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aeif-model documentation does not point out peculiarities #3088

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heplesser opened this issue Feb 1, 2024 · 1 comment
Open

aeif-model documentation does not point out peculiarities #3088

heplesser opened this issue Feb 1, 2024 · 1 comment
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I: No breaking change Previously written code will work as before, no one should note anything changing (aside the fix) S: Normal Handle this with default priority stale Automatic marker for inactivity, please have another look here T: Enhancement New functionality, model or documentation

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@heplesser
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The current documentation for the aeif models does not point out two peculiarities of these models:

  1. The default refractory period to these models is zero. This is consistent with the model definition in Brette & Gerstner, but most likely unexpected, since NEST models generally have a non-zero refractory period.
  2. Because NEST uses an adaptive stepsize solver for the aeif ODEs with spike detection inside the update loop, aeif neurons can fire multiple spikes in a single time step if the refractory period is zero (the default). This can lead to exploding spike numbers and extreme slow-down of simulations.

Documentation should point this out clearly in note boxes and recommend users to set t_ref > 0.

@heplesser heplesser added T: Enhancement New functionality, model or documentation S: Normal Handle this with default priority I: No breaking change Previously written code will work as before, no one should note anything changing (aside the fix) labels Feb 1, 2024
@heplesser heplesser added this to To do in Documentation via automation Feb 1, 2024
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github-actions bot commented Apr 2, 2024

Issue automatically marked stale!

@github-actions github-actions bot added the stale Automatic marker for inactivity, please have another look here label Apr 2, 2024
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Labels
I: No breaking change Previously written code will work as before, no one should note anything changing (aside the fix) S: Normal Handle this with default priority stale Automatic marker for inactivity, please have another look here T: Enhancement New functionality, model or documentation
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