Neuroscience and Neurobiology Commons^™

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 …

Improved Efficiency And Sensitivity Analysis Of 3-D Agent-Based Model For Pain-Related Neural Activity In The Amygdala, Kayla Kraeuter, Carley Reith, Benedict J. Kolber, Rachael Miller Neilan

Spora: A Journal of Biomathematics

Neuropathic pain is caused by nerve injury and involves brain areas such as the central nucleus of the amygdala (CeA). We developed the first 3-D agent-based model (ABM) of neuropathic pain-related neurons in the CeA using NetLogo3D. The execution time of a single ABM simulation using realistic parameters (e.g., 13,000 neurons and 22,000+ neural connections) is an important factor in the model’s usability. In this paper, we describe our efforts to improve the computational efficiency of our 3-D ABM, which resulted in a 28% reduction in execution time on average for a typical simulation. With this upgraded model, we performed …

Astrocyte Spatial Distribution Affects Growth Dynamics Of Breast Cancer Brain Metastases: An Agent-Based Modeling Study, Rupleen Kaur

Biology and Medicine Through Mathematics Conference

No abstract provided.

Fusing Classic Motion Energy Models And Deep Learning For Coarse-To-Fine Moving Object Segmentation, Matthias Tangemann, Matthias Kümmerer, Matthias Bethge

MODVIS Workshop

Classic motion energy models are able to predict a wide range of physiological and behavioral aspects of motion perception in humans. Whether these models can be used as a basis for higher-level tasks, such as moving object segmentation, has however hardly been explored yet. Here, we present a model that combines a motion energy representation with recent computer vision approaches for figure-ground segmentation of naturalistic stimuli. We find that unlike established motion segmentation models but similar to humans, our model generalizes to random-dot stimuli when only trained on RGB videos.

Perceptual Grouping With Latent Noise, Ben Lonnqvist, Zhengqing Wu, Michael H. Herzog

MODVIS Workshop

Humans effortlessly group elements into objects and segment them from the background and other objects without supervision. For example, the black and white stripes of a zebra are grouped together despite vastly different colors. A thorough theoretical and empirical account of perceptual grouping is still missing – Deep Neural Networks (DNNs), which are considered leading models of the visual system still regularly fail at simplistic perceptual grouping tasks. Here, we propose a counterintuitive unsupervised computational approach to perceptual grouping and segmentation: that they arise because of neural noise, rather than in spite of it. We show that adding noise in …

Facilitation In Pattern Motion Perception Of Self-Operated Stimuli Explained By Adaptive Contrast Normalization, Fulvio Missoni, Francesca Peveri, Andrea Canessa, Giulia Sedda, Vittorio Sanguineti, Silvio P. Sabatini

MODVIS Workshop

Movement can affect the way we make sense of complex visual information. To investigate this issue, we designed an experiment to assess changes of plaid motion perception threshold after a period of sensorimotor contingency experience. We found that movement training facilitates combination of elementary motion cues into a global motion percept. No changes in perceptual thresholds are observed in a passive visual condition. A Bayesian model suggested a reduction, after training, of the cross-talk between two gratings with unbalanced contrasts in corresponding sensory channels. To test plausible neural mechanisms for active reduction of cross-talk in cortical representation of complex visual …

Modeling Human Temporal Eeg Responses To Vr Visual Stimuli, Richard R. Foster, Connor Delaney, Dean J. Krusienski, Cheng Ly

Biology and Medicine Through Mathematics Conference

No abstract provided.

Normalization With Dynamic Weights Predicts Neural And Behavioral Effects Of Orientation Adaptation, Huseyin Boyaci

MODVIS Workshop

Prolonged exposure to an oriented contour causes adaptation and has nontrivial effects on neural activity and perception. For example, the neuron's response amplitude may change (suppression or facilitation), the width of its tuning curve may change (broadening or sharpening), and its preferred orientation may shift (repulsion or attraction). Perceptually, adaptation affects the perceived orientation of a subsequently presented contour (direct and indirect tilt aftereffect) and alters orientation discrimination thresholds. In this study, I show that the normalization model with dynamic weights can predict these empirical results.

Local Geometry Of Elementary Visual Computations, Peter Neri

MODVIS Workshop

Visual operators (e.g. edge detectors) are classically modelled using small circuits involving canonical computations, such as template-matching and gain control. Circuit models explain many aspects of the empirical descriptors that are used to characterize local visual operators, from sensitivity to classification images. Notwithstanding their utility, these models fail to provide a unified framework encompassing the variety of effects observed experimentally, such as the impact of contrast, SNR, and attention on the above descriptors. My goal is to start with a simple, plausible geometrical representation of the perceptual operation carried out by the observer, and to show that this representation is …

Do Mechanisms Of Sinusoidal Contrast Sensitivity Account For Edge Sensitivity?, Lynn Schmittwilken, Felix A. Wichmann, Marianne Maertens

MODVIS Workshop

No abstract provided.

Spike Timing-Dependent Plasticity And Synaptic Scaling Invoke Episodic Bursting In An Excitatory Recurrent Neuronal Population, Ryno Chen, Gregory D. Conradi Smith

Biology and Medicine Through Mathematics Conference

No abstract provided.

Characterization Of Perceptual Spaces From Triadic Similarity Judgments, Jonathan Victor

MODVIS Workshop

Perceptual spaces are mental workspaces that organize a sensory or cognitive domain into a format that supports functions such as comparison, grouping, learning, and generalization. Determining the geometry of a perceptual space – i.e., the properties of the perceptual distances within the space -- is thus crucial not only to understand these intermediate levels of processing at an algorithmic level, but also as a starting point for comparison with neural measures of similarity. While perceptual spaces are often taken to be Euclidean or nearly so (the classic example is trichromatic color space), this assumption, when tested, is often violated. Moreover, …

A Foveated Model Of Visual Discrimination Based On Windowed Texture Statistics, Jan W. Kurzawski, William F. Broderick, Eero P. Simoncelli, Jonathan Winawer

MODVIS Workshop

Most information from visual scenes is discarded by the human nervous system and thus cannot influence visual behavior. Here, we investigated the loss of spatial pattern information. This loss increases dramatically with eccentricity. Recently, models have been developed that average image features in pooling windows whose diameters scale with eccentricity. These models can be used to synthesize “metamers” of natural scenes, images which are physically different but perceptually indistinguishable. Psychophysical experiments have identified the maximum window scaling for which model discrimination abilities match human performance (“critical scaling”). If images are synthesized with pooling windows that exceed critical scaling (“supercritical scaling”), …

Dissecting Bayes: Using Influence Measures To Test Normative Use Of Probability Density Information Derived From A Sample, Laurence T. Maloney, Keiji Ota

MODVIS Workshop

Bayesian decision theory (BDT) is used to model human performance in tasks where the decision maker must compensate for uncertainty in order to gain rewards and avoid losses. BDT prescribes how the decision maker can combine available data, prior knowledge, and value to reach a decision maximizing expected winnings. Do human decision makers actually use BDT in making decisions? Researchers typically compare overall human performance (total winnings or overall percent correct) to the predictions of BDT but we cannot conclude that BDT is an adequate model for human performance based on just overall performance. We break BDT down into elementary …

Explaining The Staircase Gelb Illusion, Simultaneous Contrast, And Perceptual Fading Of Stabilized Images With A Neural Model Driven By Fixational Eye Movements, Michael E. Rudd

MODVIS Workshop

A neural model of lightness computation driven by fixational eye movements is described and used to simulate various lightness phenomenon, including the Staircase Gelb illusion and its variants, simultaneous contrast, the Chevreul illusion, and perceptual fading of stabilized images. The model provides a precise account of the lightness matches from several experiments, with an overall error of only 1.5%. In the model, spatial maps of transient ON and OFF cell activations—produced as the eyes traverse the visual scene—are sorted by eye movement direction in visual cortex. At a subsequent processing stage, the activations within these maps are summed across space …

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 …