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Full-Text Articles in Neuroscience and Neurobiology

An Implementation Of Integrated Information Theory In Resting-State Fmri, Idan E. Nemirovsky Apr 2022

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 …


A Generative-Discriminative Approach To Human Brain Mapping, Deepanshu Wadhwa Aug 2021

A Generative-Discriminative Approach To Human Brain Mapping, Deepanshu Wadhwa

Electronic Thesis and Dissertation Repository

During everyday behaviours, the brain shows complex spatial patterns of activity. These activity maps are very replicable within an individual, but vary significantly across individuals, even though they are evoked by the same behaviour. It is unknown how differences in these spatial patterns relate to differences in behavior or function. More fundamentally, the structural, developmental, and genetic factors that determine the spatial organisation of these brain maps in each individual are unclear. Here we propose a new quantitative approach for uncovering the basic principles by which functional brain maps are organized. We propose to take an generative-discriminative approach to human …


Imaging Of Neurotransmitters And Small Molecules In Brain Tissues Using Laser Desorption/Ionization Mass Spectrometry Assisted With Zinc Oxide Nanoparticles., Chaochao Chen, Steven R Laviolette, Shawn N Whitehead, Justin B Renaud, Ken K-C Yeung Mar 2021

Imaging Of Neurotransmitters And Small Molecules In Brain Tissues Using Laser Desorption/Ionization Mass Spectrometry Assisted With Zinc Oxide Nanoparticles., Chaochao Chen, Steven R Laviolette, Shawn N Whitehead, Justin B Renaud, Ken K-C Yeung

Chemistry Publications

Inorganic nanostructured materials such as silicon, carbon, metals, and metal oxides have been explored as matrices of low-background signals to assist the laser desorption/ionization (LDI) mass spectrometric (MS) analysis of small molecules, but their applications for imaging of small molecules in biological tissues remain limited in the literature. Titanium dioxide is one of the known nanoparticles (NP) that can effectively assist LDI MS imaging of low molecular weight molecules (LMWM). TiO2 NP is commercially available as dispersions, which can be applied using a chemical solution sprayer. However, aggregation of NP can occur in the dispersions and the aggregated NP …


Calculating The Dimensionality Of The Brain, And Other Applications Of An Optimized Generalized Ising Model In Predicting Brain's Spontaneous Functions, Pubuditha M. Abeyasinghe Apr 2019

Calculating The Dimensionality Of The Brain, And Other Applications Of An Optimized Generalized Ising Model In Predicting Brain's Spontaneous Functions, Pubuditha M. Abeyasinghe

Electronic Thesis and Dissertation Repository

Understanding a system as complex as the human brain is a very demanding task. Directly working with structural and functional neuroimaging data has led to most of the understanding we have gained about the human brain. However, performing only the direct statistical comparisons on the empirical function and the structure does not fully explain the observed long-range functional correlations. Therefore, implementations of mathematical models to gain further understanding of the relationship between the structure and function of the brain is critical. Additionally, spontaneous functions of the brain can only be predicted using computer simulated models; which will be pivotal for …


Finding Nonlinear Relationships In Functional Magnetic Resonance Imaging Data With Genetic Programming, James Hughes Jul 2018

Finding Nonlinear Relationships In Functional Magnetic Resonance Imaging Data With Genetic Programming, James Hughes

Electronic Thesis and Dissertation Repository

The human brain is a complex, nonlinear dynamic chaotic system that is poorly understood. When faced with these difficult to understand systems, it is common to observe the system and develop models such that the underlying system might be deciphered. When observing neurological activity within the brain with functional magnetic resonance imaging (fMRI), it is common to develop linear models of functional connectivity; however, these models are incapable of describing the nonlinearities we know to exist within the system.

A genetic programming (GP) system was developed to perform symbolic regression on recorded fMRI data. Symbolic regression makes fewer assumptions than …


Tinnitus And Dysfunctional Interactions Between Distributed Resting State Networks, Sivayini Kandeepan Mar 2018

Tinnitus And Dysfunctional Interactions Between Distributed Resting State Networks, Sivayini Kandeepan

Western Research Forum

It is known that peripheral lesions in the cochlea or the auditory nerve produce dysfunctional input to central auditory structures and induce changes in the auditory system causing tinnitus. Recently, it has been proposed that the unified percept of tinnitus could be considered as an emergent property of multiple overlapping dynamic brain networks, each encoding a specific tinnitus characteristic.

The aim of our study was to investigate the neuronal activation patterns associated with specific clinical tinnitus characteristics using fMRI. We hypothesize that tinnitus clinical characteristics could be associated with specific resting-state activity and connectivity patterns and that this could be …


Advances In Image Acquisition And Filtering For Mri Neuroimaging At 7 Tesla, Andrew T. Curtis Sep 2014

Advances In Image Acquisition And Filtering For Mri Neuroimaging At 7 Tesla, Andrew T. Curtis

Electronic Thesis and Dissertation Repository

Performing magnetic resonance imaging at high magnetic field strength promises many improvements over low fields that are of direct benefit in functional neuroimaging. This includes the possibility of improved signal-to-noise levels, and increased BOLD functional contrast and spatial specificity. However, human MRI at 7T and above suffers from unique engineering challenges that limit the achievable gains. In this thesis, three technological developments are introduced, all of which address separate issues associated with functional magnetic resonance neuroimaging at very high magnetic field strengths.

First, the image homogeneity problem is addressed by investigating methods of RF shimming — modifying the excitation portion …


A Non-Contrast Magnetic Resonance Imaging Technique To Assess Blood-Brain Barrier Permeability, Harini Pandithasekera Jun 2014

A Non-Contrast Magnetic Resonance Imaging Technique To Assess Blood-Brain Barrier Permeability, Harini Pandithasekera

Electronic Thesis and Dissertation Repository

The Blood-brain barrier (BBB) regulates the entry of compounds between the blood and the brain, thus plays an important role in brain homeostasis. Studies indicate in disease states such as Alzheimer’s the BBB integrity is compromised. The motive of this project is to investigate the sensitivity of the diffusion-weighted arterial spin labeling (DW-ASL) technique to detect water exchange. Testing the sensitivity requires a reliable method of opening the barrier at specific locations of the brain. Here, a unique technology named focused ultrasound (FUS) has been used to mimic a compromised BBB environment.

A series of experiments were conducted in a …


Optimizing The Analysis Of Electroencephalographic Data By Dynamic Graphs, Mehrsasadat Golestaneh Apr 2014

Optimizing The Analysis Of Electroencephalographic Data By Dynamic Graphs, Mehrsasadat Golestaneh

Electronic Thesis and Dissertation Repository

The brain’s underlying functional connectivity has been recently studied using tools offered by graph theory and network theory. Although the primary research focus in this area has so far been mostly on static graphs, the complex and dynamic nature of the brain’s underlying mechanism has initiated the usage of dynamic graphs, providing groundwork for time sensi- tive and finer investigations. Studying the topological reconfiguration of these dynamic graphs is done by exploiting a pool of graph metrics, which describe the network’s characteristics at different scales. However, considering the vast amount of data generated by neuroimaging tools, heavy computation load and …