A Single NeuronΒΆ

Purpose: This demo shows how to construct and manipulate a single neuron.

Comments: This leaky integrate-and-fire (LIF) neuron is a simple, standard model of a spiking single neuron. It resides inside a neural ‘population’, even though there is only one neuron.

Usage: Grab the slider control and move it up and down to see the effects of increasing or decreasing input. This neuron will fire faster with more input (an ‘on’ neuron).

Output: See the screen capture below

../_images/singleneuron.png
Code:
import nef

net=nef.Network('Single Neuron')      # Create the network

net.make_input('input',[-0.45])       # Create a controllable input
                                      #   with a starting value of -.45
                                      
net.make('neuron',neurons=1,dimensions=1,      # Make 1 neuron representing
    max_rate=(100,100),intercept=(-0.5,-0.5),  #  1 dimension, with a maximum
    encoders=[[1]],noise=3)                    #  firing rate of 100, with a
                                               #  tuning curve x-intercept of 
                                               #  -0.5, encoder of 1 (i.e. it
                                               #  responds more to positive
                                               #  values) and a noise of
                                               #  variance 3
    
net.connect('input','neuron')         # Connect the input to the neuron
net.add_to_nengo()

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