Hodgkin-Huxley neuron model
A self organizing state space model approach for parameter estimation in Hodgkin Huxley type models of single neurons
... state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological ...state-space model with an adaptive sampling algorithm akin to ...
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Saddle Slow Manifolds and Canard Orbits in \(\mathbb{R}^{4}\) and Application to the Full Hodgkin–Huxley Model
... Neuron models with one slow and two fast variables may feature high-frequency spikes separated by quiescent periods. This behavior is called “bursting”. Rinzel [17] introduced a scheme for classifying bursting ...
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Clarification and Complement to “Mean-Field Description and Propagation of Chaos in Networks of Hodgkin–Huxley and FitzHugh–Nagumo Neurons”
... This note restricts the neuron model to the much used variants of the FitzHugh– Nagumo and Hodgkin–Huxley models. Our objective is two-fold: first, we discuss a modeling issue on the diffusion ...
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Dynamics in a Coupled FHN Model with Two Different Delays
... The FHN model with cubic nonlinearity has been obtained from a simplified Hodgkin-Huxley(HH) neuron model [1-3]. Its complete topological and qualitative investigation has been carried ...
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A modified Hodgkin–Huxley model to show the effect of motor cortex stimulation on the trigeminal neuralgia network
... HH model is able to be a proper candidate for modeling the pain modulation ...original model being useful for modeling the behavior of neurons, it is a general model and should be specialized for our ...
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Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON’s programming language hoc
... SENB has been designed as a numerical simulation in the NEURON simulation environment. The SENB soft- ware implementation facilitates changing both the passive and active conduction of the following: maximum spe- ...
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Can the thermodynamic Hodgkin Huxley model of voltage dependent conductance extrapolate for temperature?
... The Hodgkin-Huxley model, in all its forms, is an ...So, neuron modelling studies typically use the H-H model as opposed to Markov descriptions ...H-H model is still relevant and ...
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A comparision of Hodgkin-Huxley and soliton neural theories
... 2 consists mainly of Cl - ions contribute to the voltage signal in the neuron. The flow of these ions through the cell membrane is controlled by their respective voltage-dependent ion channels. The leak current ...
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Data-Driven Predictive Modeling of Neuronal Dynamics using Long Short-Term Memory
... our model with the ground truth synthetic data obtained from an experimentally validated biophysiological model of CA1 pyramidal neuron in the Hodgkin-Huxley ...
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Mean-field description and propagation of chaos in networks of Hodgkin-Huxley and FitzHugh-Nagumo neurons
... response model, via the introduction of suitable kernels propagating the collective ac- tivity of a neural population in ...individual neuron models are rate models, hence already mean-field ...
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Understanding the Action Potential Generation in the Hodgkin-Huxley model
... Abstract— The generation and the propagation of electrical signals in the basic unit of nervous system “neuron” has been a topic of interest to physiologists and researchers for centuries. In this effort of trying ...
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Quantized Three-Ion-Channel Neuron Model for Neural Action Potentials
... The simulation of the voltage response in the circuit reveals similar dynamics to what was ob- served in Ref. [35] when studying the Hodgkin- Huxley model containing a single potassium channel. ...
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Timing control of single neuron spikes with optogenetic stimulation
... Izhikevich model can produce the behaviors of different types of cortical neu- rons by appropriately tuning the parameters {a, b, c, d}, even though the model itself is not biophysically ...of neuron ...
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Finite difference method for numerical solution of a generalized burgers-huxley equation
... The importance for this study is to provide numerical solution for the Burgers-Huxley equations using FDM in several different ways. The main method that is discussed in this thesis is NFDS which has been used in ...
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Modeling Neuromorphic Persistent Firing Networks
... Understanding how human brain represents, stores, and processes information is one of the greatest unsolved mysteries and fundamental challenges of science today. Over the past century, since Lapicque introduced the ...
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Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster
... full model. The reduced model could be run quickly on a laptop (Intel I5) and simulating it for 120 model seconds was not a ...full model, however, could not be simulated over this time frame, ...
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Stimulus dependent refractoriness in the Frankenhaeuser Huxley model
... (FH) model (1964) models the response of a sciatic nerve fibre of the toad Xenopus laevis at a single node of ...The model contains five differential equations and thirty-six parameters, and describes the ...
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Investigation of a Chaotic Spiking Neuron Model
... state neuron (NDS) ...NDS model such as the control mechanism, the reset mechanism, and the way the model may exhibit dynamic behaviours in phase ...NDS model to work and to stabilise to one ...
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Paper 03-2016-1
... real-world model of the complex muscle structure of the ...tongue model setup is identical to that described by Mijailovich S ...The model consists of 873 finite elements, with 3492 integration ...
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BUSINESS PROCESS REENGINEERING TO IMPROVE PROCESS ALIGNMENT & INFORMATION SYSTEM PLATFORM AT STAINLESS EQUIPMENT COMPANY
... network model have been applied to predict financial time series ...hybrid model by combining ARIMA and Neural Network and producing better ...hybrid model with a fixed Neural Network ...of ...
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