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Thursday, July 30, 2020 | History

4 edition of Nonlinear models of the electrical properties of neuronal membranes found in the catalog.

Nonlinear models of the electrical properties of neuronal membranes

William Neil Wright

Nonlinear models of the electrical properties of neuronal membranes

by William Neil Wright

  • 127 Want to read
  • 26 Currently reading

Published by National Library of Canada = Bibliothèque nationale du Canada in Ottawa .
Written in English


Edition Notes

SeriesCanadian theses = Thèses canadiennes
The Physical Object
FormatMicroform
Pagination2 microfiches : negative.
ID Numbers
Open LibraryOL15085251M
ISBN 100315833645
OCLC/WorldCa30810335

Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these models are computationally expensive, considerably curtailing their utility.   Cerebellar purkinje cells. The question of intrinsic electroresponsive properties in vertebrate CNS neurons was first encountered in the detailed study of cerebellar Purkinje cells (Llinás and Hess, ; Llinás and Sugimori, a,b).These studies demonstrated that Purkinje cells have intricate firing properties and that the dendritic and somatic membranes each have .

An emerging explanation of the molecular mechanism, which results in neurodegeneration, places the cause of neurotoxicity of the amyloid- peptides on their potentially negative interaction with neuronal membranes. It is known that amyloid-β peptides interact with the membrane, modifying the membrane’s structural and dynamic properties.   Brainstorms are the electrical signals that encode information from populations of neurons (referred to as neuronal ensembles) and produce various complex behaviors and functions. The author explains in his book that brainstorms represent the depth and potential of population processing and distributive organization of the by:

The application of stimulus-evoked activity to characterize neuronal systems is a powerful analysis tool that dates to the 19th-century identification of functional areas of the brain [].Electrical stimulation has since become ubiquitous for research applications such as mapping cortical regions associated with behavioral outputs and uncovering cortical processing Cited by: 1. () Dynamics of firing patterns, synchronization and resonances in neuronal electrical activities: experiments and analysis. Acta Mechanica Sinica , () A Phantom Bursting Mechanism for Episodic by:


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Nonlinear models of the electrical properties of neuronal membranes by William Neil Wright Download PDF EPUB FB2

The Contributions of Different Ions to the Resting Membrane Potential Can Be Quantified by the Goldman Equation. The Functional Properties of the Neuron Can Be Represented as an Electrical Equivalent Circuit. The Passive Electrical Properties of the Neuron Affect Electrical Signaling.

Membrane Capacitance Slows the Time Course of Electrical Signals. Perhaps the best way to begin a discussion of the Hodgkin-Huxley (HH) model is to analyze the equivalent electrical circuit employed by Hodgkin and Huxley to represent a patch of membrane ().In this approach, the membrane is considered to be an electrical circuit composed of a capacitive element (C m) in parallel with conductances (g), which are in series with a by: 3.

The study of nonlinearities in physiology has been hindered by the lack of effective ways to obtain nonlinear dynamic models from stimulus-response data in a practical context. A considerable body of knowledge has accumulated over the last thirty years in this area of research.

This book summarizes that progress, and details the most recent methodologies that offer practical. For membranes, by definition, the current is zero when the voltage equals the resting potential, and the current direction depends on whether the applied voltage is higher or lower than the resting value.

Therefore, the equation often used for modeling the conducting properties of membranes instead of the GHK formula is a quasi-linear relationship. Linear analysis provides powerful tools for understanding the behavior of neuronal components and systems, but all real physical components are. Cell membranes act as an insulator (nonconductive material) and the inner and outer space of the cell as conductive plates with free ions that can transport electrical charges (Niebur ).

A Author: Ernst Niebur. You can write a book review and share your experiences. Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them.

In contrast to the two-dimensional neuron models, encountered in Chapter 4, we don’t have a relaxation variable that enables us to describe the return of the membrane potential to the integrate-and-fire models, discussed in this and the following chapters, the downswing of the action potential is replaced by an algorithmic reset of the membrane potential to a new value u.

A structure for the operator for the identification of mathematical models of excitable membranes with a large number of membrane currents is proposed. It is found that the nonlinear electrical properties of biological membranes can be identified using tests with other types of “clamped” parameters, such as the current, ramp voltage, : M.

Mazurov. The structure of lipid bilayer membranes is investigated by analysis of the harmonics generated by electrical ac excitation with dc bias. For the detection of nonlinear effects this method is complementary to current relaxation experiments and may be suitable for gating current measurements at nerve by: 3.

The nonlinear and linear mechanical properties were investigated, and the changes in stress and strain distributions of the mucosa were estimated using FE models. According to the values presented in Figure 6, the curve fitting results show that the nonlinear model is more accurate than the linear model and has perfect adaptability to all Author: Min Zhai, Haode Cheng, Jing Yuan, Xin Wang, Bing Li, Dehua Li.

Harmon performed experiments also with combinations of many neuron models. Furthermore, Harmon investigated propagation of the action pulse by chaining models together. These neuron models can be applied to simulate quite complex neural networks, and even to model brain waves. Fig.

Properties of the Harmon model. (A) strength-duration curve. The brain works primarily via synapses that interpret incoming inhibitory and excitatory impulses and nonlinear dynamics are involved in the feedback system of these complex neuronal systems.

Physiologically, for energy conservation, it would make sense for living systems to utilize a nonlinear system, rather than random or simple linear dynamics.

The effect of transverse polarization on nonlinear neuronal activation thresholds is quantified and discussed in the context of previous studies using linear membrane models. Approach. The response of neuronal membranes to applied electric fields is derived under two time scales and a unified solution of transverse polarization is given for Cited by: 8.

The Hodgkin–Huxley model, or conductance-based model, is a mathematical model that describes how action potentials in neurons are initiated and propagated. It is a set of nonlinear differential equations that approximates the electrical characteristics of excitable cells such as neurons and cardiac is a continuous-time dynamical system, unlike, for example.

Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications.

NONLINEAR MEMBRANE SOLUTIONS FOR SYMMETRICALLY LOADED DEEP MEMBRANES OF REVOLUTION By John N. Rossettos Langley Research Center SUMMARY An explicit closed form solution is given for the equations of a nonlinear theory for deep membranes of the theory, it is assumed that strains are small and rotations are moderately small, that is, of File Size: 1MB.

Spectral properties of neuronal pulse interval modulation. CrossRef; End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study.

The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study Cited by: Nonlinear Multivariate Analysis of Neurophysiological Signals Ernesto Pereda1, Rodrigo Quian Quiroga2, But due to the intrinsic nonlinearity of neuronal activity these nonlinear features might be present in neurophysiological data, which has led the electrical signal in the cerebral cortex.

Many models of increasing complexity have been developed The models I will be implementing are based on statistics Linear Models – Linear Nonlinear Poisson (LNP) Model 1.

LNP using Spike Triggered Average (STA) 2. LNP using Maximum Likelihood Estimates – Generalized Linear Model (GLM) 3. Spike Triggered Covariance (STC) Nonlinear Models 4.

Complex emergent properties in synchronized neuronal oscillations. From System Complexity to Emergent Properties, () A Nonautonomous Phenomenological Model for On and Off Responses of Cells in Sensory by: NONLINEAR SHELL MODELING OF THIN MEMBRANES WITH EMPHASIS ON STRUCTURAL WRINKLING Alexander Tessler*, David W.

Sleight*, and John T. Wang* Analytical and Computational Methods Branch, Structures and Materials Competency NASA Langley Research Center, Hampton, VAU.S.A.

Abstract Thin solar sail membranes of very large File Size: 1MB.In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input.

Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other scientists because most systems are inherently nonlinear in nature. Nonlinear dynamical systems, describing changes in variables .