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Articles 1 - 30 of 36
Full-Text Articles in Computational Neuroscience
A Causal Inference Approach For Spike Train Interactions, Zach Saccomano
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 …
Destined Failure, Chengjun Pan
Destined Failure, Chengjun Pan
Masters Theses
I attempt to examine the complex structure of human communication, explaining why it is bound to fail. By reproducing experienceable phenomena, I demonstrate how they can expose communication structure and reveal the limitations of our perception and symbolization.I divide the process of communication into six stages: input, detection, symbolization, dictionary, interpretation, and output. In this thesis, I examine the flaws and challenges that arise in the first five stages. I argue that reception acts as a filter and that understanding relies on a symbolic system that is full of redundancies. Therefore, every interpretation is destined to be a deviation.
The Genomics Of Autism-Related Genes Il1rapl1 And Il1rapl2: Insights Into Their Cortical Distribution, Cell-Type Specificity, And Developmental Trajectories, Jacob Weaver
MUSC Theses and Dissertations
Neuropsychiatric disorders have a significant impact on modern society. These disorders affect a large percentage of the population: schizophrenia has a world-wide prevalence of 1% and autism spectrum disorders (ASD) affects 1 in 59 school-aged children in the US. There is substantial evidence that most neuropsychiatric disorders have a genetic component. Thus, with the advent of high throughput sequencing much effort has gone into identifying genetic variants associated with these disorders. The emerging picture from these studies is a complex one where hundreds of genes with small effects interact with a varied landscape of common variants to result in disease. …
Age- And Sex-Dependent Alterations In Primary Somatosensory Neuronal Calcium Network Dynamics During Locomotion, Sami L. Case
Age- And Sex-Dependent Alterations In Primary Somatosensory Neuronal Calcium Network Dynamics During Locomotion, Sami L. Case
Theses and Dissertations--Pharmacology and Nutritional Sciences
Over the past 30 years, the calcium (Ca2+) hypothesis of brain aging has provided clear evidence that hippocampal neuronal Ca2+ dysregulation is a key biomarker of aging. Indeed, age-dependent Ca2+-mediated changes in intrinsic excitability, synaptic plasticity, and activity have helped identify some of the mechanisms engaged in memory and cognitive decline. However, much of this work has been done at the single-cell level, mostly in slice preparations, and in restricted structures of the brain. Recently, our lab identified age- and Ca2+-related neuronal network dysregulation in the cortex of the anesthetized animal. Still, investigations in the awake animal are needed to …
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
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%.
Mixed Mode Oscillations In Three-Timescale Coupled Morris-Lecar Neurons, Ngocanh Phan, Yangyang Wang
Mixed Mode Oscillations In Three-Timescale Coupled Morris-Lecar Neurons, Ngocanh Phan, Yangyang Wang
Biology and Medicine Through Mathematics Conference
No abstract provided.
Automated Fitting Of Allosteric Parameters In Receptor Oligomer Models, Spenser Wood
Automated Fitting Of Allosteric Parameters In Receptor Oligomer Models, Spenser Wood
Biology and Medicine Through Mathematics Conference
No abstract provided.
Estimating Glutamate Transporter Surface Density In Mouse Hippocampal Astrocytes, Anca R. Radulescu, Annalisa Scimemi
Estimating Glutamate Transporter Surface Density In Mouse Hippocampal Astrocytes, Anca R. Radulescu, Annalisa Scimemi
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
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.
Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang
Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang
Electrical Engineering Theses and Dissertations
The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …
Scale-Free Behavioral Dynamics Directly Linked With Scale-Free Cortical Dynamics, Sabrina Jones
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 …
Memoir Dataset: Quantifying Image Memorability In Adolescents, Gal Almog, Yalda Mohsenzadeh
Memoir Dataset: Quantifying Image Memorability In Adolescents, Gal Almog, Yalda Mohsenzadeh
Undergraduate Student Research Internships Conference
Every day, humans observe and interact with hundreds of images and scenes; whether it be on a cellphone, on television, or in print. Yet a vast majority of these images are forgotten, some immediately and some after variable lengths of time. Memorability is indeed a property intrinsic to all images that can be extracted, as well as predicted. While memory itself is a process that occurs in the brain of an individual, the concept of memorability is an intrinsic, continuous property of a stimulus that can be both measured and manipulated. We selected images from the MemCat data set that …
When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki
When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki
Dissertations and Theses
Many day-to-day tasks involve processing of complex visual information in a continuous stream. While much of our knowledge on visual processing has been established from reductionist approaches in lab-controlled settings, very little is known about the processing of complex dynamic stimuli experienced in everyday scenarios. Traditional investigations employ event-related paradigms that involve presentation of simple stimuli at select locations in visual space and discrete moments in time. In contrast, visual stimuli in real-life are highly dynamic, spatially-heterogeneous, and semantically rich. Moreover, traditional experiments impose unnatural task constraints (e.g., inhibited saccades), thus, it is unclear whether theories developed under the reductionist …
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. …
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 …
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.
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.
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 …
Timing Is Everything: Temporal Dynamics Of Brain Activity Using The Human Connectome Project, Francesca Lofaro
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 …
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 …
Differentiation Of Neurons And Glia For Use In Cellular Connectomics, Jacob T. Brettin
Differentiation Of Neurons And Glia For Use In Cellular Connectomics, Jacob T. Brettin
Chancellor’s Honors Program Projects
No abstract provided.
Population Codes And Their Correlates In Decision Making, Neda Shahidi
Population Codes And Their Correlates In Decision Making, Neda Shahidi
Dissertations & 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 …
Social Experience Affects Decision Making And Learning: Empirical And Computational Analysis, Sungwoo Ahn
Social Experience Affects Decision Making And Learning: Empirical And Computational Analysis, Sungwoo Ahn
Biology and Medicine Through Mathematics Conference
No abstract provided.
Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell
Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell
Biology and Medicine Through Mathematics Conference
No abstract provided.
Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu
Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu
Biology and Medicine Through Mathematics Conference
No abstract provided.
Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon
Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon
Biology and Medicine Through Mathematics Conference
No abstract provided.
An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard
An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard
Biology and Medicine Through Mathematics Conference
No abstract provided.
Rules And Mechanisms For Efficient Two-Stage Learning In Neural Circuits, Tiberiu Teşileanu, Bence Ölveczky, Vijay Balasubramanian
Rules And Mechanisms For Efficient Two-Stage Learning In Neural Circuits, Tiberiu Teşileanu, Bence Ölveczky, Vijay Balasubramanian
Publications and Research
Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching …