Computational Neuroscience Commons^™

Using Machine Learning To Identify Neural Mechanisms Underlying The Development Of Cognition In Children And Adolescents With Adhd, Brian Pho

Electronic Thesis and Dissertation Repository

Childhood and adolescence are marked by improvements to cognition and by the emergence of neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). What neural mechanisms are associated with cognitive development in ADHD? In this study, I applied machine learning models to functional connectivity profiles to identify patterns of network connectivity that predict various cognitive abilities in a group of participants ages 6 to 16 with ADHD. The models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children ages 6 to 11, but not adolescents. Furthermore, the models identified connections with the default mode, memory retrieval, and …

Analysis Of The Distributed Representation Of Operant Memory In Aplysia, Renan Murillo Costa

Dissertations & Theses (Open Access)

Operant conditioning, a ubiquitous form of learning in which animals learn from the consequences of behavior, engages a high-dimensional neuronal population space spanning multiple brain regions. A complete characterization of an operant memory remains elusive. Some sites of plasticity participating in the engram underlying an example of operant memory in Aplysia have been previously uncovered. Three studies are described here that sought to draw closer to a thorough characterization of this memory. The first study used a computational model to examine the ways in which sites of plasticity (individually and in combination) contribute to memory expression. Each site of plasticity …

Improving An Ssvep-Based Brain Computer Interface Speller, Mac Kenzie J. Frank

Honors Theses

A brain-computer interface (BCI) is a novel technology that creates direct assistive communication between the brain and a computer. While numerous electroencephalogram (EEG) based BCI-speller applications have been used for communication by adults with physical disabilities; few BCI studies have included children, and none using BCI spellers. A pilot study of a developmentally-appropriate EEG-based speller-storybook interface that relied on steady-state visual evoked potentials (SSVEPs) by two pediatric users with quadriplegic cerebral palsy showed limited speller reliability (E. Floreani, personal communication, September 30, 2021). In the pilot study, the alphabet was parsed between three boxes, each flashing at a different rate …

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 …

Individual Differences In Structure Learning, Philip Newlin

Theses and Dissertations

Humans have a tendency to impute structure spontaneously even in simple learning tasks, however the way they approach structure learning can vary drastically. The present study sought to determine why individuals learn structure differently. One hypothesized explanation for differences in structure learning is individual differences in cognitive control. Cognitive control allows individuals to maintain representations of a task and may interact with reinforcement learning systems. It was expected that individual differences in propensity to apply cognitive control, which shares component processes with hierarchical reinforcement learning, may explain how individuals learn structure differently in a simple structure learning task. Results showed …

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 …

Impact Of Brain State On Visual And Prefrontal Population Coding In Behaving Animals, Russell Milton

Dissertations & Theses (Open Access)

Patterns of neural activity in the brain constantly shift between different processing states. Earlier studies have established that the ongoing, spontaneous activity has major repercussions regarding how the brain processes incoming sensory stimuli. However, the interaction between behavioral activity and brain states throughout the cortical hierarchy of primates has not been understood. In particular, technical considerations have greatly limited the range of physical activities in which primate neuronal activity can be recorded. We have implemented two separate strategies to overcome these limitations. First, we have advanced wireless electrophysiological methodologies that enable recording high-yield neuronal data from animals as they freely …

Ongoing Calculus In The Cerebral Cortex, Luke Long

Physics Undergraduate Honors Theses

Various modes of neuronal computations have long been theorized to be possible based on the structure and geometry of the brain. These computations also seem necessary for many of the integral functions of the brain, like information processing and regulatory processes in the body. However, experimental data directly supporting these claims have been rare.

In this study, data collected in mice from a large number of neurons over a long period of time provided the opportunity to search for some of these computations, specifically change detection and squaring calculations. Using Matlab, the goal of this analysis was to find statistically …

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 …

Modeling And Analyses Of Mechanisms Underlying Network Synaptic Dynamics In Two Neural Circuits, Linda Ma

Undergraduate Honors Theses

In systems neuroscience, circuit models of cortical structures can be used to deconstruct mechanisms responsible for spike patterns that generate a variety of behaviors observed in the brain. In particular, mathematical simulations of these circuits can replicate complex dynamical behaviors that mirror not only macroscopically patterns observed in the brain, but also a significant amount of experimentally characterized minutiae. These models are capable of analyzing neural mechanisms by explicitly deconstructing connectivities between populations of neurons in ways that tend to be empirically inaccessible. This work presents two such models; one in the rat somatosensory barrel cortex, responsible for processing sensory …

Nonhematopoietic Erythropoietin: A Study Of Signaling, Structure, And Behavior, Nicholas John Pekas

Dissertations and Theses

Erythropoietin (EPO) is a cytokine hormone known for initiating red blood cell proliferation by binding to its homodimer receptor (EPOR)2 in the bone marrow. Recent progress in neurobiology has shown that EPO also exerts robust neurotrophic and neuroprotective activity in the CNS. It is widely thought that EPO’s neurotrophic activity is centrally involved in its antidepressant and cognitive enhancing effects. However, EPO’s potent erythropoietic effects prevent it from being used in the clinic to treat psychiatric disorders. A chemically engineered non-erythropoietic derivative of EPO, carbamoylated EPO (CEPO), produces psychoactive effects without activating hematopoiesis. However, CEPO is expensive to produce and …

Energy As A Limiting Factor In Neuronal Seizure Control: A Mathematical Model, Sophia E. Epstein

CMC Senior Theses

The majority of seizures are self-limiting. Within a few minutes, the observed neuronal synchrony and deviant dynamics of a tonic-clonic or generalized seizure often terminate. However, a small epilesia partialis continua can occur for years. The mechanisms that regulate subcortical activity of neuronal firing and seizure control are poorly understood. Published studies, however, through PET scans, ketogenic treatments, and in vivo mouse experiments, observe hypermetabolism followed by metabolic suppression. These observations indicate that energy can play a key role in mediating seizure dynamics. In this research, I seek to explore this hypothesis and propose a mathematical framework to model how …