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@@ -1,73 +1,107 @@
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-This repository contains the code used for the following manuscript:
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-Kumaraswamy, A., Maksutov, A., Kai, K., Ai, H., Ikeno, H., & Wachtler, T. (2017). Network simulations of interneuron circuits in the honeybee primary auditory center. *bioRxiv*. https://doi.org/10.1101/159533
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-Authors:
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-Ajayrama Kumaraswamy, ajkumaraswamy@tutamail.com
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-Based on and contains parts of work by Aynur Maksutov during AMGEN program 2016 at Wachtlerlab, LMU.
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-
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-Installation:
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-With anaconda (recommended):
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-
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- 1. conda create --name Ai2017Sim -c brian-team ipython>=6.1 numpy>=1.11.2 matplotlib>=1.5.3 seaborn>=0.7.1 brian2>=2.0.1 python>=3.5
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- 2. source activate Ai2017Sim (unix) or activate Ai2017Sim (windows)
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- 3. pip install <full path of this repository>
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-
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-without anaconda, normal python installation required (https://www.python.org/)
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-
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- 1. Install virtualenvwrapper (unix) or virtualenvwrapper-win (windows) be pre-installed with pip
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- 2. (only on windows) Install microsoft Visual C++ 14.0. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
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- 3. mkvirtualenv Ai2017Sim
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- 4. pip install <full path of this repository>
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-
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-Usage:
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- 1. source activate Ai2017Sim (unix) or activate Ai2017Sim (windows)
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- 2. Change the variable homeFolder in dirDefs.py to a folder. The results of the simulation will be stored here.
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- 3. The scripts of this repo are described below. All of them have some parameters at their top. Change these and run the scripts as needed.
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-
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-
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-Here is an overview of the contents:
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-
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-.
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-+-- Ai2017Sim.yml: A file that can be used to create a conda environment to run the scripts below. Essentially is a list of dependencies.
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-+-- models
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-| +-- neuronModels.py: wrapper classes for brian2 neuron models
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-| +-- neurons.py: Model equations and static parameters for neurons
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-| +-- synapses.py: Model equations for synapses
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-|
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-+-- paramLists
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-| +-- AdExpPars.py: Parameter combinations for the AdExp model
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-| +-- inputParsList.py: Stimulii definitions
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-| +-- synapsePropsList.py: Parameter combinations for the difference of exponential synaptic conductance model
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-|
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-+-- brianUtils.py: utility function related to brian2
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-|
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-+-- dirDefs.py: directory definitions imported in other scripts
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-|
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-+-- DLInt1SynCurrent.py: Script to simulate DL-Int-1 recording membrane potential and synaptic currents in [NIX](https://github.com/G-Node/nixpy) files
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-|
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-+-- DLInt2try.py: Legacy code
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-|
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-+-- forAi2017.py: Script to generate a subplot of an upcoming manuscript.
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-|
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-+-- JODLInt1DLInt2: Class to run network simulations
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-|
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-+-- justDLInt1.py: Legacy code
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-|
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-+-- mplPars.py: matplotlib rc parameters
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-|
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-+-- neoNIXIO.py: adapted from GJEMS, utility functions to work jointly with [NIX](https://github.com/G-Node/nixpy) and [neo](https://github.com/NeuralEnsemble/python-neo).
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-|
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-+-- plotDLInt1DLInt2SynEffects.py: script to plot summary of DL-Int-1 and DL-Int-2 responses to pulse trains.
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-+-- plotShortStims.py: script to plot summary of DL-Int-1 and DL-Int-2 responses to short continuous pulses.
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-|
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-+-- plotSynCurrents.py: script to plot membrane potential and synaptic currents of DL-Int-1 and DL-Int-2 for one stimulus.
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-|
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-+-- runJODLInt1DLInt2Multiple.py: script to simulate the network for multiple stimulii. Out is saved as a [NIX](https://github.com/G-Node/nixpy) File.
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-|
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-+-- simSynCurrents.py: script to simulate DL-Int-1 and DL-Int-2 recording membrane potential and synaptics currents in a [NIX](https://github.com/G-Node/nixpy) file.
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+# Description
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+This repository contains the code to simulate a neuronal network in the honeybee primary auditory center.
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+
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+Author:
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+Ajayrama Kumaraswamy, ajayramak@bio.lmu.de
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+
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+Reference:
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+>Kumaraswamy, A., Maksutov, A., Kai, K., Ai, H., Ikeno, H., & Wachtler, T. (2017). Network simulations of interneuron circuits in the honeybee primary auditory center. *bioRxiv*. https://doi.org/10.1101/159533
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+
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+This model has been added to ModelDB ([Accession number 239413](https://senselab.med.yale.edu/ModelDB/showmodel.cshtml?model=239413#tabs-1))
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+
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+This repo contains parts of the code written by Aynur Maksutov during AMGEN program 2016 at Wachtlerlab, LMU, Munich.
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+
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+
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+# Installation
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+## With anaconda (recommended):
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+
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+Step 1: Download the repository
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+
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+
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+Step 2: Create a new virtual environment and install some dependencies
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+
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+`conda create --name Ai2017Sim -c brian-team ipython>=6.1 numpy>=1.11.2 matplotlib>=1.5.3 seaborn>=0.7.1 brian2>=2.0.1 python>=3.5`
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+
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+Step 3: Activate the virtual environment
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+
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+`source activate Ai2017Sim` (unix) or `activate Ai2017Sim` (windows)
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+
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+
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+Step 4: Install the package (the option '-e' is required)
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+
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+`pip install -e <full path of this repository>`
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+
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+
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+## Without anaconda (normal python installation required, https://www.python.org/)
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+
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+Step 1: Download the repository
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+
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+Step 2: Install virtualenvwrapper (unix) or virtualenvwrapper-win (windows) with pip
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+
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+Step 3: (only on windows) Install microsoft Visual C++ 14.0. Get it with "Microsoft Visual C++ Build Tools" [here](http://landinghub.visualstudio.com/visual-cpp-build-tools)
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+
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+Step 4: Create virtual environment
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+
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+`mkvirtualenv Ai2017Sim`
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+
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+
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+Step 5: Install the package (the option '-e' is required)
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+
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+`pip install -e <full path of this repository>`
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+
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+# Usage:
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+Step 1: Activate the virtual environment
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+
|
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+`source activate Ai2017Sim` (unix) or `activate Ai2017Sim` (windows)
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+
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+Step 2: Change the variable 'homeFolder' in the file 'dirDefs.py' to a folder of your choice. The results of the simulation will be stored here.
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+
|
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+Step 3: The scripts of this repository are described below. All of them have some parameters at their top. Change these and run the scripts as needed.
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+
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+
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+# Overview of Contents
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+
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+* **HB-PAC_disinhibitory_network**
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+ * **Ai2017Sim.yml:** A file that can be used to create a conda environment to run the scripts below. Essentially is a list of dependencies.
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+
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+ * **models**
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+
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+ * **neuronModels.py:** wrapper classes for brian2 neuron models
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+ * **neurons.py:** Model equations and static parameters for neurons
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+ * **synapses.py:** Model equations for synapses
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+
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+ * **paramLists**
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+
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+ * **AdExpPars.py:** Parameter combinations for the AdExp model
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+ * **inputParsList.py:** Stimulii definitions
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+ * **synapsePropsList.py:** Parameter combinations for the difference of exponential synaptic conductance model
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+
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+ * **brianUtils.py:** utility functions related to brian2
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+
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+ * **dirDefs.py:** directory definitions imported in other scripts
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+
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+ * **DLInt1SynCurrent.py:** Script to simulate DL-Int-1 recording membrane potential and synaptic currents in [NIX](https://github.com/G-Node/nixpy) files
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+
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+ * **DLInt2try.py:** Legacy code
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+
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+ * **forAi2017.py:** Script to generate a subplot of an upcoming manuscript.
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+
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+ * **JODLInt1DLInt2:** Class to run network simulations
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+
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+ * **justDLInt1.py:** Legacy code
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+
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+ * **mplPars.py:** matplotlib rc parameters
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+
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+ * **neoNIXIO.py:** adapted from [GJEphys](https://github.com/wachtlerlab/GJEphys), utility functions to work jointly with [NIX](https://github.com/G-Node/nixpy) and [neo](https://github.com/NeuralEnsemble/python-neo).
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+
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+ * **plotDLInt1DLInt2SynEffects.py:** script to plot summary of DL-Int-1 and DL-Int-2 responses to pulse trains.
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+
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+ * **plotShortStims.py:** script to plot summary of DL-Int-1 and DL-Int-2 responses to short continuous pulses.
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+
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+ * **plotSynCurrents.py:** script to plot membrane potential and synaptic currents of DL-Int-1 and DL-Int-2 for one stimulus.
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+
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+ * **runJODLInt1DLInt2Multiple.py:** script to simulate the network for multiple stimulii. Output is saved as a [NIX](https://github.com/G-Node/nixpy) File.
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+
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+ * **simSynCurrents.py:** script to simulate DL-Int-1 and DL-Int-2 recording membrane potential and synaptics currents in a [NIX](https://github.com/G-Node/nixpy) file.
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