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Articles 1 - 13 of 13
Full-Text Articles in Computational Neuroscience
Extending Power Series Methods For The Hodgkin-Huxley Equations, Including Sensitive Dependence, James S. Sochacki
Extending Power Series Methods For The Hodgkin-Huxley Equations, Including Sensitive Dependence, James S. Sochacki
CODEE Journal
A neural cell or neuron is the basic building block of the brain and transmits information to other neurons. This paper demonstrates the complicated dynamics of the neuron through a numerical study of the Hodgkin-Huxley differential equations that model the ionic mechanisms of the neuron: slight changes in parameter values and inputted electrical impulses can lead to very different (unexpected) results. The methods and ideas developed for the ordinary differential equations are extended to partial differential equations for Hodgkin-Huxley networks of neurons in one, two and three dimensions.
Mathematical Modelling Of Temperature Effects On The Afd Neuron Of Caenorhabditis Elegans, Zachary Mobille, Rosangela Follmann, Epaminondas Rosa
Mathematical Modelling Of Temperature Effects On The Afd Neuron Of Caenorhabditis Elegans, Zachary Mobille, Rosangela Follmann, Epaminondas Rosa
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Axonal Blockage With Microscopic Magnetic Stimulation, Hui Ye
Axonal Blockage With Microscopic Magnetic Stimulation, Hui Ye
Biology: Faculty Publications and Other Works
Numerous neurological dysfunctions are characterized by undesirable nerve activity. By providing reversible nerve blockage, electric stimulation with an implanted electrode holds promise in the treatment of these conditions. However, there are several limitations to its application, including poor bio-compatibility and decreased efficacy during chronic implantation. A magnetic coil of miniature size can mitigate some of these problems, by coating it with biocompatible material for chronic implantation. However, it is unknown if miniature coils could be effective in axonal blockage and, if so, what the underlying mechanisms are. Here we demonstrate that a submillimeter magnetic coil can reversibly block action potentials …
Circuits With Broken Fibration Symmetries Perform Core Logic Computations In Biological Networks, Ian Leifer, Flaviano Morone, Saulo D. S. Reis, José S. Andrade Jr., Mariano Sigman, Hernán A. Makse
Circuits With Broken Fibration Symmetries Perform Core Logic Computations In Biological Networks, Ian Leifer, Flaviano Morone, Saulo D. S. Reis, José S. Andrade Jr., Mariano Sigman, Hernán A. Makse
Publications and Research
We show that logic computational circuits in gene regulatory networks arise from a fibration symmetry breaking in the network structure. From this idea we implement a constructive procedure that reveals a hierarchy of genetic circuits, ubiquitous across species, that are surprising analogues to the emblematic circuits of solid-state electronics: starting from the transistor and progressing to ring oscillators, current-mirror circuits to toggle switches and flip-flops. These canonical variants serve fundamental operations of synchronization and clocks (in their symmetric states) and memory storage (in their broken symmetry states). These conclusions introduce a theoretically principled strategy to search for computational building blocks …
Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran
Exploring Effects Of Background Music In A Serious Game On Attention By Means Of Eeg Signals In Children, Fettah Kiran
LSU Master's Theses
Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that …
Nonlinear Control Of Biological Dynamical Systems, Megan J. Morrison
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
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. …
Serum-Based Biomarkers And Magnetic Resonance Imaging Following Mild Traumatic Brain Injury In Collegiate Athletes Post Return-To-Play, Taylor R. Susa
Serum-Based Biomarkers And Magnetic Resonance Imaging Following Mild Traumatic Brain Injury In Collegiate Athletes Post Return-To-Play, Taylor R. Susa
All NMU Master's Theses
Recently there has been an increase in the use of MRI (Magnetic Resonance Imaging), to measure the effects of traumatic brain injury (TBI). Proteins such as BDNF, S100B, UCH-L1, and Tau have been found to have altered levels in blood serum after TBI. However, there is limited knowledge about the relationship between serum-based and MRI-based biomarkers in concussed athletes post return-to-play. This study aimed to bridge this gap by collecting serum samples from 42 participants across two groups. The first group (n = 21) consisted of recently cleared to return-to-play collegiate athletes after experiencing a sports-related concussion. The second group …
Mechanisms Of Value-Biased Prioritization In Fast Sensorimotor Decision Making, Kivilcim Afacan-Seref
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 …
Effects Of Weak Electric Fields On Long-Term Synaptic Plasticity, Gregory Kronberg
Effects Of Weak Electric Fields On Long-Term Synaptic Plasticity, Gregory Kronberg
Dissertations and Theses
Transcranial direct current stimulation (tDCS) is a technique where a weak direct electrical current is applied to the scalp with the goal of stimulating the brain. There is tremendous interest in the use of tDCS for treating brain disorders and improving brain function. However, the effects of tDCS have been highly variable across studies, leading to a debate over its efficacy. A major challenge is therefore to design tDCS protocols that yield predictable effects, which will require a better understanding of its basic mechanisms of action. One commonly discussed mechanism is that tDCS may alter synaptic plasticity, but the biophysics …
Automated And Standardized Tools For Realistic, Generic Musculoskeletal Model Development, Trevor Rees Moon
Automated And Standardized Tools For Realistic, Generic Musculoskeletal Model Development, Trevor Rees Moon
Graduate Theses, Dissertations, and Problem Reports (ETD)
Human movement is an instinctive yet challenging task that involves complex interactions between the neuromusculoskeletal system and its interaction with the surrounding environment. One key obstacle in the understanding of human locomotion is the availability and validity of experimental data or computational models. Corresponding measurements describing the relationships of the nervous and musculoskeletal systems and their dynamics are highly variable. Likewise, computational models and musculoskeletal models in particular are vitally dependent on these measurements to define model behavior and mechanics. These measurements are often sparse and disparate due to unsystematic data collection containing variable methodologies and reporting conventions. To date, …
Neuromechanical Tuning For Arm Motor Control, Russell Lee Hardesty Jr
Neuromechanical Tuning For Arm Motor Control, Russell Lee Hardesty Jr
Graduate Theses, Dissertations, and Problem Reports (ETD)
Movement is a fundamental behavior that allows us to interact with the external world. Its importance to human health is most evident when it becomes impaired due to disease or injury. Physical and occupational rehabilitation remains the most common treatment for these types of disorders. Although therapeutic interventions may improve motor function, residual deficits are common for many pathologies, such as stroke. The development of novel therapeutics is dependent upon a better understanding of the underlying mechanisms that govern movement. Movement of the human body adheres to the principles of classic Newtonian mechanics. However, due to the inherent complexity of …
What Makes An Image Memorable? Effects Of Encoding On The Mechanism Of Recognition, Asiya Gul
What Makes An Image Memorable? Effects Of Encoding On The Mechanism Of Recognition, Asiya Gul
Theses and Dissertations (Comprehensive)
Memory is undoubtedly one of the most important processes of human cognition. A long line of research suggests that recognition relies on the assessment of two explicit memory phenomena: familiarity and recollection. Researchers who support the Dual Process Signal Detection (DPSD) model of recognition memory link the FN400 component (a negative ERP deflection peaking around 400 ms at frontal electrodes) with familiarity; however, it is currently unclear whether the FN400 reflects familiarity or implicit memory. Three event-related potentials (ERP) studies were conducted to determine whether implicit memory plays a role in setting up encoding strategies, and how these encoding strategies …