Biological restraint on the Izhikevich neuron model essential for seizure modeling

Izhikevich model of a neuron allows for simulation of spiking pattern that mimics known biological subtypes. When a current within a range typical for biological experiments is injected into the cell the firing pattern produced in the simulation is close to that observed biologically. However, once...

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Published in2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Vol. 2013; pp. 395 - 398
Main Authors Strack, Beata, Jacobs, Kimberle M., Cios, Krzysztof J.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.11.2013
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ISSN1948-3546
DOI10.1109/NER.2013.6695955

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Abstract Izhikevich model of a neuron allows for simulation of spiking pattern that mimics known biological subtypes. When a current within a range typical for biological experiments is injected into the cell the firing pattern produced in the simulation is close to that observed biologically. However, once these neurons are embedded into a network, the level of depolarization is controlled only by the synaptic depolarization received by the simulated connections. Under these conditions there is no limit on the maximum firing rate produced by any of the neurons. Here we introduce a modification of the Izhikevich model to restrict the firing rate. We demonstrate how this modification affects the overall network activity using a simple artificial neural network. The proposed restraint on the Izhikevich model is particularly important for larger scale simulations or when the frequency dependent short-term plasticity is used in the network. Although maximum firing rates are most likely exceeded in simulations of seizure-like activity we show that restriction of neuronal firing frequencies impacts even small networks with moderate levels of activity.
AbstractList Izhikevich model of a neuron allows for simulation of spiking pattern that mimics known biological subtypes. When a current within a range typical for biological experiments is injected into the cell the firing pattern produced in the simulation is close to that observed biologically. However, once these neurons are embedded into a network, the level of depolarization is controlled only by the synaptic depolarization received by the simulated connections. Under these conditions there is no limit on the maximum firing rate produced by any of the neurons. Here we introduce a modification of the Izhikevich model to restrict the firing rate. We demonstrate how this modification affects the overall network activity using a simple artificial neural network. The proposed restraint on the Izhikevich model is particularly important for larger scale simulations or when the frequency dependent short-term plasticity is used in the network. Although maximum firing rates are most likely exceeded in simulations of seizure-like activity we show that restriction of neuronal firing frequencies impacts even small networks with moderate levels of activity.
We propose a simple modification of the Izhikevich neuron model to restrict firing rates of neurons. We demonstrate how this modification affects overall network activity using a simple artificial network. Such restraint on the Izhikevich neuron model would be especially important in larger scale simulations or when frequency dependent short-term plasticity is one of the network components. Although maximum firing rates are most likely exceeded in simulations of seizure like activity or other conditions that promote excessive excitation, we show that restriction of neuronal firing frequencies has impact even on small networks with moderate levels of input.
We propose a simple modification of the Izhikevich neuron model to restrict firing rates of neurons. We demonstrate how this modification affects overall network activity using a simple artificial network. Such restraint on the Izhikevich neuron model would be especially important in larger scale simulations or when frequency dependent short-term plasticity is one of the network components. Although maximum firing rates are most likely exceeded in simulations of seizure like activity or other conditions that promote excessive excitation, we show that restriction of neuronal firing frequencies has impact even on small networks with moderate levels of input.We propose a simple modification of the Izhikevich neuron model to restrict firing rates of neurons. We demonstrate how this modification affects overall network activity using a simple artificial network. Such restraint on the Izhikevich neuron model would be especially important in larger scale simulations or when frequency dependent short-term plasticity is one of the network components. Although maximum firing rates are most likely exceeded in simulations of seizure like activity or other conditions that promote excessive excitation, we show that restriction of neuronal firing frequencies has impact even on small networks with moderate levels of input.
Author Jacobs, Kimberle M.
Cios, Krzysztof J.
Strack, Beata
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Snippet Izhikevich model of a neuron allows for simulation of spiking pattern that mimics known biological subtypes. When a current within a range typical for...
We propose a simple modification of the Izhikevich neuron model to restrict firing rates of neurons. We demonstrate how this modification affects overall...
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StartPage 395
SubjectTerms Biological neural networks
Biological system modeling
Brain modeling
Computational modeling
Mathematical model
Neurons
Title Biological restraint on the Izhikevich neuron model essential for seizure modeling
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