The Experts below are selected from a list of 816 Experts worldwide ranked by ideXlab platform

John M Myers - One of the best experts on this subject based on the ideXlab platform.

  • modeling the effect of an external electric field on the velocity of spike propagation in a nerve fiber
    Physical Review E, 1999
    Co-Authors: John M Myers
    Abstract:

    The effect of an externally generated electric field on the propagation of action potentials is modeled, assuming the Hodgkin-Huxley Equation for the voltage-dependent conductance of the membrane of a nerve fiber. With some simplifying assumptions, this conductance together with Maxwell's Equations leads to the Hodgkin-Huxley differential Equations for propagation, modified by a term proportional to the gradient of the externally generated electric field component along the nerve fiber. Computer solution of these Equations shows the influence of an electric field gradient on propagation velocity. When the electric field oscillates, voltage spikes starting later along a given axon advance or lag relative to earlier spikes, so the time between spikes at the receiving end differs from the time between spike originations. The amount that a low-frequency electric field modulates pulse timing at the end of a fiber relative to that at the beginning is estimated under several conditions.

浅井 竜哉 - One of the best experts on this subject based on the ideXlab platform.

  • A Numerical Simulation of Hodgkin-Huxley Model : An Approach to an Understanding of a Brain
    2004
    Co-Authors: 平田 隆幸, 黒岩 丈介, 浅井 竜哉
    Abstract:

    A numerical simulation of Hodgkin-Huxley model was carried out by using a Runge-Kutta method. In the numerical simulation, the functions of Numerical Recipes in C were used for solving the Hodgkin-Huxley Equation. The accuracy of numerical solutions was discussed for both simple Runge-Kutta method and adaptive stepsize control Runge-Kutta method. The difference between simulation performed by using float type variables and one by using double type variables was also discussed. A large neural network of Hodgkin-Huxley neurons was carried out. A synchronization in the neural network was observed by changing the weight of synaptic transmission

Mohit Nigam - One of the best experts on this subject based on the ideXlab platform.

  • three step taylor galerkin method for singularly perturbed generalized Hodgkin Huxley Equation
    International Journal of Modeling Simulation and Scientific Computing, 2010
    Co-Authors: Vivek Sangwan, B Rathish V Kumar, S V S S N V G K Murthy, Mohit Nigam
    Abstract:

    A numerical study is carried out for the singularly perturbed generalized Hodgkin–Huxley Equation. The Equation is nonlinear which mimics the ionic processes at a real nerve membrane. A small parameter called singular perturbation parameter is introduced in the highest order derivative term. Keeping other parameters fixed, as this singular perturbation parameter approaches to zero, a boundary layer occurs in the solution. Three-step Taylor Galerkin finite element method is employed on a piecewise uniform Shishkin mesh to solve the Equation. To procure more accurate temporal differencing, the method employs forward-time Taylor series expansion including time derivatives of third order which are evaluated from the governing singularly perturbed generalized Hodgkin–Huxley Equation. This yields a generalized time-discretized Equation which is successively discretized in space by means of the standard Bubnov–Galerkin finite element method. The method is third-order accurate in time. The code based on the purposed scheme has been validated against the cases for which the exact solution is available. It is also observed that for the Singularly Perturbed Generalized Hodgkin–Huxley Equation, the boundary layer in the solution manifests not only by varying the singular perturbation parameter but also by varying the other parameters appearing in the model.

Yoshifumi Nishio - One of the best experts on this subject based on the ideXlab platform.

  • CHAOSOM and its Application to Traveling Salesman Problem
    2015
    Co-Authors: Haruna Matsushita, Yoshifumi Nishio
    Abstract:

    Abstract In this study, we try to implant chaotic features into the learning algorithm of self-organizing map. We call this concept as Chaotic SOM (CHAOSOM). As a first step to realize CHAOSOM, we consider the case that learning rate and neighboring coefficient of SOM are refreshed by chaotic pulses generated by the Hodgkin-Huxley Equation. We apply the CHAOSOM to solve a traveling salesman problem and confirm that the chaotic feature improves the performance. Key words self-organizing map (SOM), chaos, Hodgkin-Huxley Equation, traveling salesman problem 1

  • CHAOSOM: Collaboration between Chaos and Self-Organizing Map
    2015
    Co-Authors: Haruna Matsushita, Yoshifumi Nishio
    Abstract:

    In this study, we try to implant chaotic features into the learn-ing algorithm of self-organizing map. We call this concept as Chaotic SOM (CHAOSOM). As a first step to realize CHAO-SOM, we consider the case that learning rate and neighboring coefficient of SOM are refreshed by chaotic pulses generated by the Hodgkin-Huxley Equation. We apply the CHAOSOM to solve a traveling salesman problem and confirm that the chaotic feature improves the performance

Vahid Salari - One of the best experts on this subject based on the ideXlab platform.

  • selectivity filter gate versus voltage sensitive gate a study of quantum probabilities in the Hodgkin Huxley Equation
    arXiv: Other Quantitative Biology, 2014
    Co-Authors: Narges Moradi, Felix Scholkmann, Vahid Salari
    Abstract:

    The Hodgkin-Huxley (HH) model is a powerful model to explain different aspects of spike generation in excitable cells. However, the HH model was proposed in 1952 when the real structure of the ion channel was unknown. It is now common knowledge that in many ion-channel proteins the flow of ions through the pore is governed by a gate, comprising a so-called selectivity filter inside the ion channel, which can be controlled by electrical interactions. The selectivity filter is believed to be responsible for the selection and fast conduction of particular ions across the membrane of an excitable cell. Other (generally larger) parts of the molecule such as the pore-domain gate control the access of ions to the channel protein. In fact, two types of gates are considered here for ion channels: the external gate, which is the voltage sensitive gate, and the internal gate which is the selectivity filter gate (SFG). Some quantum effects are to expected in the SFG due to its small dimensions, which may play an important role in the operation of an ion channel. Here, we examine parameters in a generalized model of HH to see whether any parameter affects the spike generation. Our results indicate that the previously suggested semi-quantum-classical Equation proposed by Bernroider and Summhammer (BS) agrees strongly with the HH Equation under different conditions and may even provide a better explanation in some cases. We conclude that the BS model can refine the classical HH model substantially.