Computational Neuroscience Commons^™

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 …

Delineating Differences In Firing Rate Estimates Of Healthy And Parkinsonian Single-Unit Basal Ganglia Recordings, Richard R. Foster, Cheng Ly

Biology and Medicine Through Mathematics Conference

No abstract provided.

Gap Junction Architecture And Synchronization Clusters In The Thalamic Reticular Nuclei, Alex Norwood

Biology and Medicine Through Mathematics Conference

No abstract provided.

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 …

Web Application For Simulation Of An Agent-Based Model In Netlogo3d, Chris Davis Perumal, Abraham Nofal, Benedict J. Kolber, Rachael Miller Neilan

Spora: A Journal of Biomathematics

Agent-based models (ABMs) are computer simulation models for studying systems of autonomous agents. Modelers often use specialized software like NetLogo to develop ABMs, but this software poses barriers to researchers in other disciplines with no prior programming experience. To address this issue, we developed a web application that allows users to simulate our ABM via a web browser, eliminating the need for the user to download and use specialized software. While presented in the context of a specific ABM, our approach can be applied to other ABMs to enhance accessibility. The ABM presented here was developed in NetLogo3D. The model …

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 …

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 …

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.

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.

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 …

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 …

A Causal Inference Approach For Spike Train Interactions, Zach Saccomano

Dissertations, Theses, and Capstone Projects

Since the 1960s, neuroscientists have worked on the problem of estimating synaptic properties, such as connectivity and strength, from simultaneously recorded spike trains. Recent years have seen renewed interest in the problem coinciding with rapid advances in experimental technologies, including an approximate exponential increase in the number of neurons that can be recorded in parallel and perturbation techniques such as optogenetics that can be used to calibrate and validate causal hypotheses about functional connectivity. This thesis presents a mathematical examination of synaptic inference from two perspectives: (1) using in vivo data and biophysical models, we ask in what cases the …

Here Come The Test Results: An Analysis Of Games In Experimental Design For Neuroscience Research, Madison Mcdougall

Scripps Senior Theses

A large part of experimental design in neuroscience revolves around the tasks that are designed for participants to complete to understand the complex system that is the brain. However, as Alan Newell pointed out in his 1973 paper, “You can’t play 20 questions with nature and win,” as designed tasks often answer a binary question that limits their contribution to understanding the brain as a system or a “genuine slab of human behavior.” Games provide an apt solution to this problem, as their complexity embodies a naturalistic task while their well-defined rules create a robust experimental system. Video games specifically …

Destined Failure, Chengjun Pan

Masters Theses

I attempt to examine the complex structure of human communication, explaining why it is bound to fail. By reproducing experienceable phenomena, I demonstrate how they can expose communication structure and reveal the limitations of our perception and symbolization.I divide the process of communication into six stages: input, detection, symbolization, dictionary, interpretation, and output. In this thesis, I examine the flaws and challenges that arise in the first five stages. I argue that reception acts as a filter and that understanding relies on a symbolic system that is full of redundancies. Therefore, every interpretation is destined to be a deviation.

Neural Tabula Rasa: Foundations For Realistic Memories And Learning, Patrick R. Perrine

Master's Theses

Understanding how neural systems perform memorization and inductive learning tasks are of key interest in the field of computational neuroscience. Similarly, inductive learning tasks are the focus within the field of machine learning, which has seen rapid growth and innovation utilizing feedforward neural networks. However, there have also been concerns regarding the precipitous nature of such efforts, specifically in the area of deep learning. As a result, we revisit the foundation of the artificial neural network to better incorporate current knowledge of the brain from computational neuroscience. More specifically, a random graph was chosen to model a neural system. This …

The Genomics Of Autism-Related Genes Il1rapl1 And Il1rapl2: Insights Into Their Cortical Distribution, Cell-Type Specificity, And Developmental Trajectories, Jacob Weaver

MUSC Theses and Dissertations

Neuropsychiatric disorders have a significant impact on modern society. These disorders affect a large percentage of the population: schizophrenia has a world-wide prevalence of 1% and autism spectrum disorders (ASD) affects 1 in 59 school-aged children in the US. There is substantial evidence that most neuropsychiatric disorders have a genetic component. Thus, with the advent of high throughput sequencing much effort has gone into identifying genetic variants associated with these disorders. The emerging picture from these studies is a complex one where hundreds of genes with small effects interact with a varied landscape of common variants to result in disease. …

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 …

The Distinction Of Logical Decision According To The Model Of The Analysis Of Brain Signals (Eeg), Akeel Abdulkareem Al-Sakaa, Zaid H. Nasralla, Mohsin Hasan Hussein, Saif A. Abd, Hazim Alsaqaa, Kesra Nermend, Anna Borawska

Karbala International Journal of Modern Science

Recently, brain signal patterns have been recruited by researchers in different life activities. Researchers have studied each life activity and how brain signal patterns appear. These patterns could then be generalised and used in different disciplines. In this paper, we study the brain state during decision making in a lottery experiment. An EEG device is used to capture brain signals during an experiment to extract the optimal state for logical decision making. After collecting data, extracting useful information and then processing it, the proposed method is able to identify rational decisions from irrational ones with a success rate of 67%.

Mixed Mode Oscillations In Three-Timescale Coupled Morris-Lecar Neurons, Ngocanh Phan, Yangyang Wang

Biology and Medicine Through Mathematics Conference

No abstract provided.

Estimating Glutamate Transporter Surface Density In Mouse Hippocampal Astrocytes, Anca R. Radulescu, Annalisa Scimemi

Biology and Medicine Through Mathematics Conference

No abstract provided.

Automated Fitting Of Allosteric Parameters In Receptor Oligomer Models, Spenser Wood

Biology and Medicine Through Mathematics Conference

No abstract provided.

Olfactory Bulb Processing Of Ortho Versus Retronasal Odors, Michelle F. Craft, Andrea Barreiro, Shree Gautam, Woodrow Shew, Cheng Ly

Biology and Medicine Through Mathematics Conference

No abstract provided.

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …

Scale-Free Behavioral Dynamics Directly Linked With Scale-Free Cortical Dynamics, Sabrina Jones

Physics Undergraduate Honors Theses

In organisms, an interesting phenomenon occurs in both behavior and neuronal activity: organization with fractal, scale-free fluctuations over multiple spatiotemporal orders of magnitude (1,2). In regard to behavior, this sort of complex structure-- which manifests itself from small scale fidgeting to purposeful, full body movements-- may support goals such as foraging (3-6), visual search (4), and decision making (7,8). Likewise, the presence of this sort of structure in the cerebral cortex in the form of spatiotemporal cascades, coined “neuronal avalanches,” may offer optimal information transfer (9). Thus, when considering the functional relationship between the cerebral cortex and movements of the …

When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki

Dissertations and Theses

Many day-to-day tasks involve processing of complex visual information in a continuous stream. While much of our knowledge on visual processing has been established from reductionist approaches in lab-controlled settings, very little is known about the processing of complex dynamic stimuli experienced in everyday scenarios. Traditional investigations employ event-related paradigms that involve presentation of simple stimuli at select locations in visual space and discrete moments in time. In contrast, visual stimuli in real-life are highly dynamic, spatially-heterogeneous, and semantically rich. Moreover, traditional experiments impose unnatural task constraints (e.g., inhibited saccades), thus, it is unclear whether theories developed under the reductionist …

Nonlinear Control Of Biological Dynamical Systems, Megan J. Morrison

Biology and Medicine Through Mathematics Conference

No abstract provided.

Using Machine Learning To Conduct A Detailed Behavioral Analysis In An Appetitive Social Learning Task, Thomas Shao

Honors Scholar Theses

Learning by watching others, or observational learning, is important for social development and survival. However, not much is known about the brain mechanisms underlying this type of learning. Since the 1960s, observational learning has been widely studied in humans, but developing and analyzing experiments for animals has been challenging. Here, I explore observational learning using a novel paradigm while performing an analysis that involves tracking the rats using an active learning paradigm called DeepLabCut. In this novel paradigm, customized operant conditioning chambers are used for the rats to observe and learn from another animal repeatedly on multiple trials each day. …

Mechanisms Of Value-Biased Prioritization In Fast Sensorimotor Decision Making, Kivilcim Afacan-Seref

Dissertations and Theses

In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively, but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. This research examines the behavioral and electrophysiological indices of how value biases split-second perceptual decisions and the possible mechanisms underlying the process. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases …

Bifurcation Analysis Of A Photoreceptor Interaction Model For Retinitis Pigmentosa, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.

Spiking Activity In Networks Of Neurons Impacted By Axonal Swelling, Brian Frost, Stan Mintchev

Biology and Medicine Through Mathematics Conference

No abstract provided.