Physical Sciences and Mathematics Commons^™

Reliability And Validity Of Neurobehavioral Function On The Psychology Experimental Building Language Test Battery In Young Adults, Brian J. Piper, Shane Mueller, Alexander R. Geerken, Kyle L. Dixon, Gregory Kroliczak, Reid H. Olsen, Jeremy K. Miller

Michigan Tech Publications

Background. The Psychology Experiment Building Language (PEBL) software consists of over one-hundred computerized tests based on classic and novel cognitive neuropsychology and behavioral neurology measures. Although the PEBL tests are becoming more widely utilized, there is currently very limited information about the psychometric properties of these measures.

Methods. Study I examined inter-relationships among nine PEBL tests including indices of motor-function (Pursuit Rotor and Dexterity), attention (Test of Attentional Vigilance and Time-Wall), working memory (Digit Span Forward), and executive-function (PEBL Trail Making Test, Berg/Wisconsin Card Sorting Test, Iowa Gambling Test, and Mental Rotation) in a normative sample (N = 189, …

Analysis Of Neuronal Sequences Using Pairwise Biases, Zachary Roth

Department of Mathematics: Dissertations, Theses, and Student Research

Sequences of neuronal activation have long been implicated in a variety of brain functions. In particular, these sequences have been tied to memory formation and spatial navigation in the hippocampus, a region of mammalian brains. Traditionally, neuronal sequences have been interpreted as noisy manifestations of neuronal templates (i.e., orderings), ignoring much richer structure contained in the sequences. This paper introduces a new tool for understanding neuronal sequences: the bias matrix. The bias matrix captures the probabilistic tendency of each neuron to fire before or after each other neuron. Despite considering only pairs of neurons, the bias matrix captures the best …

Chemical Biology-Based Probes For The Labeling Of Targets On Live Cells, Amanda M. Hussey

Doctoral Dissertations

Proper detection is the key to studying any processes on the cellular scale. Nowhere is this more evident than in the tight space which confines the synaptic cleft. Being able to ascertain the location of receptors on live neurons is fundamental to our understanding of not only how these receptors interact and move inside the cell but also how neurons function. Most detection methods rely on significantly altering the receptor; both tagging with a fluorescent protein or targeting the receptor by a fluorescent reporter in the form of a small molecule causes significant difficulties. These localization techniques often result in …

Partial Covariance Based Functional Connectivity Computation Using Ledoit-Wolf Covariance Regularization, Matthew R. Brier, Anish Mitra, John E. Mccarthy, Beau M. Ances, Abraham Z. Snyder

Mathematics Faculty Publications

Highlights •We use the well characterized matrix regularization technique described by Ledoit and Wolf to calculate high dimensional partial correlations in fMRI data. •Using this approach we demonstrate that partial correlations reveal RSN structure suggesting that RSNs are defined by widely and uniquely shared variance. •Partial correlation functional connectivity is sensitive to changes in brain state indicating that they contain functional information. Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a …

Flexible Gating Of Contextual Influences In Natural Vision, Odelia Schwartz

Mathematics Colloquium Series

An appealing hypothesis suggests that neurons represent inputs in a coordinate system that is matched to the statistical structure of images in the natural environment. I discuss theoretical work on unsupervised learning of statistical regularities in natural images. In the model, Bayesian inference amounts to a generalized form of divisive normalization, a canonical computation that has been implicated in many neural areas. In our framework, divisive normalization is flexible: it is recruited only when the image is inferred to contain dependencies, and muted otherwise. I particularly focus on recent work in which we have applied this approach to understanding spatial …

Age-Related Sexual Dimorphism In Temporal Discrimination And In Adult-Onset Dystonia Suggests Gabaergic Mechanisms, John Butler, Ines M. Beiser, Laura Williams, Eavan Mcgovern, Fiona Molloy, Timothy Lynch, Dan G. Healy, Helena Moore, Richard Walsh, Richard B. Reilly, Sean O'Riordan, Cathal Walsh, Michael Hutchinson

Articles

Background: Adult-onset isolated focal dystonia (AOIFD) presenting in early adult life is more frequent in men, whereas in middle age it is female predominant. Temporal discrimination, an endophenotype of adult-onset idiopathic isolated focal dystonia, shows evidence of sexual dimorphism in healthy participants. Objectives: We assessed the distinctive features of age-related sexual dimorphism of (i) sex ratios in dystonia phenotypes and (ii) sexual dimorphism in temporal discrimination in unaffected relatives of cervical dystonia patients. Methods: We performed (i) a meta-regression analysis of the proportion of men in published cohorts of phenotypes of adult-onset dystonia in relation to their mean age of …

Subject Assessment Of In-Vehicle Auditory Warnings For Rail Grade Crossings, Steven Landry, Jayde Croschere, Myounghoon Jeon

Michigan Tech Publications

Human factors research has played an important role in reducing the incidents of vehicle-train collisions at rail grade crossings over the past 30 years. With the growing popularity of in-vehicle infotainment systems and GPS devices, new opportunities arise to cost-efficiently and effectively alert drivers of railroad crossings and to promote safer driving habits. To best utilize this in-vehicle technology, 32 auditory warnings (16 verbal, 7 train-related auditory icons, and 9 generic earcons) were generated and presented to 31 participants after a brief low-fidelity driving simulation. Participants rated each sound on eight dimensions deemed important in previous auditory warning literature. Preliminary …

Wavelet-Domain Regression And Predictive Inference In Psychiatric Neuroimaging, Philip T. Reiss, Lan Huo, Yihong Zhao, Clare Kelly, R. Todd Ogden

Philip T. Reiss

An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants of principal component regression and of partial least squares, and the elastic net. Second, we consider assessing the contribution of image predictors over and above available scalar predictors, in particular via permutation tests and an extension of the idea of confounding to the case of functional or image predictors. …

Binocular 3d Motion Perception As Bayesian Inference, Martin Lages, Suzanne Heron

MODVIS Workshop

The human visual system encodes monocular motion and binocular disparity input before it is integrated into a single 3D percept. Here we propose a geometric-statistical model of human 3D motion perception that solves the aperture problem in 3D by assuming that (i) velocity constraints arise from inverse projection of local 2D velocity constraints in a binocular viewing geometry, (ii) noise from monocular motion and binocular disparity processing is independent, and (iii) slower motions are more likely to occur than faster ones. In two experiments we found that instantiation of this Bayesian model can explain perceived 3D line motion direction under …

Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker

MODVIS Workshop

Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.

To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …

Modeling Visual Features To Recognize Biological Motion: A Developmental Approach, Giulio Sandini, Nicoletta Noceti, Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Alessandro Verri, Francesca Odone

MODVIS Workshop

In this work we deal with the problem of designing and developing computational vision models – comparable to the early stages of the human development – using coarse low-level information.

More specifically, we consider a binary classification setting to characterize biological movements with respect to non-biological dynamic events. To this purpose, our model builds on top of the optical flow estimation, and abstract the representation to simulate the limited amount of visual information available at birth. We take inspiration from known biological motion regularities explained by the Two-Thirds Power Law, and design a motion representation that includes different low-level features, …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Complementary Effect Of Electrical And Inhibitory Coupling In Bursting Synchronization, Kevin Daley

Georgia State Undergraduate Research Conference

gsurc 2015

Quantitative And Qualitative Stability Analysis Of Polyrhythmic Circuits, Drake Knapper

Georgia State Undergraduate Research Conference

No abstract provided.

Essential Oils From Apple Mint (Mentha Suaveolens) And Passionflower Fruit (Passiflora Incarnata): Studies On Cognition, Coordination, And Chemical Components., Evelyn F. Patrick *, Jessie Bowers *, Shannon Read *, Brett R. Lackey, Christine Murphy, Sandra L. Gray

Journal of the South Carolina Academy of Science

Plant essential oils (EO) are used as perfumes, lotions and air fresheners because of their pleasant aromas, but EO also have the ability to elicit changes in mood and behavior. These activities are influenced by the mode of administration and by multiple signaling pathways. The EO aromas from organically grown apple mint (Mentha suaveolens) and passionflower fruit (Passiflora incarnata) were assessed for their effects on cognition and coordination. Participants completed two tasks designed to test working memory and bimanual task efficiency in rooms infused with apple mint, passionflower fruit or control EO. Bimanual coordination was assessed using the Intercept2 program …

Exploring The Unknown: Electrophysiological And Behavioural Measures Of Visuospatial Learning, Brendan Quinlivan, John Butler, Abdur R. Ridwan, Ines Beiser, Laura Williams, Eavan Mcgovern, Sean O'Riordan, Michael Hutchinson, Richard B. Reilly

Articles

Visuospatial memory describes our ability to temporarily store and manipulate visual and spatial information, and is employed for a wide variety of complex cognitive tasks. Here, a visuospatial learning task requiring fine motor control is employed to investigate visuospatial learning in a group of typically developing adults. Electrophysiological and behavioural data are collected during a target location task under two experimental conditions: Target Learning and Target Cued. Movement times (MTs) are employed as a behavioural metric of performance, while dynamic P3b amplitudes and power in the alpha band (approximately 10 Hz) are explored as electrophysiological metrics during visuospatial learning. Results …

Modeling Neurovascular Coupling From Clustered Parameter Sets For Multimodal Eeg-Nirs, M. Tanveer Talukdar, H. Robert Frost, Solomon G. G. Diamond

Dartmouth Scholarship

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation. The approach is evaluated first with simulated EEG-NIRS data and then by applying the method to experimental EEG-NIRS data measured from …

Clique Topology Reveals Intrinsic Geometric Structure In Neural Correlations, Chad Giusti, Eva Pastalkova, Carina Curto, Vladimir Itskov

Department of Mathematics: Faculty Publications

Detecting meaningful structure in neural activity and connectivity data is challenging in the presence of hidden nonlinearities, where traditional eigenvalue-based methods may be misleading. We introduce a novel approach to matrix analysis, called clique topology, that extracts features of the data invariant under nonlinear monotone transformations. These features can be used to detect both random and geometric structure, and depend only on the relative ordering of matrix entries. We then analyzed the activity of pyramidal neurons in rat hippocampus, recorded while the animal was exploring a 2D environment, and confirmed that our method is able to detect geometric organization using …

Characterization Of Calbindin Positive Interneurons Within The Ventral Horn Of The Mouse Spinal Cord, Taylor L. Floyd, David R. Ladle

Symposium of Student Research, Scholarship, and Creative Activities Materials

Sensory-motor circuits in the spinal cord integrate sensory feedback from muscles and modulate locomotor behavior. Although we know how the sensory-motor system generally works, the main issue lies in identifying all neurons involved and understanding their interrelationships. Many interneurons contribute to sensory-motor circuits and have been well studied. For example, Renshaw cells (RC) are inhibitory interneurons that prevent motor neurons from over-activity. A distinguishing feature of RCs is that they are the only interneurons within the ventral-most region of the spinal cord expressing the calcium binding protein calbindin (CB). Recent studies have found other subpopulations of ventral horn interneurons outside …

Firing Rate Dynamics In Recurrent Spiking Neural Networks With Intrinsic And Network Heterogeneity, Cheng Ly

Statistical Sciences and Operations Research Publications

Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, …

Functional Organization And Restoration Of The Brain Motor-Execution Network After Stroke And Rehabilitation, Sahil Bajaj, Andrew Butler, Daniel Drake, Mukesh Dhamala

Physics and Astronomy Faculty Publications

Multiple cortical areas of the human brain motor system interact coherently in the low frequency range (<0.1 Hz), even in the absence of explicit tasks. Following stroke, cortical interactions are functionally disturbed. How these interactions are affected and how the functional organization is regained from rehabilitative treatments as people begin to recover motor behaviors has not been systematically studied. We recorded the intrinsic functional magnetic resonance imaging (fMRI) signals from 30 participants: 17 young healthy controls and 13 aged stroke survivors. Stroke participants underwent mental practice (MP) or both mental practice and physical therapy (MP+PT) within 14–51 days following stroke. We investigated the network activity of five core areas in the motor-execution network, consisting of the left primary motor area (LM1), the right primary motor area (RM1), the left pre-motor cortex (LPMC), the right pre-motor cortex (RPMC) and the supplementary motor area (SMA). We discovered that (i) the network activity dominated in the frequency range 0.06–0.08 Hz for all the regions, and for both able-bodied and stroke participants (ii) the causal information flow between the regions: LM1 and SMA, RPMC and SMA, RPMC and LM1, SMA and RM1, SMA and LPMC, was reduced significantly for stroke survivors (iii) the flow did not increase significantly after MP alone and (iv) the flow among the regions during MP+PT increased significantly. We also found that sensation and motor scores were significantly higher and correlated with directed functional connectivity measures when the stroke-survivors underwent MP+PT but not MP alone. The findings provide evidence that a combination of mental practice and physical therapy can be an effective means of treatment for stroke survivors to recover or regain the strength of motor behaviors, and that the spectra of causal information flow can be used as a reliable biomarker for evaluating rehabilitation in stroke survivors.

Lexical Mechanics: Partitions, Mixtures, And Context, Jake Ryland Williams

Graduate College Dissertations and Theses

Highly structured for efficient communication, natural languages are complex systems. Unlike in their computational cousins, functions and meanings in natural languages are relative, frequently prescribed to symbols through unexpected social processes. Despite grammar and definition, the presence of metaphor can leave unwitting language users "in the dark," so to speak. This is not problematic, but rather an important operational feature of languages, since the lifting of meaning onto higher-order structures allows individuals to compress descriptions of regularly-conveyed information. This compressed terminology, often only appropriate when taken locally (in context), is beneficial in an enormous world of novel experience. However, what …

The Effects Of Molecular Chaperones On Tau Fibril Assembly, Ahmed Omran

Electronic Theses and Dissertations

The accumulation of microtubule-associated protein tau into fibrillar aggregates is the hallmark of Alzheimer’s disease and other neurodegenerative disorders, collectively referred to as tauopathies. Fibrils can propagate from one cell to the next and spread throughout the brain. However, a study shows that only small aggregates can be taken up by cultured neuronal cells. The mechanisms that lead to the breakage of fibrils into smaller fragments remain unknown. In yeast, the AAA+ chaperone HSP104 processes the reactivation of protein aggregates and is responsible for fragmentation of fibrils. This study focused on investigating the effects of molecular chaperones on tau fibrils …

Learning Emotions: A Software Engine For Simulating Realistic Emotion In Artificial Agents, Douglas Code

Senior Independent Study Theses

This paper outlines a software framework for the simulation of dynamic emotions in simulated agents. This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events. The emotion management engine provided by the framework uses a modified Fuzzy Logic Adaptive Model of Emotions (FLAME) model, which lets it manage both appraisal of events in relation to an individual’s emotional state, and learning mechanisms through which an individual’s emotional responses to a particular event or object can change over time. In addition to the FLAME model, the engine draws on the design …

A Principle Of Economy Predicts The Functional Architecture Of Grid Cells, Xue-Xin Wei, Jason Prentice, Vijay Balasubramanian

Publications and Research

Grid cells in the brain respond when an animal occupies a periodic lattice of ‘grid fields’ during navigation. Grids are organized in modules with different periodicity. We propose that the grid system implements a hierarchical code for space that economizes the number of neurons required to encode location with a given resolution across a range equal to the largest period. This theory predicts that (i) grid fields should lie on a triangular lattice, (ii) grid scales should follow a geometric progression, (iii) the ratio between adjacent grid scales should be √e for idealized neurons, and lie between 1.4 and 1.7 …

Quantile Rank Maps: A New Tool For Understanding Individual Brain Development, Huaihou Chen, Clare Kelly, F. Xavier Castellanos, Ye He, Xi-Nian Zuo, Philip T. Reiss

Philip T. Reiss

We propose a novel method for neurodevelopmental brain mapping that displays how an individual’s values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be …