Physical Sciences and Mathematics Commons^™

A Model Of Shell Structure And Pattern In Mollusks, Rahnuma Islam, Bard Ermentrout, Sabrina Streipert

Biology and Medicine Through Mathematics Conference

No abstract provided.

Modeling Mechanisms Of Microtubule Dynamics And Polarity In Neurons, Anna Nelson, Veronica Ciocanel, Scott Mckinley, Hannah Scanlon

Biology and Medicine Through Mathematics Conference

No abstract provided.

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.

The Neural Dynamics Of Autism Spectrum Disorder And Typically Developing Individuals: Insights From Eeg Modeling And Mathematical Analysis, Sungwoo Ahn, Evie A. Malaia, Leonid L. Rubchinsky

Biology and Medicine Through Mathematics Conference

No abstract provided.

Assessing The Pre- And Post-Synaptic Effects Of Opioids On Inspiratory Rhythmogenesis, Diego F. Morandi Zerpa, Jingzhi Zhao

Biology and Medicine Through Mathematics Conference

No abstract provided.

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 …

Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen

Theses and Dissertations (Comprehensive)

The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …

Human Brain Function Above All Other And The Creation Model, James D. Johansen

Proceedings of the International Conference on Creationism

The human brain functions at a level beyond any other brain in all of creation. With mankind being made in the image of God, there must be signatures of this fact in its design. Modeling the human brain that develops an architectural framework offers the potential to unpack this reality. This premise offers a rich area to explore that expands the creation model to capture the engineering framework God used in creation. This paper will focus on brain neurons and neural networks using systems engineering modeling tools.

The systems modeling language (SysML) will be used to capture a model of …

Strengthening Brain Research In Africa, Abdullahi Tunde Aborode, Nike Jesutofunmi Idowu, Samuel Tundealao, Joseph Jaiyeola, Ogunware Adedayo Emmanuel

Chemistry Department: Faculty Publications

This paper explores the emerging field of neuroscience in Africa, considering the unique genetic diversity, sociocultural determinants, and health inequalities in the continent. It presents numerous brain research initiatives, such as ABDRN, AMARI, APCDR, and H3Africa, aimed at understanding genetic and environmental factors influencing brain disorders in Africa. Despite numerous challenges like the brain drain phenomenon, inadequate infrastructure, and scarce research expertise, significant progress has been achieved. The paper proposes solutions, including international collaboration, capacity-building efforts, and policies to promote neuroscience research, to enhance the understanding of brain function and address brain-related health issues within the African context.

Using Machine Learning Techniques To Model Encoder/Decoder Pair For Non-Invasive Electroencephalographic Wireless Signal Transmission, Ernst Fanfan

Master of Science in Computer Science Theses

This study investigated the application and enhancement of Non-Invasive Brain-Computer Interfaces (NI-BCIs), focused on enhancing the efficiency and effectiveness of this technology for individuals with severe physical limitations. The core research goal was to improve current limitations associated with wires, noise, and invasive procedures often associated with BCI technology. The key discussed solution involves developing an optimized Encoder/Decoder (E/D) pair using machine learning techniques, particularly those borrowed from Generative Adversarial Networks (GAN) and other Deep Neural Networks, to minimize data transmission and ensure robustness against data degradation. The study highlighted the crucial role of machine learning in self-adjusting and isolating …

The Mandelbrot Set For Networks, Templates And Mutated Systems, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.

Intermittent Synchronization In Gamma-Band Neural Oscillations, Anh Nguyen, Leonid L. Rubchinsky

Biology and Medicine Through Mathematics Conference

No abstract provided.

Leveraging A Machine Learning Based Predictive Framework To Study Brain-Phenotype Relationships, Sage Hahn

Graduate College Dissertations and Theses

An immense collective effort has been put towards the development of methods forquantifying brain activity and structure. In parallel, a similar effort has focused on collecting experimental data, resulting in ever-growing data banks of complex human in vivo neuroimaging data. Machine learning, a broad set of powerful and effective tools for identifying multivariate relationships in high-dimensional problem spaces, has proven to be a promising approach toward better understanding the relationships between the brain and different phenotypes of interest. However, applied machine learning within a predictive framework for the study of neuroimaging data introduces several domain-specific problems and considerations, leaving the …

Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical …

Design And Implementation Of A Low Cost And Portable Tactile Stimulator, Coşkun Kazma, Vecdi̇ Emre Levent, Merve Çardak, Ni̇zametti̇n Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

When central nervous system has a problem, somatic area I and II respond to stimulation differently. Therefore, it is possible to identify some of the central nervous diseases when somatosensory on the fingertip is stimulated and responses are recorded and analyzed. We designed a system to stimulate the mechanoreceptors on fingertips. It is composed of a mechanical system for fingertip stimulation, an embedded controller, a control computer, and a software to control overall operation. During test, mechanoreceptors are stimulated according to the test protocols. Individuals' answers are recorded to be evaluated by the developed software. In this study, several design …

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%.

Reinforcement In The Information Revolution, Phillip M. Baker

SPU Works

This chapter will outline what it means to be a behaving human and how AI makes sense of these concepts. It will then explore possible near-future implications of our remarkable progress in understanding how human behavior works with the assistance of AI from a neurobiological basis. A focus on understanding the reinforcement mechanisms of the brain will reveal the consequences of ceding control of so much of our brain-environment interactions to AI. It will conclude by offering a potential Christian response to this digital reality from a uniquely Anabaptist perspective.

Mathematical Model Of Subthalamic Nucleus Neuron - Characteristic Activity Patterns And Bifurcation Analysis, Choongseok Park, Sungwoo Ahn, Leonid Rubchinsky

Biology and Medicine Through Mathematics Conference

No abstract provided.

2d Spatio-Temporal Patterns In Coupled Phase Oscillators: Spiral Waves And Chimeras, Yujie Ding, Bard Ermentrout

Biology and Medicine Through Mathematics Conference

No abstract provided.

Scale-Free Properties Influence Breathing Rhythmogenesis., Cameron Grover

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.

Computational Model Of Mutant Arpp Protein Aggregation And Diffusion And Its Impact On Calcium Dynamics And Stress Responses Using Neuron., Gaby Clarke

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.

Noise As A Strategy, Nour Riman, Bard Ermentrout

Biology and Medicine Through Mathematics Conference

No abstract provided.

Empirical And Computational Approaches To Explore The Underlying Neuromodulatory Mechanisms Of Social Status Regulation On Zebrafish Motor Circuits, Sungwoo Ahn, Choongseok Park, Fadi Issa

Biology and Medicine Through Mathematics Conference

No abstract provided.

Probability Distributions Of Active Sensing, Kathleen Hoffman

Biology and Medicine Through Mathematics Conference

No abstract provided.

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 …

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.

Neurodevelopment Correlates With Gut Microbiota In A Cross-Sectional Analysis Of Children At 3 Years Of Age In Rural China, Sarah E. Rothenberg, Qiurong Chen, Yanfen Nong, Hua Nong, Eva P. Trinh, Fred J. Biasini, Jihong Liu, Xiaoyun Zeng, Yunfeng Zou, Fengxiu Ouyang, Susan A. Korrick

Faculty Publications

We investigated cross-sectional associations between children’s neurodevelopment and their gut microbiota composition. Study children (36 months of age) lived in rural China (n = 46). Neurodevelopment was assessed using the Bayley Scales of Infant Development, 2nd Edition, yielding the Mental Developmental Index (MDI) and Psychomotor Developmental Index (PDI). Children's gut microbiota was assessed using 16S rRNA gene profiling. Microbial diversity was characterized using alpha diversity patterns. Additionally, 3 coabundance factors were determined for the 25 most abundant taxa. Multivariable linear regression models were constructed to examine the relationships between Bayley scores (MDI and PDI) and children's gut microbiota. In adjusted …