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Neural Network Tutorials

1. Integrate And Fire Neurons. (14 MB)
Describes the integrate-and-fire neural model and how to use it in AnimatLab.
   
2. Spiking Chemical Synapses. (11 MB)
Spiking chemical synapses can be used to connect the integrate-and-fire neurons of the realistic neural module. It simulates a standard synapse that releases transmitter when the pre-synaptic neuron spikes.
   
3. Non-Spiking Chemical Synapses. (10 MB)
Non-Spiking chemical synapses can be used to connect the integrate-and-fire neurons of the realistic neural module. It simulates a synapse that releases transmitter proportionally to the depolarization of the membrane voltage.
   
4. Electrical Synapses. (10 MB)
electrical synapses can be used to connect the integrate-and-fire neurons of the realistic neural module. It simulates an electrical coupling between two neurons. This can be either a rectifying or non-rectifying connection.
   
5. Voltage Dependent Synapses. (8 MB)
Synapses within the realistic neural module can be made voltage dependent. This describes how to configure synapses to be dependent on voltage.
   
6. Long-Term Potentiation. (15 MB)
Shows how to configure synapses within the realistic neural module to use Hebbian learning to implement long-term potentiation (LTP). LTP is a long-term increase in the effectiveness of a synapse after brief high-frequency stimulation.
   
7. Classical Conditioning. (15 MB)
Shows how to configure synapses within the realistic neural module to use Hebbian learning to form associations between stimuli.
   
8. Network Oscillators. (24 MB)
Demonstrates how to build small networks that dynamically interact to produce oscillations.
   
9. Endogenous Bursters. (29 MB)
Describes how to build neurons that produce oscillatory bursts with no external stimuli.
   
10. Coordination. (15 MB)
Shows how to coordinate the activity of multiple oscillatory neurons.
   
11. Lateral Inhibition. (16 MB)
Describes the principle of lateral inhibition and how it can use contrast enhancement to detect line segments.
   
12. Compartmental Model. (30 MB)
Demonstrates how to use the integrate-and-fire neurons to build simple compartmental models. Also shows the difference in effects of proximal vs. distal inhibition.
   
13. Normal Firing Rate Neuron. (21 MB)
Firing rate neurons are a more abstract representation of neurons. The firing frequency is proportional to the membrane voltage. This tutorial describe the properties of this model.
   
13. Random Firing Rate Neuron. (9 MB)
Describes how to get a randomly bursting firing rate neuron.
   
14. Bistable Firing Rate Neuron. (8 MB)
Describes how to build a neuron that will switch between two stable states when given a brief stimulus.
   
15. Firing Rate Normal Synapse. (8 MB)
Describes the standard excitatory/inhibitory synaptic connection used in the firing rate neural model.
   
16. Firing Rate Gated Synapse. (17 MB)
Describes the gated synaptic connection used in the firing rate neural model. This is an axo-axonic synapse that allows a third neuron to modulate the connection between two other neurons.
   
17. Firing Rate Modulatory Synapse. (15 MB)
Describes the modulatory synaptic connection used in the firing rate neural model. This is an axo-axonic synapse that allows a third neuron to modulate the connection between two other neurons.