| 1. |
Integrate And Fire Neurons. (14 MB) |
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Describes the integrate-and-fire neural model and how to use it in AnimatLab.
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| 2. |
Spiking Chemical Synapses. (11 MB) |
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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.
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| 3. |
Non-Spiking Chemical Synapses. (10 MB) |
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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.
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| 4. |
Electrical Synapses. (10 MB) |
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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.
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| 5. |
Voltage Dependent Synapses. (8 MB) |
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Synapses within the realistic neural module can be made voltage dependent.
This describes how to configure synapses to be dependent on voltage.
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| 6. |
Long-Term Potentiation. (15 MB) |
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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.
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| 7. |
Classical Conditioning. (15 MB) |
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Shows how to configure synapses within the realistic neural module to use Hebbian learning
to form associations between stimuli.
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| 8. |
Network Oscillators. (24 MB) |
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Demonstrates how to build small networks that dynamically interact to produce oscillations.
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| 9. |
Endogenous Bursters. (29 MB) |
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Describes how to build neurons that produce oscillatory bursts with no external stimuli.
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| 10. |
Coordination. (15 MB) |
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Shows how to coordinate the activity of multiple oscillatory neurons.
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| 11. |
Lateral Inhibition. (16 MB) |
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Describes the principle of lateral inhibition and how it can use contrast enhancement to detect line segments.
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| 12. |
Compartmental Model. (30 MB) |
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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.
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| 13. |
Normal Firing Rate Neuron. (21 MB) |
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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.
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| 13. |
Random Firing Rate Neuron. (9 MB) |
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Describes how to get a randomly bursting firing rate neuron.
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| 14. |
Bistable Firing Rate Neuron. (8 MB) |
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Describes how to build a neuron that will switch between two stable states when given a brief stimulus.
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| 15. |
Firing Rate Normal Synapse. (8 MB) |
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Describes the standard excitatory/inhibitory synaptic connection used in the firing rate neural model.
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| 16. |
Firing Rate Gated Synapse. (17 MB) |
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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.
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| 17. |
Firing Rate Modulatory Synapse. (15 MB) |
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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.
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