next-generation sequencing, generate large amounts of molecular data, holding a wealth of knowledge. These datasets unveil the roles of genes and their interactions with various factors through analysis, shedding light on previously unknown molecular mechanisms underlying disease pathogenesis. Furthermore, they facilitate the discovery of biomarkers crucial for …

Analysis And Computation Of Constrained Sparse Coding On Emerging Non-Von Neumann Devices, Kyle Henke

Mathematics & Statistics ETDs

This dissertation seeks to understand how different formulations of the neurally inspired Locally Competitive Algorithm (LCA) represent and solve optimization problems. By studying these networks mathematically through the lens of dynamical and gradient systems, the goal is to discern how neural computations converge and link this knowledge to theoretical neuroscience and artificial intelligence (AI). Both classical computers and advanced emerging hardware are employed in this study. The contributions of this work include:

1. Theoretical Work: A comprehensive convergence analysis for networks using both generic Rectified Linear Unit (ReLU) and Rectified Sigmoid activation functions. Exploration of techniques to address the binary …

Mapping The Neural Circuits That Underlie Metabolic Vs. Emotional Regulation Of Food-Seeking Behavior, Xu Zhang

Dissertations and Theses (Open Access)

Flexibly adjusting food-seeking behaviors based on metabolic needs and environmental threats is crucial for animal survival. In humans, maladaptive food-seeking behaviors that contravene energy homeostasis, which is often driven by food-associated cues with hedonic reward values, lead to obesity and eating disorders. However, the neural mechanisms underlying the modulation of cued food-seeking behaviors by distinct metabolic and threat states remain elusive. Using an approach-food vs. avoid-predator threat conflict test in rats, we identified a subpopulation of neurons in the anterior portion of the paraventricular thalamic nucleus (aPVT) which express corticotrophin-releasing factor (CRF) and are preferentially recruited to respond to food …

Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed

Dissertations and Theses (Open Access)

Operant conditioning (OC) is a form of associative learning in which an animal modifies its behavior based on the consequences that follow that behavior. Despite its ubiquity, the underlying mechanisms of OC are poorly understood. Insights into the mechanisms of OC can be obtained by studying Aplysia feeding behavior as it can be modified by OC. This behavior is mediated by a central pattern generator (CPG) network in the buccal ganglia that contains a relatively small number of neurons. This CPG generates rhythmic motor patterns (BMPs) that move food into the gut by closing a tongue-like structure (i.e., radula) during …

The Genomics Of Champ1: Insights Into Their Cell-Type Specificity And Developmental Trajectories, Zoe Marie Van Caugherty

MUSC Theses and Dissertations

Chromosome alignment maintaining phosphoprotein 1(CHAMP1) is a gene that encodes a zinc finger protein that is involved in in the maintenance of kinetochore-microtubule attachment and regulating chromosome segregation in mitosis. (Itoh et al., 2011) CHAMP1 mutations have been shown to be major risk factors for neurodevelopmental disorders (NDDs) and autism spectrum disorder (ASD).(Asakura et al., 2021; Isidor et al., 2016; Levy et al., 2022) Although there is information on the link between CHAMP1 mutations and NDD, the role of CHAMP1 in regulating processes of human cortical development, namely, neurogenesis, proliferation, and electrophysiological properties of newly born neurons, is unknown. This …