Add detailed neuron documentation #3448
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jessica-mitchell
added
T: Enhancement
ddahmen
suggested changes
May 9, 2025
| .. grid-item-card:: | ||
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| The autonomous dynamics describes the neuron behavior in the absence of stimulation or in the presence of constant inputs, |
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| The autonomous dynamics describes the neuron behavior in the absence of stimulation or in the presence of constant inputs, | |
| The autonomous dynamics describe the neuron behavior in the absence of stimulation or in the presence of constant inputs, |
| :columns: 7 | ||
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| Increment state variables associated with the post-spike dynamics | ||
| (such as refractoriness timers or adaptation variables), and send spike. |
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| (such as refractoriness timers or adaptation variables), and send spike. | |
| (such as refractoriness timers or adaptation variables), and send events (e.g. spike). |
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| When the membrane potential reaches a certain threshold, | ||
| the neuron deterministically "fires" an action potential |
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| the neuron deterministically "fires" an action potential | |
| the neuron deterministically "fires" an action potential. |
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| When the membrane potential reaches a certain threshold, | ||
| the neuron deterministically "fires" an action potential | ||
| Neuron models iwth hard threshold do not contain intrinsic dynamics that produce the upswing of a spike. The downswing is realized |
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| Neuron models iwth hard threshold do not contain intrinsic dynamics that produce the upswing of a spike. The downswing is realized | |
| Neuron models with hard threshold do not contain intrinsic dynamics that produce the upswing of a spike. The downswing is realized |
| When the membrane potential reaches a certain threshold, | ||
| the neuron deterministically "fires" an action potential | ||
| Neuron models iwth hard threshold do not contain intrinsic dynamics that produce the upswing of a spike. The downswing is realized | ||
| is by an artificial reset mechanism |
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| is by an artificial reset mechanism | |
| is by an artificial reset mechanism. |
| Unlike a fixed threshold, an adaptive threshold increases temporarily following each spike and | ||
| gradually returns to its baseline value over time. This mechanism models phenomena | ||
| such as spike-frequency adaptation, where a neuron's responsiveness decreases with sustained | ||
| high-frequency input. |
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| high-frequency input. | |
| high-frequency input. A different mechanism to implement similar adaptation behavior is via a spike-triggered hyperpolarizing adaptation current. |
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| .. dropdown:: Auxillary neurons | ||
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| ignore-and-fire - used for benchmarking . . . |
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| ignore-and-fire - used for benchmarking . . . | |
| ignore-and-fire – Used for benchmarking |
| .. tab-item:: General info | ||
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| Mean-field theory |
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| Mean-field theory | |
| Rate models can also be used as mean-field descriptions for the population-rate dynamics of spiking networks. |
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| Neurons with two or three states. Simplest neuron models with threshold activation. Binary neurons have |
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| Neurons with two or three states. Simplest neuron models with threshold activation. Binary neurons have | |
| Neurons with two or three discrete states. These are the simplest neuron models with threshold activation. Binary neurons have |
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| Neurons with two or three states. Simplest neuron models with threshold activation. Binary neurons have | ||
| On / Off behavior used in theoretical and disease theory. |
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| On / Off behavior used in theoretical and disease theory. | |
| On / Off behavior used in theoretical neuroscience and disease theory. |
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This PR adds 2 new pages detailing neurons in NEST for users to better understand what's available in NEST from a comp neuroscience perspective.
the first page describes the various neuron types
the second page describes the update algorithm for neurons using iaf_psc_alpha as the example.
We use this model as an example as it's one that has extensive documentation updates, and is used as an example in many cases.
Further flowcharts will be considered in the future to describe other model types like rate neurons, but that is for another PR.
This PR focuses on neurons - but there are plans to add synase docs in another PR
See the output here: https://nest-simulator--3448.org.readthedocs.build/en/3448/neurons/neuron_types.html
https://nest-simulator--3448.org.readthedocs.build/en/3448/neurons/neuron_update.html