Physical Sciences and Mathematics Commons^™

High Fat Diet & Social Isolation: Interactive Effects On Pain, Cognition, & Neuroinflammation, Ian M. Campuzano

Research Psychology Theses

Prior research has established a role for both social isolation and exposure to high fat Western diets in altering a range of behaviors from reduced memory performance to increased depression-like behaviors. The present study scrutinizes the interplay among these variables during the peri-adolescent developmental phase, utilizing Long-Evans rats as the experimental model. Our overarching hypothesis is that rats exposed to either social isolation, a high-fat diet, or both will result in heightened pain sensitivity, diminished cognitive flexibility, and increased neuroinflammatory responses within brain regions implicated in sociability, cognition, memory, and pain processing. Behavioral flexibility will be assessed using a maze-based …

Quantifying Resting-State Functional Connectivity In Critically Brain-Injured Patients: A Graph-Theoretical Approach With Fnirs, Ira Gupta

Electronic Thesis and Dissertation Repository

Assessment of consciousness in behaviourally unresponsive patients with critical brain injuries continues to be a challenge. There remains a need for robust tools that can accurately characterize preserved cortical function and predict patient outcomes. In the present study, functional near-infrared spectroscopy is employed in conjunction with graph theory and machine learning to quantify resting-state functional connectivity in 16 acutely brain-injured patients and 23 healthy controls. Results revealed significant channel-level differences between the groups for three graph metrics, including degree, clustering coefficient, and local efficiency. Further investigation using machine learning algorithms revealed that these metrics can be used to distinguish between …

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 …

The Relationship Between Amygdala And Orbitofrontal Cortex Volume In The Context Of Oppositional Defiant Disorder, Rahul Alla

Honors Scholar Theses

Disobedient and rebellious attitude in children is on the rise and this type of behavior is categorized as Oppositional Defiant Disorder (ODD). ODD in children can be identified as a persistent pattern of angry or irritable mood, argumentative or defiant behavior or vindictiveness toward others according to the Diagnostic and Statistical Manual (DSM-5, Fifth Edition) of Mental Disorders.1 Children with ODD typically have difficulty regulating and processing their emotions. Issues with regulating emotions is defined as the process by which individuals “influence which emotions they have, when they have them, and how they experience and express them”.2 Dysregulation of emotions …

Unraveling The Neural Basis Of Emotions: Advancing Understanding With Ecologically Valid Paradigms And High-Resolution Intracranial Eeg, Tiankang Xie

Dartmouth College Ph.D Dissertations

Background

Emotion arises from integrating information about the external world with memories of past experiences, current homeostatic states, and future goals. They play a vital role in regulating our thoughts, feelings and behaviors, significantly impacting our mental health. Thus, it is important to understand the neurobiological mechanisms that give rise to emotions. While there has been considerable work investigating the neural basis of emotions, progress has been hampered by several methodological limitations. For example, prior work has relied on relatively simple and isolated stimuli, which often fail to effectively capture the dynamic and multifaceted nature of emotional experiences in real-life …

Attention Visual, Baris Dingil

College of Computing and Digital Media Dissertations

This research presents an innovative approach to improving visual-spatial attention using a research tool based on the web. Recognizing the significant role visual-spatial attention plays in everyday life and cognitive function for humans, this research was undertaken with the aim of developing a user-friendly, accessible web-based tool called Attention Visual (attentionvisual.com) to enhance this crucial cognitive skill. This tool also facilitates data collection, potentially accelerating the pace and enhancing the quality of related research. Both qualitative and quantitative methods were utilized for data collection and analysis. In order to stimulate improvements in visual-spatial attention, the tool’s algorithm was structured to …

A Dynamical Model Of Binding In Visual Cortex During Incremental Grouping And Search, Daniel Schmid, Daniel A. Braun, Heiko Neumann

MODVIS Workshop

Binding of visual information is crucial for several perceptual tasks. To incrementally group an object, elements in a space-feature neighborhood need to be bound together starting from an attended location (Roelfsema, TICS, 2005). To perform visual search, candidate locations and cued features must be evaluated conjunctively to retrieve a target (Treisman&Gormican, Psychol Rev, 1988). Despite different requirements on binding, both tasks are solved by the same neural substrate. In a model of perceptual decision-making, we give a mechanistic explanation for how this can be achieved. The architecture consists of a visual cortex module and a higher-order thalamic module. While the …

Do Plants Have The Cognitive Complexity For Sentience?, Ricard V. Solé

Animal Sentience

Are plants sentient? Like other aspects of the cognitive potential of plants, this is a controversial issue, often driven by analogies and seldom supported on solid theoretical grounds. Sentience is understood in cognitive sciences as the capacity to feel. I suggest that because of plants’ evolved adaptations to morphological plasticity, sessile nature and ecological constraints, they are unlikely to have the requisite cognitive complexity for sentience.

Intellectual Disability Related To De Novo Germline Loss Of The Distal End Of The P-Arm Of Chromosome 17: A Case Report, Eden Pope, Matthew Huertas, Amar Paul, Braden Cunningham, Matthew Jennings, Ryan Perry, Stephanie Chavez, John A. Kriak, Kyle B. Bills, David W. Sant

Annual Research Symposium

Hypothesis/Purpose: In this report we present a case of a 20-year-old female with congenital intellectual disability, stunted growth, and hypothyroidism. Competitive genetic hybridization (CHG) revealed a loss of 17p13.3, and the deletion was not present in either parent. This deletion has not previously been characterized, but mutations on the p-arm of chromosome 17 are responsible for Miller-Dieker Syndrome and Isolated Lissencephaly Sequence, both of which share symptoms in common with the patient.

Methods: Peripheral mononuclear cells (PBMCs) were used for karyotyping and competitive genetic hybridization (CHG). Bioinformatic analysis was carried out using the Genome Data Viewer (ncbi.nlm.nih.gov/genome/gdv).

Results: Karyotype was …

Reversible Emerging Neuropsychological Pattern In Chronic Intractable Migraine, Tanner Williford, Pooja Chemiti, Mason Allen, Brandon Burrell, Stephanie Chavez, Jude Emego, Bridger Gunter, Matthew Huertas, Matthew Jennings, Roshni Jogin, Paulo Kelly, Laura Minor, Steven Salazar, Jameson Williams, David W. Sant, John A. Kriak, Kyle B. Bills

Annual Research Symposium

No abstract provided.

Heterodyned Whole-Body Vibration Ameliorates Anxiety In Opioid-Use Disorder, Kailee Edwards, Braden Cunningham, Alfred Amendolara, Marryam Anwar, Jon Gonzales, Roshni Jogin, Wyatt Magoffin, Amar Paul, Ryan Perry, James Pike, Nathan Swallow, Steven Tung, Mary Seamons, Andrew Payne, John A. Kriak, David W. Sant, David W. Sant

Annual Research Symposium

No abstract provided.

Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer

Honors Theses and Capstones

Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) …

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%.

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

An Implementation Of Integrated Information Theory In Resting-State Fmri, Idan E. Nemirovsky

Electronic Thesis and Dissertation Repository

Integrated Information Theory (IIT) is a framework developed to explain consciousness, arguing that conscious systems consist of interacting elements that are integrated through their causal properties. In this study, we present the first application of IIT to functional magnetic resonance imaging (fMRI) data and investigate whether its principal metric, Phi, can meaningfully quantify resting-state cortical activity patterns. Data was acquired from 17 healthy subjects who underwent sedation with propofol, a short acting anesthetic. Using PyPhi, a software package developed for IIT, we thoroughly analyze how Phi varies across different networks and throughout sedation. Our findings indicate that variations in Phi …

Do Environmental Toxins Predict Violent Crimes?, Tyler Stahl

Symposium of Student Scholars

Do chemical pollutants that persistent in the environment and bioaccumulate in the body affect human health and behavior? Could these Persistent, Bioaccumulative, and Toxic (PBT) chemicals play a role in the cause of violent crimes due to deterioration of mental and cognitive functions? In the past, Mercury, a PBT chemical, has been shown in salmon to be associated with aggression. Could similar aggression occur in humans exposed to mercury through a toxic spill? Two sources of data are utilized in this analysis. The Environmental Protection Agency’s (EPA) Annual Toxic Release Inventory publishes data on toxic releases into the environment and …

Medical Schools Ignore The Nature Of Consciousness At Great Cost, Anoop Kumar

Journal of Wellness

The essential question of the relationship between consciousness and matter is ignored in medical school curricula, leading to a machine-like view of the human being that contributes to physician burnout and intellectual dissatisfaction. The evidence suggesting that the brain may not be the seat of consciousness is generally ignored to preserve the worldview of the primacy of matter. By investigating new frameworks detailing the nature of consciousness at different levels of hierarchy, we can bring intellectual rigor to a once opaque subject that supports a fundamental reality about our experience: We are human beings, not only human bodies.

Exercise, Cognition, And Cannabis Use In Adolescents, Ileana Pacheco-Colón

FIU Electronic Theses and Dissertations

Heavy and/or chronic cannabis use has been associated with neurocognitive impairment and decline, often in domains such as memory and executive functioning. On the other hand, exercise has been linked to positive effects on brain and cognitive health across the lifespan, as well as to better substance use outcomes. Despite this, little is known about the ways in which exercise could help prevent or ameliorate adverse cannabis-related outcomes among adolescents.

Through three separate studies, the current dissertation examines interrelations among exercise, cognition, and cannabis use in children and adolescents in an effort to determine whether exercise can prevent or ameliorate …

Using Deep Learning For Children Brain Image Analysis, Rafael Toche Pizano

Computer Science and Computer Engineering Undergraduate Honors Theses

Analyzing the correlation between brain volumetric/morphometry features and cognition/behavior in children is important in the field of pediatrics as identifying such relationships can help identify children who may be at risk for illnesses. Understanding these relationships can not only help identify children who may be at risk of illnesses, but it can also help evaluate strategies that promote brain development in children. Currently, one way to do this is to use traditional statistical methods such as a correlation analysis, but such an approach does not make it easy to generalize and predict how brain volumetric/morphometry will impact cognition/behavior. One of …

Cortical Dynamics Of Language, Kiefer Forseth

Dissertations & Theses (Open Access)

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches.

Application Of Cycle-By-Cycle Analysis To Eeg Data From Individuals With Phelan-Mcdermid Syndrome, Naomi Miller

ENGS 88 Honors Thesis (AB Students)

This study aimed to analyze a novel method of processing data from electroencephalography (EEG) recordings, which implements time-domain cycle-by-cycle analysis. This "bycycle" method, developed by the Cole & Voytek laboratory, was implemented on a EEG dataset of children with and without Phelan-McDermid Syndrome in the hopes of uncovering network-level explanations for the genetic disorder. A supplemental Python pipeline was developed to organize and visualize the data. This led to the discovery of group-level differences in measures of cycle symmetry in alpha band waves over the sensorimotor electrodes. Through the same pipeline, the bycycle tool was validated as a sound EEG …

Comparison Of Longitudinal Changes In Resting State Functional Magnetic Resonance Imaging Between Alzheimer’S And Healthy Controls, Berk Can Yilmaz

Theses

Resting State Functional Magnetic Resonance Imaging (rs-fMRI) is a technique that is widely used for analyzing brain function using different approaches and methods. This study involves rs-fMRI analysis of Blood Oxygenation Level Dependent (BOLD) signals acquired from Alzheimer’s disease (AD) Patients and Healthy Controls (HC). Each subject in the study had both functional and anatomical images with at least one rs-fMRI scan with their Anatomical (T1) scans. Previous rs-fMRI studies have demonstrated that AD shows differences in Amplitude of Low Frequency (<0.1 Hz) Fluctuations (ALFF), and Regional Homogeneity (ReHo) measures according to HCs.

The aim of the study is to investigate individual and group level differences using ReHo and mALFF related …

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 …

Image And Video-Based Autism Spectrum Disorder Detection Via Deep Learning, Mindi Ruan

Graduate Theses, Dissertations, and Problem Reports

People with Autism Spectrum Disorder (ASD) show atypical attention to social stimuli and aberrant gaze when viewing images of the physical world. However, it is unknown how they perceive the world from a first-person perspective. In this study, we used machine learning to classify photos taken in three different categories (people, indoors, and outdoors) as either having been taken by individuals with ASD or by peers without ASD. Our classifier effectively discriminated photos from all three categories but was particularly successful at classifying photos of people with >80% accuracy. Importantly, the visualization of our model revealed critical features that led …

Biological And Practical Implications Of Genome-Wide Association Study Of Schizophrenia Using Bayesian Variable Selection, Benazir Rowe, Xiangning Chen, Zuoheng Wang, Jingchun Chen, Amei Amei

School of Medicine Faculty Publications

Genome-wide association studies (GWAS) have identified over 100 loci associated with schizophrenia. Most of these studies test genetic variants for association one at a time. In this study, we performed GWAS of the molecular genetics of schizophrenia (MGS) dataset with 5334 subjects using multivariate Bayesian variable selection (BVS) method Posterior Inference via Model Averaging and Subset Selection (piMASS) and compared our results with the previous univariate analysis of the MGS dataset. We showed that piMASS can improve the power of detecting schizophrenia-associated SNPs, potentially leading to new discoveries from existing data without increasing the sample size. We tested SNPs in …

Impact Of Excitation-Inhibition Balance/Imbalance On Dynamics Of Cortical Neural Networks, Vidit Agrawal

Graduate Theses and Dissertations

The purpose of this research is to study the implications of Excitation/Inhibition balance and imbalance on the dynamics of ongoing (spontaneous) neural activity in the cerebral cortex region of the brain.

The first research work addresses the question that why among the continuum of Excitation-Inhibition balance configurations, particular configuration should be favored? We calculate the entropy of neural network dynamics by studying an analytically tractable network of binary neurons. Our main result from this work is that the entropy maximizes at regime which is neither excitation-dominant nor inhibition-dominant but at the boundary of both. Along this boundary we see there …

Feedforward And Feedback Signals In The Olfactory System, Srimoy Chakraborty

Graduate Theses and Dissertations

The conglomeration of myriad activities in neural systems often results in prominent oscillations. The primary goal of the research presented in this thesis was to study effects of sensory stimulus on the olfactory system of rats, focusing on the olfactory bulb (OB) and the anterior piriform cortex (aPC). Extracellular electrophysiological measurements revealed distinct frequency bands of oscillations in OB and aPC. However, how these oscillatory fluctuations help the animal to process sensory input is not clearly understood. Here we show high frequency oscillations in olfactory bulb carry feedforward signals to anterior piriform cortex whereas feedback from the aPC is predominantly …

Exploring The Neural Mechanisms Of Physics Learning, Jessica E. Bartley

FIU Electronic Theses and Dissertations

This dissertation presents a series of neuroimaging investigations and achievements that strive to deepen and broaden our understanding of human problem solving and physics learning. Neuroscience conceives of dynamic relationships between behavior, experience, and brain structure and function, but how neural changes enable human learning across classroom instruction remains an open question. At the same time, physics is a challenging area of study in which introductory students regularly struggle to achieve success across university instruction. Research and initiatives in neuroeducation promise a new understanding into the interactions between biology and education, including the neural mechanisms of learning and development. These …

Ai-Human Collaboration Via Eeg, Adam Noack

All College Thesis Program, 2016-2019

As AI becomes ever more competent and integrated into our lives, the issue of AI-human goal misalignment looms larger. This is partially because there is often a rift between what humans explicitly command and what they actually mean. Most contemporary AI systems cannot bridge this gap. In this study we attempted to reconcile the goals of human and machine by using EEG signals from a human to help a simulated agent complete a task.

Functional Human Grin2b Promoter Polymorphism And Variation Of Mental Processing Speed In Older Adults, Yang Jiang, Ming Kuan Lin, Gregory A. Jicha, Xiuhua Ding, Sabrina L. Mcilwrath, David W. Fardo, Lucas S. Broster, Frederick A. Schmitt, Richard J. Kryscio, Robert H. Lipsky

Behavioral Science Faculty Publications

We investigated the role of a single nucleotide polymorphism rs3764030 (G > A) within the human GRIN2B promoter in mental processing speed in healthy, cognitively intact, older adults. In vitro DNA-binding and reporter gene assays of different allele combinations in transfected cells showed that the A allele was a gain-of-function variant associated with increasing GRIN2B mRNA levels. We tested the hypothesis that individuals with A allele will have better memory performance (i.e. faster reaction times) in older age. Twenty-eight older adults (ages 65-86) from a well-characterized longitudinal cohort were recruited and performed a modified delayed match-to-sample task. The rs3764030 polymorphism was …