Repo of the bachelor thesis 'Dynamic memory traces for sequence learning in spiking networks'

To run the code from the nest/ subdirectory NEST and NESTML (with gh pr checkout 805 for issue #805) are required.

To run the code in the legacy/ subdirectory Python 2.7 is required.

Updating the custom NESTML neuron and synapse models can be a bit tedious. The easiest way to do so is laid out here:

1. Generate a new target by setting the global variables NEURON_MODEL and SYNAPSE_MODEL to the names of your custom models in the nest/nestml_models subdirectory and calling python nest_network.py regen_models. This will create and install a new target in the nest/nestml_targets subdirectory.
2. Reimport all the custom changes made to support normalization_sum and InstantaneousRateConnectionEvent in the corresponding .cpp and .h files.
3. Run make -j 4 install to recompile the model with the custom changes.