Computational Neuroscience Commons^™

Predicting Dynamics From Hardwiring In Canonical Low-Dimensional Coupled Networks, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.

Variance Partitioning Reveals Consistent Representation Of Object Boundary Contours In Lo Across Different Datasets, Mark D. Lescroart, Utkarsh Singhal

MODVIS Workshop

No abstract provided.

The 5-Ht1a-R Knockout Mouse As A Model Of Later Life Anxiety Disorders: Implications For Sex Differences, Tatyana Budylin

Dissertations, Theses, and Capstone Projects

Anxiety affects nearly twice as many women as it affects men across all cultures and economic groups. Importantly, girls have a higher chance of inheriting anxiety disorders than boys, and many anxiety disorders appear at a very young age. However, little is known about sex differences in brain and behavioral development and how they relate to anxiety in adulthood. Serotonin 1A receptor (5-HT_1A-R) mediated signaling has been implicated in depression and anxiety, however most studies that focus on the involvement of the 5-HT_1A-R have been conducted in adults. Little is known about how the 5-HT_{1A …}

Calculating The Dimensionality Of The Brain, And Other Applications Of An Optimized Generalized Ising Model In Predicting Brain's Spontaneous Functions, Pubuditha M. Abeyasinghe

Electronic Thesis and Dissertation Repository

Understanding a system as complex as the human brain is a very demanding task. Directly working with structural and functional neuroimaging data has led to most of the understanding we have gained about the human brain. However, performing only the direct statistical comparisons on the empirical function and the structure does not fully explain the observed long-range functional correlations. Therefore, implementations of mathematical models to gain further understanding of the relationship between the structure and function of the brain is critical. Additionally, spontaneous functions of the brain can only be predicted using computer simulated models; which will be pivotal for …

Ultra-High Field Magnetic Resonance Imaging For Stereotactic Neurosurgery, Jonathan Lau

Electronic Thesis and Dissertation Repository

Stereotactic neurosurgery is a subspecialty within neurosurgery concerned with accurate targeting of brain structures. Deep brain stimulation (DBS) is a specific type of stereotaxy in which electrodes are implanted in deep brain structures. It has proven therapeutic efficacy in Parkinson’s disease and Essential Tremor, but with an expanding number of indications under evaluation including Alzheimer’s disease, depression, epilepsy, and obesity, many more Canadians with chronic health conditions may benefit. Accurate surgical targeting is crucial with millimeter deviations resulting in unwanted side effects including muscle contractions, or worse, vessel injury. Lack of adequate visualization of surgical targets with conventional lower field …

Cognitive Rehabilitation Of Prospective Memory Deficits After Acquired Brain Injury: Cognitive, Behavioral, And Physiological Measures, Meaghan Race

Senior Theses and Projects

Acquired brain injury (ABI) affects approximately 3.5 million Americans each year and is associated with cognitive and emotional changes. Prospective memory (PM) deficits are important predictors of functioning in daily life for individuals with ABI. Previous studies have shown that cognitive rehabilitation therapy (CRT) via PM training has a high rate of success in improving quality of life, independence and productivity for ABI survivors. There is limited information on utilizing imaging techniques in relation to changes in cognition and behavior following rehabilitation; however, previous studies suggest that imaging provides evidence that CRT could be related to changes to underlying brain …

Strengthening Relationships Between Neural Ideals And Receptive Fields, Angelique Morvant

Rose-Hulman Undergraduate Mathematics Journal

Neural codes are collections of binary vectors that represent the firing patterns of neurons. The information given by a neural code C can be represented by its neural ideal J_C. In turn, the polynomials in J_C can be used to determine the relationships among the receptive fields of the neurons. In a paper by Curto et al., three such relationships, known as the Type 1-3 relations, were linked to the neural ideal by three if-and-only-if statements. Later, Garcia et al. discovered the Type 4-6 relations. These new relations differed from the first three in that they were …

A Defense Of Pure Connectionism, Alex B. Kiefer

Dissertations, Theses, and Capstone Projects

Connectionism is an approach to neural-networks-based cognitive modeling that encompasses the recent deep learning movement in artificial intelligence. It came of age in the 1980s, with its roots in cybernetics and earlier attempts to model the brain as a system of simple parallel processors. Connectionist models center on statistical inference within neural networks with empirically learnable parameters, which can be represented as graphical models. More recent approaches focus on learning and inference within hierarchical generative models. Contra influential and ongoing critiques, I argue in this dissertation that the connectionist approach to cognitive science possesses in principle (and, as is becoming …

Timing Is Everything: Temporal Dynamics Of Brain Activity Using The Human Connectome Project, Francesca Lofaro

Summer Research

Most neuroimaging studies produce snapshots of brain activity. The goal of this project is to examine the temporal dynamics of how these areas interact through time, using fear as a case study to assess how regions involved in fear interact. Working with Matlab computer code, I sort through the large fMRI dataset known as the Human Connectome Project to extract neuroimaging data from patients with different NIH Toolbox Fear-Somatic survey scores to assess the temporal dynamics between brain regions. The results will allow an understanding beyond which areas are involved, and instead will provide a picture of how these areas …

Agent Based Model Of Cavitation In Spinal Cord Injury, Rahma Ahmed

Senior Projects Spring 2019

Annually, approximately 375,000 people suffer from spinal cord injury (SCI) worldwide and many SCI patients develop secondary health conditions such as respiratory, cardiovascular, and urinary/bowel complications which negatively impact their daily lives. SCI occurs when there is damage to the spinal cord resulting in decreased motor functions, decreased sensory functions, or paralysis. Days to weeks after initial impact, the lesion (area of injury) continues to increase in size in a process called progressive cavitation which demyelinates axons and inhibits effective axonal regeneration. In an in vitro model of progressive cavitation, Fitch et al. showed that activated macrophages cause cavities to …

The Characterization Of Alzheimer’S Disease And The Development Of Early Detection Paradigms: Insights From Nosology, Biomarkers And Machine Learning, Isabel Milano

CMC Senior Theses

Alzheimer’s Disease (AD) is the only condition in the top ten leading causes of death for which we do not have an effective treatment that prevents, slows, or stops its progression. Our ability to design useful interventions relies on (a) increasing our understanding of the pathological process of AD and (b) improving our ability for its early detection. These goals are impeded by our current reliance on the clinical symptoms of AD for its diagnosis. This characterizations of AD often falsely assumes a unified, underlying AD-specific pathology for similar presentations of dementia that leads to inconsistent diagnoses. It also hinges …

Cortical Stimulation Mapping Of Heschl’S Gyrus In The Auditory Cortex For Tinnitus Treatment, Austin Huang

CMC Senior Theses

Tinnitus is the perception of sound in the absence of an actual sound stimulus. Recent developments have shifted the focus to the central nervous system and the neural correlate of tinnitus. Broadly, tinnitus involves cortical map rearrangement, pathological neural synchrony, and increased spontaneous firing rates. Various cortical regions, such as Heschl’s gyrus in the auditory cortex, have been found to be associated with different aspects of tinnitus, such as perception and loudness. I propose a cortical stimulation mapping study of Heschl’s gyrus using a depth and subdural electrode montage to conduct electrocorticography. This study would provide high-resolution data on abnormal …

Differentiation Of Neurons And Glia For Use In Cellular Connectomics, Jacob T. Brettin

Chancellor’s Honors Program Projects

No abstract provided.

Temporal Information Guides Prefrontal Preparatory Activity, Jacqueline R. Janowich

Shared Knowledge Conference

Proactive preparation for an upcoming goal differs from last-minute reactive adaptation, but it is unclear how preparatory mechanisms change based on when in the future a goal needs to be executed. To assess how timing information is integrated into preparatory control, we designed a novel variant of the Dot Pattern Expectancy task, where each cue signaled both task rule and delay duration (known short, known long, or unknown) between cue and probe. We recorded EEG while healthy young adult participants (n=36) performed this task, and found that delay demands elicited distinct prefrontal preparatory activities. Medial prefrontal amplitude was sensitive to …

Learning Expands The Preplanning Horizon In Finger Sequence Tasks, Neda Kordjazi

Electronic Thesis and Dissertation Repository

Many everyday skills involve the production of complex sequences of movements. However, the dynamics of the interplay between action selection and execution processes in sequential movements is poorly understood.Here, we set out to investigate the extent to which information regarding upcoming actions is utilized by the motor system to preplan into the future and furthermore, how this ability is influenced by learning. We designed a finger sequence taskwhere participants were shown only a fixed number of upcoming cues regarding future presses in every trial (viewing window, W). W varied between 1 (next digit revealed with pressing the current digit – …

Decision Making In A Changing Environment, Alan Veliz-Cuba

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Hopfield Networks: Modeling Memory, Maria Gabriela Navas Zuloaga

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Population Codes And Their Correlates In Decision Making, Neda Shahidi

The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access)

This dissertation was organized in two parts: in part 1, we discussed Neural Correlates of Perceptual Accuracy” and in part 2 we discussed “Strategy encoding in Prefrontal Cortex”.

Abstract of part 1_The accurate transmission of electrical signals within neocortex is central to sensory perception and cognition. Theoretical studies have long proposed that the temporal coordination of cortical spiking activity controls signal transmission and cognitive function. In reality, whether and how the precise temporal coordination in neuronal populations during wakefulness influences perception remains a mystery. Here, we simultaneously recorded populations of neurons in early and mid-level visual cortex (areas V1 …

Finding Nonlinear Relationships In Functional Magnetic Resonance Imaging Data With Genetic Programming, James Hughes

Electronic Thesis and Dissertation Repository

The human brain is a complex, nonlinear dynamic chaotic system that is poorly understood. When faced with these difficult to understand systems, it is common to observe the system and develop models such that the underlying system might be deciphered. When observing neurological activity within the brain with functional magnetic resonance imaging (fMRI), it is common to develop linear models of functional connectivity; however, these models are incapable of describing the nonlinearities we know to exist within the system.

A genetic programming (GP) system was developed to perform symbolic regression on recorded fMRI data. Symbolic regression makes fewer assumptions than …

Mapping Molecular Datasets Back To The Brain Regions They Are Extracted From: Remembering The Native Countries Of Hypothalamic Expatriates And Refugees, Arshad M. Khan, Alice H. Grant, Anais Martinez, Gully Apc Burns, Brendan S. Thatcher, Vishwanath T. Anekonda, Benjamin W. Thompson, Zachary S. Roberts, Daniel H. Moralejo, James E. Blevins

Arshad M. Khan, Ph.D.