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Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

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Biological Restraint on the Izhikevich Neuron Model Essential for Seizure Modeling.

Beata Strack¹, Kimberle M Jacobs², Krzysztof J Cios³

¹B. Strack is with the Department of Computer Science, Virginia Commonwealth University School of Engineering, Richmond, VA.

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|February 23, 2023

Summary

We modified the Izhikevich neuron model to limit neuronal firing rates. This modification impacts network activity, especially in large-scale simulations and models with frequency-dependent plasticity.

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Area of Science:

Computational Neuroscience
Neural Network Modeling

Background:

The Izhikevich neuron model is widely used for simulating neuronal dynamics.
Unrestricted firing rates can lead to unrealistic network activity, particularly in large-scale simulations or when modeling frequency-dependent plasticity.

Purpose of the Study:

To introduce a simple modification to the Izhikevich neuron model to restrict maximum neuronal firing rates.
To investigate the effects of this firing rate restriction on artificial neural network activity.

Main Methods:

A modification was applied to the standard Izhikevich neuron model to cap the firing rate.
The modified model was incorporated into a small artificial neural network.
Network activity was analyzed under varying levels of input.

Main Results:

The modification successfully restricted the maximum firing rates of individual neurons.
Even in small networks with moderate input, the firing rate restriction influenced overall network dynamics.
The impact was demonstrated even when maximum firing rates were not consistently exceeded.

Conclusions:

A simple modification can effectively limit Izhikevich neuron firing rates.
This modification is beneficial for large-scale simulations and models incorporating frequency-dependent short-term plasticity.
Restricting neuronal firing frequencies has significant effects on network activity, even under moderate excitation levels.