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Potjans and Diesmann microcircuit model implementation in python

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PD_python

Potjans and Diesmann microcircuit model (PD) implementation in python

Files:

  • PD_python.py: python class to create and simulate a neuron network model with the GL neuron and poisson external input
  • run_PD_python.py: python script to run the microcircuit whith layer specific poisson external input
  • delay.npy: numpy array containing connection delay information. each line contains the delay from a single source to its respective target stored in the target.npy data below
  • target.npy: numpy array containing connection target information. each line contains the targer from a single source. weight and delay are described in a different array
  • weight.npy: numpy array containing connection weight information. each line contains the weight from a single source to its respective target. see above

Requirements:

  • python 3.6
  • numpy > 1.17

How to run:

python3 run_PD_python.py

Output

  • spike_recorder.txt: text file containig two colums with neuron id and spike time in (ms)

Scaled down version

There is a scaled down version in scaled branch which contains connectivity data and sample output

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Potjans and Diesmann microcircuit model implementation in python

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