| | Models | Description |
| 1. |
Axonal HH-model for temperature stimulation (Fribance et al 2016)
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"... To analyze the temperature effect, our study modified
the classical HH axonal model by incorporating a membrane
capacitance-temperature relationship. The modified model
successfully simulated the generation and propagation of action
potentials induced by a rapid increase in local temperature
when the Curie temperature of membrane capacitance is below
40 °C, while the classical model failed to simulate the
axonal excitation by temperature stimulation. The new model
predicts that a rapid increase in local temperature produces a
rapid increase in membrane capacitance, which causes an inward
membrane current across the membrane capacitor strong
enough to depolarize the membrane and generate an action
potential. ..." |
| 2. |
CellExcite: an efficient simulation environment for excitable cells (Bartocci et al. 2008)
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"We have developed CellExcite, a sophisticated simulation environment for excitable-cell networks. CellExcite allows the user to sketch a tissue of excitable cells, plan the stimuli to be applied during simulation, and customize the diffusion model. CellExcite adopts Hybrid Automata (HA) as the computational model in order to efficiently capture both discrete and continuous excitable-cell behavior." |
| 3. |
Comparison of DA-based Stochastic Algorithms (Pezo et al. 2014)
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" ...
Here we review and test a set of the most recently published DA (Langevin-based Diffusion Approximation) implementations (Goldwyn et al., 2011; Linaro et al., 2011; Dangerfield et al., 2012; Orio and Soudry, 2012; Schmandt and Galán, 2012; Güler, 2013; Huang et al., 2013a), comparing all of them in a set of numerical simulations that asses numerical accuracy and computational efficiency on three different models: the original Hodgkin and Huxley model, a model with faster sodium channels, and a multi-compartmental model inspired in granular cells.
..." |
| 4. |
Effect of trp-like current on APs during exposure to sinusoidal voltage (Chen et al. 2010)
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"...
Previous work showed that magnetic electrical field-induced antinoceptive action is mediated by activation of capsaicin-sensitive sensory afferents. In this study, a modified Hodgkin-Huxley model, in which TRP-like current (I-TRP) was incorporated, was implemented to predict the firing behavior of action potentials (APs), as the model neuron was exposed to sinusoidal changes in externally-applied voltage.
...
Our simulation results suggest that modulation of TRP-like channels functionally expressed in small-diameter peripheral sensory neurons should be an important mechanism through which it can contribute to the firing pattern of APs." |
| 5. |
Enhancing the HH eqs: simulations based on the first publication in Biophys J (Moore 2015)
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"The experiments in the Cole and Moore article in the first issue of the Biophysical Journal provided the first independent experimental confirmation of the Hodgkin-Huxley (HH) equations. A log-log plot of the K current versus time showed that raising the HH variable n to the sixth power provided the best fit to the data. Subsequent simulations using n6 and setting the resting potential at the in vivo value simplifies the HH equations by eliminating the leakage term. ..." |
| 6. |
Lillie Transition: onset of saltatory conduction in myelinating axons (Young et al. 2013)
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Included are the NEURON (.hoc) files needed to generate the data used in our Young, Castelfranco, Hartline (2013) paper. The resulting .dat files are in the same folder as the MATLAB (.m) files that are used to sort the data. |
| 7. |
Mechanisms of magnetic stimulation of central nervous system neurons (Pashut et al. 2011)
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Transcranial magnetic stimulation (TMS) is a widely applied tool for probing cognitive function in humans and is one of the best tools for clinical treatments and interfering with cognitive tasks. Surprisingly, while TMS has been commercially available for decades, the cellular mechanisms underlying magnetic stimulation remain unclear. Here we investigate these mechanisms using compartmental modeling. We generated a numerical scheme allowing simulation of the physiological response to magnetic stimulation of neurons with arbitrary morphologies and active properties. Computational experiments using this scheme suggested that TMS affects neurons in the central nervous system (CNS) primarily by somatic stimulation. |
| 8. |
On stochastic diff. eq. models for ion channel noise in Hodgkin-Huxley neurons (Goldwyn et al. 2010)
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" ... We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effect on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. ..." |
| 9. |
PyRhO: A multiscale optogenetics simulation platform (Evans et al 2016)
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"... we present an integrated suite of open-source, multi-scale
computational tools called PyRhO. The purpose of developing PyRhO is
three-fold: (i) to characterize new (and existing) opsins by
automatically fitting a minimal set of experimental data to three-,
four-, or six-state kinetic models, (ii) to simulate these models at
the channel, neuron and network levels, and (iii) provide functional
insights through model selection and virtual experiments in
silico. The module is written in Python with an additional
IPython/Jupyter notebook based GUI, allowing models to be fit,
simulations to be run and results to be shared through simply
interacting with a webpage. The seamless integration of model fitting
algorithms with simulation environments (including NEURON and Brian2)
for these virtual opsins will enable neuroscientists to gain a
comprehensive understanding of their behavior and rapidly identify the
most suitable variant for application in a particular biological
system. ..." |
| 10. |
Software for teaching the Hodgkin-Huxley model (Hernandez & Zurek 2013) (SENB written in NEURON hoc)
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" ... The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers
ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous
visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB
calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and
potassium equilibrium potentials, and propagation velocity of the action potentials. ..." |
| 11. |
Spike trains in Hodgkin–Huxley model and ISIs of acupuncture manipulations (Wang et al. 2008)
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The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters
and shows a variety of qualitatively different behaviors depending on the
parameter values. Under stimulation of an external periodic voltage, the
ISIs (interspike intervals) of a HH model are investigated in this work,
while the frequency of the voltage is taken as the controlling parameter.
As well-known, the science of acupuncture and moxibustion is an important
component of Traditional Chinese Medicine with a long history. Although there
are a number of different acupuncture manipulations, the method for
distinguishing them is rarely investigated. With the idea of ISI, we study
the electrical signal time series at the spinal dorsal horn produced by
three different acupuncture manipulations in Zusanli point and present an
effective way to distinguish them.
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| 12. |
Squid axon (Hodgkin, Huxley 1952) (LabAXON)
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The classic HH model of squid axon membrane implemented in LabAXON. Hodgkin, A.L., Huxley, A.F. (1952) |
| 13. |
Squid axon (Hodgkin, Huxley 1952) (NEURON)
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The classic HH model of squid axon membrane
implemented in NEURON.
Hodgkin, A.L., Huxley, A.F. (1952) |
| 14. |
Squid axon (Hodgkin, Huxley 1952) (SBML, XPP, other)
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An SBML (and related XPP and other formats) implementation of the classic HH paper is available in the BIOMODELS database. See far below for links. |
| 15. |
Squid axon (Hodgkin, Huxley 1952) (SNNAP)
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The classic HH model of squid axon membrane
implemented in SNNAP.
Hodgkin, A.L., Huxley, A.F. (1952) |
| 16. |
Squid axon (Hodgkin, Huxley 1952) used in (Chen et al 2010) (R language)
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"... Previous work showed that magnetic electrical field-induced antinoceptive action is mediated by activation of capsaicin-sensitive sensory afferents. In this study, a modified Hodgkin-Huxley model, in which TRP-like current (I-TRP) was incorporated, was implemented to predict the firing behavior of action potentials (APs), as the model neuron was exposed to sinusoidal changes in externally-applied voltage. ... Our simulation results suggest that modulation of TRP-like channels functionally expressed in small-diameter peripheral sensory neurons should be an important mechanism through which it can contribute to the firing pattern of APs." |
| 17. |
The cannula artifact (Chandler & Hodgkin 1965)
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Chandler and Hodgkin 1965 describes how using a high impedance electrode can lead to squid axon recordings that appear to overshoot the sodium reversal potential, thus resolving controversial recordings at the time. |
