Model simulation using CARLsim:

1. See CARLsim documentation at http://uci-carl.github.io/CARLsim4/ for library setup

2. Simulation scripts and Makefile are available at https://github.com/Hippocampome-Org/Time/ (select tuneIzh9p)

3. Download CARLsim parameter file (param_file) for a neuron type/subtype from the neuron page

- Parameter file structure: , ,,... ,,... ,, , ,,,,,... ,, , ..., , ,...

- Every file has a single compartment model and if the morphology warrants it, a multi-compartment model (Venkadesh et al., 2018)

4. Choose the appropriate wrapper script for a compartment layout and run a CARLsim param_file as follows:

Single-compartment model:

sed -n 6p <param_file_name> | ./carlsim_tuneIzh9p_1c_wrapper

Multi-compartment model:

sed -n 7p <param_file_name> | ./carlsim_tuneIzh9p_<param_file_suffix>_wrapper

 

5. Following output files are generated in /results/

- One phenotype file (as a JSON object) that includes a list of spike times for every I/I_dur (soma_I_scenario) in param_file

- files for voltage plotting

- : number of compartments, : number of soma_I_scenarios, : number of simulation scenarios to test multi-compartment constraints (Venkadesh et al., 2018)

- Naming convention for voltage files: allV_<scenario_id>_<compartment_id>. For example, allV_0_0 denotes somatic voltage for the first I/I_dur scenario specified in the param_file, and allV_0_1 denotes dendritic voltage for the same simulation scenario. Voltage is recorded at 1ms resolution.

- One simulation log file

6. Optionally, you can include N models in a single param_file and run them all at once. Make sure to replace the line number (6p/7p) by the appropriate range of N lines. All output files will be prefixed with an index from 0 to N-1

Refer to this article for more details and discussion on multi-compartment models: Venkadesh S, Komendantov AO, Listopad S, Scott EO, De Jong K, Krichmar JL, Ascoli GA. (2018). Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types. Frontiers in neuroinformatics. https://doi.org/10.3389/fninf.2018.00008