Neurosciences Commons^™

Explorations In Homeoviscous Adaptation And Mass Spectral Analysis Of Membrane Lipids, Michael Douglas Timmons

University of Kentucky Doctoral Dissertations

The focus of this dissertation is centered on the mass spectral analysis of lipids and changes occurring in keeping with the concept of homeoviscous adaptation [1]. Homeoviscous adaptation is the process of modification of membrane lipids in response to environmental stimuli [1]. Dissertation investigations applied this concept to prokaryotic and eukaryotic organisms, and expanded the perception of environmental factors from exogenous organic solvents to intracellular environment.

The field of lipidomics deals with the analysis of phospholipid and fatty acid components of membranes the changes that occur due to environmental stimuli and their biological significance [2-6]. The high sensitivity of mass …

Complementary Responses To Mean And Variance Modulations In The Perfect Integrate-And-Fire Model, Joanna R. Wares, Todd W. Troyer

Department of Math & Statistics Faculty Publications

In the perfect integrate-and-fire model (PIF), the membrane voltage is proportional to the integral of the input current since the time of the previous spike. It has been shown that the firing rate within a noise free ensemble of PIF neurons responds instantaneously to dynamic changes in the input current, whereas in the presence of white noise, model neurons preferentially pass low frequency modulations of the mean current. Here, we prove that when the input variance is perturbed while holding the mean current constant, the PIF responds preferentially to high frequency modulations. Moreover, the linear filters for mean and variance …

Focus On Rna Isolation: Obtaining Rna For Microrna (Mirna) Expression Profiling Analyses Of Neural Tissue, Wang-Xia Wang, Bernard R. Wilfred, Donald A. Baldwin, R. Benjamin Isett, Na Ren, Arnold J. Stromberg, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNAs (miRNAs) are present in all known plant and animal tissues and appear to be somewhat concentrated in the mammalian nervous system. Many different miRNA expression profiling platforms have been described. However, relatively little research has been published to establish the importance of 'upstream' variables in RNA isolation for neural miRNA expression profiling. We tested whether apparent changes in miRNA expression profiles may be associated with tissue processing, RNA isolation techniques, or different cell types in the sample. RNA isolation was performed on a single brain sample using eight different RNA isolation methods, and results were correlated using a conventional …

The Expression Of Microrna Mir-107 Decreases Early In Alzheimer's Disease And May Accelerate Disease Progression Through Regulation Of Β-Site Amyloid Precursor Protein-Cleaving Enzyme 1, Wang-Xia Wang, Bernard W. Rajeev, Arnold J. Stromberg, Na Ren, Guiliang Tang, Qingwei Huang, Isidore Rigoutsos, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNAs (miRNAs) are small regulatory RNAs that participate in posttranscriptional gene regulation in a sequence-specific manner. However, little is understood about the role(s) of miRNAs in Alzheimer's disease (AD). We used miRNA expression microarrays on RNA extracted from human brain tissue from the University of Kentucky Alzheimer's Disease Center Brain Bank with near-optimal clinicopathological correlation. Cases were separated into four groups: elderly nondemented with negligible AD-type pathology, nondemented with incipient AD pathology, mild cognitive impairment (MCI) with moderate AD pathology, and AD. Among the AD-related miRNA expression changes, miR-107 was exceptional because miR-107 levels decreased significantly even in patients with …

Searching For The Majority: Algorithms Of Voluntary Control, Jin Fan, Kevin G. Guise, Xun Liu, Hongbin Wang

Faculty, Staff and Student Publications

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses …

Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett

Electrical & Computer Engineering Faculty Publications

Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).

Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …

Temporal Processing In The Exponential Integrate-And-Fire Model Is Nonlinear, Joanna R. Wares, Todd W. Troyer

Department of Math & Statistics Faculty Publications

The exponential integrate-and-fire (EIF) model was introduced by Fourcaud-Trocme et al. (2003) as an extension of the standard leaky integrate-and-fire model (LIF). Here, the nonlinearity in the EIF model’s temporal response to square-wave inputs is investigated. Comparing the time course of onset and offset responses revealed that offset responses have a steeper initial slope, but a slower approach to equilibrium. A linear systems analysis performed for these square-wave inputs indicates that at frequencies above ~40 Hz, gain was slightly smaller for square-wave inputs, but phase did not change significantly relative to simulations in which the corresponding sinusoids were presented in …

Measuring Shared Information And Coordinated Activity In Neuronal Networks, K L. Klinkner, C R. Shalizi, Marcelo Camperi

Physics and Astronomy

Most nervous systems encode information about stimuli in the respond- ing activity of large neuronal networks. This activity often manifests itself as dynamically coordinated sequences of action potentials. Since multiple electrode recordings are now a standard tool in neuroscience research, it is important to have a measure of such network-wide behav- ioral coordination and information sharing, applicable to multiple neural spike train data. We propose a new statistic, informational coherence , which measures how much better one unit can be predicted by knowing the dynamical state of another. We argue informational coherence is a measure of association and shared information …

A Contrast-Based Neural Control System For Ant Navigation, Joanna R. Wares, Predrag-Peter Ilich, Daniel P. Dougherty

Department of Math & Statistics Faculty Publications

A mathematical model for a neural control system of ant locomotion was developed. Contrast-based detectors using excitation and inhibition were tuned to specific contrast orientations. A control system using multiple orientation contrast detectors was then developed and optimized for a model ant, which could move via a biased random walk. The system allowed sufficient control to guide the ant through various mazes.