Home

LSNM (Large-Scale Neural Modeling) simulator, command_line_version, by the Brain Imaging and Modeling Section, NIDCD/NIH

The LSNM simulator (commmand-line version) can be executed directly on a unix/linux terminal or remotely on the Neuroscience Gateway (NSG) Portal. Please find below instructions for both.

Running LSNM directly on a unix/linux terminal

The following syntax should be used:

python lsnm.py -m model.txt -w weightslist.txt -s script.py -l lsnm_tvb_link.txt

• lsnm.py is the python script that runs the simulation.
• weightlist.txt contains a list of individual *.w weight files (all should be included in working directory).
• script.py is the script of simulation describing all events in the simulated experiment.
• lsnm_tvb_link.txt is an optional parameter that describes how the LSNM model is embedded into a Virtual Brain (TVB) connectome.

The output is a large number of *.out files in text format that contain time-series of simulated neural and synaptic activity. They are all saved as output files.

Running LSNM on the NSG portal:

1. Group all input files (model.txt, weightslist.txt, script.py, and all of the individual *.w files describing connections among modules in your network) into a single folder and compress that folder into a zip file.
2. Log in to your NSG account at www.nsgportal.org
3. Upload the zipped input data file into your working NSG folder's Data subdirectory.
4. Push the Create New Task button
5. Push the Select Tool button and select the LSNM on Commet option
6. Enter a user-generated identifier for your simulation in the Description field
7. Push the Select Input Data button and select the zipped file containing input data
8. Push the Parameters button and enter the name of the file that describes your simulated experiment (e.g., script.py) in the Enter Main Input Filename field.
9. Modify the Maximum Hours to Run field to an estimate of the duration of your simulation. Remember that your job will be terminated when this time elapses (time that the job is waiting in the queue does not count though), so it is better to overestimate running time (say, 5-10 hours).
10. Leave the Enter subdirectory name field empty.
11. Leave the Number of nodes and Number of cores fields assigned to one. Only one node and one core are needed with the current version of LSNM.
12. Push the Save and Run Task button
13. When the task finishes running, push the View Output button.
14. Download the outputfile to your local computer and uncompress. Please note that you will end up with an output directory that contains debug and standard error files. Within that directory there will be a subdirectory named after your NSG task containing input files and output files.