See: Description
Class  Description 

AbstractSigmoidalRule 
An abstract superclass for discrete and continuous time sigmoial squashing
function based update rules containing methods and variables common to
both.

AdditiveRule 
AdditiveNeuron See Haykin (2002), section 14.5.

AdExIFRule 
An implementation of adaptive exponential integrate and fire.

BinaryRule 
BinaryNeuron takes one of two values.

ContinuousSigmoidalRule 
Continuous Sigmoidal Rule provides various squashing function
ouputs for a neuron whose activation is numerically integrated continuously
over time.

DecayRule 
DecayNeuron implements various forms of standard decay.

FitzhughNagumo  
HodgkinHuxleyRule 
HodgkinHuxley Neuron.

IACRule 
IACNeuron implements an Interactive Activation and Competition neuron.

IntegrateAndFireRule 
IntegrateAndFireNeuron implements an integrate and fire neuron.

IzhikevichRule 
IzhikevichNeuron.

LinearRule 
LinearNeuron is a standard linear neuron.

MorrisLecarRule  
NakaRushtonRule 
NakaRushtonNeuron is a firingrate based neuron which is intended to
model spike rates of real neurons.

PointNeuronRule 
PointNeuron from O'Reilley and Munakata, Computational Explorations in
Cognitive Neuroscience, chapter 2.

RunningAverageRule 
RunningAverageNeuron keeps a running average of current and past
activity.

SigmoidalRule 
SigmoidalRule provides various implementations of a standard
sigmoidal neuron.

SpikingThresholdRule 
A simple spiking neuron that fires when weighted inputs exceed a threshold.

ThreeValueRule 
ThreeValuedNeuron is a natural extension of a binary neuron, which
takes one of three values depending on the inputs to the neuron in relation
to two thresholds.

TimedAccumulatorRule 
Enum  Description 

PointNeuronRule.OutputFunction 
Output functions.
