Skip to content

GLIF (Generalized Leaky Integrate and Fire) Models for NEST Simulator

License

Notifications You must be signed in to change notification settings

hengenlab/GLIF2NEST

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

64 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Glif Models Implementation in NEST Simulator

Build and install modules dynamically

$ mkdir build
$ cd build
$ cmake --Dwith-nest=nest-config -Dwith-ltdl=ON [-Dwith-mpi=ON] ../GlifModel
$ make
$ make install

Issues

  • Pull and compile nest from the latest on their github repository. The v2.10.0 isn't working.
  • Make sure ltdl-dev libraries are available (before compiling nest). On CentOS run sudo yum install libtool-ltdl-devel, on ubuntu libltdl-dev.
  • When compiling nest make sure to use absolute paths. When completed run nest-config --libs to make sure a full path to the nest libraries are used.

Instantiate Modules in pynest

import nest
nest.Install('glifmodule')
neuron = nest.Create('glif_lif') # or glif_lif_r, glif_lif_asc, glif_lif_r_asc

Issues

  • If you get a 'File not found' message when trying to install the module:
    • Try using nest.Install('glifmodule.so') instead (On CentOS 6 lt_dlopenext() isn't working properly).
    • Check LD_LIBRARY_PATH, if needed set export LD_LIBRARY_PATH="/full/path/to/nest/module:$LD_LIBRARY_PATH

Running and Testing

Download Cell-Types-DB models to local machine

In scripts/ folder, run the following command to install 10 specific modules (AllenSDK is required)

$ python allensdk_helper.py

Or to get a specific set of models for a given cell-id

$ python allensdk_helper.py CELL-ID1 [CELL-ID2 CELL-ID3 ...]

Test all downloaded models

$ python test_glif2nest.py 1> /dev/null

Run and qualitativly compare NEST and AllenSDK implementation

First determine the type in injection schemes are available

$ python run_model.py --list-stimuli

The following will run both NEST and AllenSDK implementation of a model and plot voltage-traces and spike-trains. Model download is not required.

$ python run_model.py --cells cell-id[,cell_id,...] --model LIF[-R|-ASC|-R-ASC|-R-ASC-A] --stimulus ramp-1[,long-square-1,ramp-2,...]

Run NEST implementation of Glif models with current-based synaptic ports

First determine the type in injection schemes are available

$ python run_model_psc.py --list-stimuli

The following will run NEST implementation of a 4 neurons network as described below and plot voltage-traces and spike-trains. Model download is not required.

  • One neuron is without synaptic port, the other three are with 2 syaptic ports (one port is 2.0ms and one port is 1.0ms);
  • The first neuron is connected the first port of the second neuron;
  • The first neuron is connected the second port of the third neuron;
  • The first neuron is also connected both ports of the fourth neuron;
  • The weights between first neuron and other neurons are all 1000.0.
$ python run_model_psc.py --cells cell-id[,cell_id,...] --model LIF[-R|-ASC|-R-ASC|-R-ASC-A] --stimulus ramp-1[,long-square-1,ramp-2,...]

Run NEST implementation of Glif models with conductance-based synaptic ports

First determine the type in injection schemes are available

$ python run_model_cond.py --list-stimuli

The following will run NEST implementation of a 4 neurons network as described below and plot voltage-traces and spike-trains. Model download is not required.

  • One neuron is without synaptic port, the other three are with 2 syaptic ports (one port is 2.0ms and one port is 1.0ms);
  • The first neuron is connected the first port of the second neuron;
  • The first neuron is connected the second port of the third neuron;
  • The first neuron is also connected both ports of the fourth neuron;
  • The weights between first neuron and other neurons are all 30.0.
$ python run_model_cond.py --cells cell-id[,cell_id,...] --model LIF[-R|-ASC|-R-ASC|-R-ASC-A] --stimulus ramp-1[,long-square-1,ramp-2,...]

Notes

  • Has only been tested with python 2.7

Update

About

GLIF (Generalized Leaky Integrate and Fire) Models for NEST Simulator

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 74.8%
  • Python 22.9%
  • CMake 2.3%