Medical Sciences Commons^™

Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman

Undergraduate Research Posters

Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …

Group-Based Four-Dimensional Brain Mapping Of Executive Control, Matthew T. Brennan, Kazuki Sakakura Md, Masaki Sonoda Md, Phd, Aimee Luat Md, Neena Marupudi, Sandeep Sood Md, Eishi Asano Md, Phd

Medical Student Research Symposium

Rationale: Humans utilize executive control processes to carry out non-automatic tasks. These tasks require coordination from higher brain centers to both suppress inappropriate behaviors and initiate correct responses. The goal of this study is to generate a novel, dynamic brain atlas to visualize and understand the network dynamics underlying executive control.

Methods: We studied 547 non-epileptic intracranial electrode sites sampled from seven patients with focal epilepsy. Each patient performed two types of verbal tasks: word-reading and Stroop color-naming. Mixed model analysis compared high-gamma cortical activation prior to response onset between the word-reading and Stroop color-naming tasks. Based on mixed model …

A Neurophysiological Investigation Of Listening Effort In Normal Hearing Adults Using Fnirs And Pupillometry, Jessica Defenderfer

Theses and Dissertations (ETD)

Real-world conversations are often accompanied by some sort of interference that challenges the clarity of the speaker’s message, causing listeners to exert more effort to understand speech. Previous research has demonstrated that when listening to speech becomes difficult, various regions of the brain are recruited beyond those which engage during optimal listening conditions. However, the neural correlates that underly listening effort are not fully understood. Importantly, the pupillary response can be used to index listening effort, such that pupil size increases with increasing cognitive demand. I proposed that pupillometry can be used to characterize the cortical response, such that changes …

Visualization And Manual Segmentation Of The Post-Mortem Human Amygdala Subnuclei Using Ultra High Field Magnetic Resonance Imaging, Sara M. Pac

Electronic Thesis and Dissertation Repository

The human amygdala is composed of 13 functionally and anatomically distinct subnuclei. Because most nuclei are difficult to distinguish at the microanatomical level, they are also challenging to discern macroscopically. In low field strength magnetic resonance imaging (MRI) studies, the amygdala can be identified only in its entirety. Higher resolution scans can be acquired by employing ultra-high field strength MRI acquisition techniques. We present a step-by-step guide for the manual segmentation of the amygdala subnuclei at ultra-high field 9.4T MRI. Post-mortem human brain specimen amygdala prosections fit for the 9.4T MRI bore allowed for the collection of high resolution T2-weighted …

In Vivo Brainstem Imaging In Alzheimer’S Disease: Potential For Biomarker Development, David J. Braun, Linda J. Van Eldik

Neuroscience Faculty Publications

The dearth of effective treatments for Alzheimer’s disease (AD) is one of the largest public health issues worldwide, costing hundreds of billions of dollars per year. From a therapeutic standpoint, research efforts to date have met with strikingly little clinical success. One major issue is that trials begin after substantial pathological change has occurred, and it is increasingly clear that the most effective treatment regimens will need to be administered earlier in the disease process. In order to identify individuals within the long preclinical phase of AD who are likely to progress to dementia, improvements are required in biomarker development. …

A Meta-Analysis: A Functional Neuroanatomical Comparison Of Self-Esteem-Related And Postpartum Depression-Related Processing, Meghana Damaraju

Honors Theses

Background: Postpartum depression (PPD) is a psychiatric mood disorder that effects 1 in 10 women in the United States. There are relatively few behavioral studies looking at the association between PPD and self-esteem. There are even fewer studies looking at neuroimaging comparisons between PPD and self-esteem.. The goal of this study was to look at the neuroanatomical overlap of activated brain regions involved in both self-esteem and PPD processing. We hypothesized that the right amygdala, PCC, and insula would be involved in both processes.

Methods: Maps were created using the MKDA program in MATLAB. These images were extent-based cluster-wise …

Neural Function, Injury, And Stroke Subtype Predict Treatment Gains After Stroke, Erin Burke Quinlan, Lucy Dodakian, Jill See, Alison Mackenzie, Vu Le, Mike Wojnowicz, Babak Shahbaba, Steven C. Cramer

Physical Therapy Faculty Articles and Research

Objective

This study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value.

Methods

Patients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical …

Massively Parallel Nonparametric Regression, With An Application To Developmental Brain Mapping, Philip T. Reiss, Lei Huang, Yin-Hsiu Chen, Lan Huo, Thaddeus Tarpey, Maarten Mennes

Lei Huang

We propose a penalized spline approach to performing large numbers of parallel nonparametric analyses of either of two types: restricted likelihood ratio tests of a parametric regression model versus a general smooth alternative, and nonparametric regression. Compared with naively performing each analysis in turn, our techniques reduce computation time dramatically. Viewing the large collection of scatterplot smooths produced by our methods as functional data, we develop a clustering approach to summarize and visualize these results. Our approach is applicable to ultra-high-dimensional data, particularly data acquired by neuroimaging; we illustrate it with an analysis of developmental trajectories of functional connectivity at …

Rapid Quantitative Pharmacodynamic Imaging By A Novel Method: Theory, Simulation Testing And Proof Of Principle, Kevin J. Black, Jonathan M. Koller, Brad D. Miller

Kevin J. Black, MD

Pharmacological challenge imaging has mapped, but rarely quantified, the sensitivity of a biological system to a given drug. We describe a novel method called rapid quantitative pharmacodynamic imaging. This method combines pharmacokinetic-pharmacodynamic modeling, repeated small doses of a challenge drug over a short time scale, and functional imaging to rapidly provide quantitative estimates of drug sensitivity including EC50 (the concentration of drug that produces half the maximum possible effect). We first test the method with simulated data, assuming a typical sigmoidal dose-response curve and assuming imperfect imaging that includes artifactual baseline signal drift and random error. With these few assumptions, …

Retinal Vascular Biomarkers For Early Detection And Monitoring Of Alzheimer's Disease, Shawn Frost, Yogi Kanagasingam, Hamid Sohrabi, J Vignarajan, P Bourgeat, Olivier Salvado, Victor Villemagne, Christopher Rowe, S Lance Macaulay, Cassandra Szoeke, Kathryn A. Ellis, David Ames, Colin L. Masters, Stephanie Rainey-Smith, Ralph N. Martins

Research outputs 2013

The earliest detectable change in Alzheimer's disease (AD) is the buildup of amyloid plaque in the brain. Early detection of AD, prior to irreversible neurological damage, is important for the efficacy of current interventions as well as for the development of new treatments. Although PiB-PET imaging and CSF amyloid are the gold standards for early AD diagnosis, there are practical limitations for population screening. AD-related pathology occurs primarily in the brain, but some of the hallmarks of the disease have also been shown to occur in other tissues, including the retina, which is more accessible for imaging. Retinal vascular changes …

Orbitofrontal Cortex Provides Cross-Modal Valuation Of Self-Generated Stimuli, William A. Cunningham, Ingrid J. Haas, Ashley S. Waggoner

Department of Political Science: Faculty Publications

Prior research has shown that the orbitofrontal cortex (OFC) plays an important role in the representation of the evaluation of stimuli, regardless of stimulus modality. Based on these findings, researchers have proposed that the OFC serves a common currency function, allowing for the direct comparison of different types of perceptual stimuli (e.g. food, drink, money). The present study was designed to extend this research and investigate whether these same regions of OFC that have been identified in previous research are involved in evaluating imagined stimuli. Specifically, we asked participants to draw on prior attitudinal knowledge to generate internal representations of …