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Wiki source code of NESTML

Version 2.1 by jessicamitchell on 2023/09/11 11:44
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1 Available tutorials:
2
3 === [[Izhikevich tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/izhikevich/nestml_izhikevich_tutorial.html||rel=" noopener noreferrer" target="_blank"]] ===
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5 //Level: beginner//
6
7 Learn how to write the Izhikevich spiking neuron model in NESTML.
8 === [[Active dendrite tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/active_dendrite/nestml_active_dendrite_tutorial.html||rel=" noopener noreferrer" target="_blank"]] ===
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10 //Level: advanced//
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12 Learn how to model a dendritic action potential in an existing NESTML neuron.
13 === [[Dopamine-modulated STDP synapse tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.html||rel=" noopener noreferrer" target="_blank"]] ===
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15 //Level: advanced//
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17 Adding dopamine modulation to the weight update rule of an STDP synapse allows it to be used in reinforcement learning tasks. This allows a network to learn which of the many cues and actions preceding a reward should be credited for the reward.
18 === [[Ornstein-Uhlenbeck noise tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/ornstein_uhlenbeck_noise/nestml_ou_noise_tutorial.html||rel=" noopener noreferrer" target="_blank"]] ===
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20 //Level: advanced//
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22 Implement the Ornstein-Uhlenbeck process in NESTML and use it to inject a noise current into a neuron.
23 === [[STDP synapse tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.html||rel=" noopener noreferrer" target="_blank"]] ===
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25 //Level: advanced//
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27 A triplet STDP rule is sensitive to third-order correlations of pre- and postsynaptic spike times, and accounts better for experimentally seen dependence on timing and frequency.
28 === [[STDP windows tutorial>>https://nestml.readthedocs.io/en/latest/tutorials/stdp_windows/stdp_windows.html||rel=" noopener noreferrer" target="_blank"]] ===
29
30 //Level: advanced//
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32 An STDP window describes how the strength of the synapse changes as a function of the relative timing of pre- and postsynaptic spikes. Several different STDP model variants with different window functions are implemented.