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Articles 151 - 180 of 327
Full-Text Articles in Neuroscience and Neurobiology
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 …
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 …
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 …
Computational Neuroscience, Michelle Greene, Ns/Py 357 Students
Computational Neuroscience, Michelle Greene, Ns/Py 357 Students
Open Educational Resources
In Fall 2019, the Computational Neuroscience class at Bates College collaborated to begin an open textbook. Eight students across three majors collaborated to present the content they were learning to students who were similar to themselves. This project serves both pedagogical and social goals. By writing for fellow students, we leveraged the power of teaching for learning. By bringing together students of diverse academic backgrounds, we leveraged the power of peer instruction. Finally, by writing in the open, students not only brought their best work forward, but are working to contribute to an open knowledge environment that democratizes information. This …
Understanding Object Motion Encoding In The Mammalian Retina., Victor Julian Depiero
Understanding Object Motion Encoding In The Mammalian Retina., Victor Julian Depiero
Electronic Theses and Dissertations
Phototransduction, transmission of visual information down the optic nerve incurs delays on the order of 50 – 100ms. This implies that the neuronal representation of a moving object should lag behind the object’s actual position. However, studies have demonstrated that the visual system compensates for neuronal delays using a predictive mechanism called phase advancing, which shifts the population response toward the leading edge of a moving object’s retinal image. To understand how this compensation is achieved in the retina, I investigated cellular and synaptic mechanisms that drive phase advancing. I used three approaches, each testing phase advancing at a …
Network Structure And Dynamics Of Biological Systems, Deena R. Schmidt
Network Structure And Dynamics Of Biological Systems, Deena R. Schmidt
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Analog Implementation Of The Hodgkin-Huxley Model Neuron, Zachary D. Mobille, George H. Rutherford, Jordan Brandt-Trainer, Rosangela Follmann, Epaminondas Rosa
Analog Implementation Of The Hodgkin-Huxley Model Neuron, Zachary D. Mobille, George H. Rutherford, Jordan Brandt-Trainer, Rosangela Follmann, Epaminondas Rosa
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos
Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos
MODVIS Workshop
No abstract provided.
Functional Organization Of Cortical Maps For Ocular Dominance And Light-Dark Polarity In Primary Visual Cortex, Sohrab Najafian, Jian Zhong Jin, Jose-Manuel Alonso
Functional Organization Of Cortical Maps For Ocular Dominance And Light-Dark Polarity In Primary Visual Cortex, Sohrab Najafian, Jian Zhong Jin, Jose-Manuel Alonso
MODVIS Workshop
No abstract provided.
Computations Of Top-Down Attention By Modulating V1 Dynamics, David Berga, Xavier Otazu
Computations Of Top-Down Attention By Modulating V1 Dynamics, David Berga, Xavier Otazu
MODVIS Workshop
The human visual system processes information defining what is visually conspicuous (saliency) to our perception, guiding eye movements towards certain objects depending on scene context and its feature characteristics. However, attention has been known to be biased by top-down influences (relevance), which define voluntary eye movements driven by goal-directed behavior and memory. We propose a unified model of the visual cortex able to predict, among other effects, top-down visual attention and saccadic eye movements. First, we simulate activations of early mechanisms of the visual system (RGC/LGN), by processing distinct image chromatic opponencies with Gabor-like filters. Second, we use a cortical …
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
MODVIS Workshop
It is now common among visual scientists to make inferences about neural population coding of stimuli from indirect measures such as those provided by neuroimaging and psychophysics. The success of such studies depends strongly on simulation work using standard population encoding models extended with decoders (in psychophysics) and measurement models (in neuroimaging). However, not all studies are accompanied by simulation work, and those that are tend to vary widely in their assumptions about encoding, decoding, and measurement. To solve these issues, we designed a Python package (PEMGUIN) to assist computational modelling by providing simple ways to manage encoders' tuning functions, …
Bifurcation Analysis Of A Photoreceptor Interaction Model For Retinitis Pigmentosa, Anca R. Radulescu
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
Spiking Activity In Networks Of Neurons Impacted By Axonal Swelling, Brian Frost, Stan Mintchev
Biology and Medicine Through Mathematics Conference
No abstract provided.
Virtual Eye: A Spatial-Temporal Bottom-Up Eye Sensitivity Model, Todd Goodall
Virtual Eye: A Spatial-Temporal Bottom-Up Eye Sensitivity Model, Todd Goodall
MODVIS Workshop
Video quality and compression models use the
spatial contrast sensitivity function (CSF), which is solved
based on a linear system approximation. This function measures
the eye’s sensitivity to sinusoid gratings, ignoring the subtle
connectivity and inhomogeniety of cell density across the
visual field. Non-linear aspects of the eye, such as the change
in frequency sensitivity with changing illumination, are not
captured by this simple approximation. We propose Virtual
Eye, a bottom-up approach that models the spatio-temporal
dynamics of the eye across the visual field. Each functional
retinal cell layer in the eye is modeled using non-uniform spatial
cell responses, which …
Predicting Dynamics From Hardwiring In Canonical Low-Dimensional Coupled Networks, Anca R. Radulescu
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
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
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-HT1A-R) mediated signaling has been implicated in depression and anxiety, however most studies that focus on the involvement of the 5-HT1A-R have been conducted in adults. Little is known about how the 5-HT1A …
Strengthening Relationships Between Neural Ideals And Receptive Fields, Angelique Morvant
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 JC. In turn, the polynomials in JC 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
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 …
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
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 …