Tonic Neuron

Free C++ source code for the firing rate neuron model is available.

Tonic Neuron Description

Figure 1. The properties of the tonic neuron.

The only difference between the tonic neuron and the normal neuron is that you can specify a constant intrinsic current that will be injected into the tonic neuron to make it fire tonically.

The tonic neuron has all of the properties associated with a regular neuron: Cm, Gm, Vth, Fmin, and Gain. For a description of them please see the text that discusses the normal neuron. The properties that are unique for the pacemaker are listed below with a description of each.

I_h
A constant current that will be injected into this neuron.

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Neuron Basics
Basic explanation of how a neuron works including equations.
Neuron Model
Equations and explanation for a firing rate neuron model.
Numerical Integration
Describes how to use Euler numerical integration to calculate the membrane voltage of a neuron model.
Normal Neuron
Describes the properties and use of the firing rate neural model in AnimatLab.
Pacemaker Neuron
Details of pacemaker or bursting firing rate neural model used to build neural networks within AnimatLab.
Random Neuron
Details of random firing rate neural model used to build neural networks within AnimatLab.
Tonic Neuron
Details of tonic firing rate neural model used to build neural networks within AnimatLab. Plateau potentials.
Bistable Neuron
Details of bistable firing rate neural model used to build neural networks within AnimatLab. Neural output can switch between two stable states.
Synapse Types
Details of the excitatory, inhibitory, gated, and modulatory synaptic model types in the firing rate neural model used in AnimatLab to build neural networks.

This project was supported by:

National Science Foundation

exploratory grant (GM065762)