[BBPBGLIB-1059] Integrate Oren's gap junction compensation procedure into neurodamus

[WeinaJi]

Context

Integrate Oren's compensation script for gap junction synapses into the neurodamus main flow. Uses are expected to use predefined parameters in the SONATA simulation config files to configure the correction steps and values. In this PR, those parameters are stored in the experimental "beta_features" section of the SONATA config files. The corresponding formal SONATA parameters are to be determined in the SONATA specifications, the libsonata parser, and the future PR in neurodamus.

Scope

At the finalize step for GapJunctionManager, if users set the right gapjunction_target_population, the user corrections defined in the new file gj_user_functions.py will be triggered. This file is implemented based on Oren's script which was used for Elisabetta's publication (/gpfs/bbp.cscs.ch/project/proj55/software/gap_junctions/pylibs/manager_python.py). It provides these corrections to be enabled by users via the SONATA simulation config file:

1. Set deterministic = 1 for StochKv mechanisms set in the simulation config file "deterministic_stoch"
2. Update the conductance value of gap synapses to the value set in the simulation config file "gjc"
3. Remove cell channel mechanisms set by "remove_channels"
4. Update segment g_pas to fit the gjc with values set by the calibration file given in the simulation config file "load_g_pas_file"
5. Add current clamps to certain cells where the gids and the amplitudes are read from the file given in the simulation config "manual_MEComboInfo_file"
6. Add SEClamps to the certain cells where the gids and the amplitudes are read from the file given in the simulation config "vc_amp" and meanwhile save the SEClamp Data

Those SONATA parameters are chosen based on the setting in Elisabetta's publication /gpfs/bbp.cscs.ch/project/proj55/iavarone/releases/simulations/spontaneous_evoked/CorrectCTFiberAll_Backgroundwith_afferents_MLNoise25_CTNoise4/MLStim4/MLNoise0/CTNoise0/settings.p for which corrections 1,2,4,5 were used.

Testing

New test test_v5_gap_junction_corrections in test/scientific/test_simulation.py

Review

• PR description is complete
• Coding style (imports, function length, New functions, classes or files) are good
• Unit/Scientific test added
• Updated Readme, in-code, developer documentation

[jorblancoa]

General comment:
Do we want to merge those in beta_features? or shall we wait to define them in the sonata-extension and then implement the necessary changes in libsonata first?

[orena1]

Hi @WeinaJi I think it looks good, but is there a way to test it?

[orena1]

Very cool, a bit off-topic, but there is also the code that generates the GJs and use them. I'll try to get it on github and we can refer to it.

[WeinaJi]

General comment: Do we want to merge those in beta_features? or shall we wait to define them in the sonata-extension and then implement the necessary changes in libsonata first?

Thinking about the time left, I am inclined to merge them in beta_features so @PolinaL can use in her thalamus simulation asap. This way we don't need the approval for the SONATA specs and the libsonata API.
For the SONATA specs, we need to define proper naming for all required parameters, and possibly store them in a proper section. Maybe we could brainstorm with scientists if time permits, @jamesgking ?

[WeinaJi]

Hi @WeinaJi I think it looks good, but is there a way to test it?

Hello @orena1 , can you access our bb5 cluster? If yes, you can clone this branch into your directory, load the thalamus module, and overwrite the neurodamus component with your local copy. Something like:

git clone [email protected]:BlueBrain/neurodamus.git -b weji/oren
module load unstable neurodamus-thalamus
export PYTHONPATH=$(pwd)/neurodamus:$PYTHONPATH
srun dplace special -mpi -python $NEURODAMUS_PYTHON/init.py --configFile=simulation_config.json

The config file simulation_config.json should contain the beta_features section like

{
"beta_features" :{
        "gapjunction_target_population": "thalamus_neurons",
        "deterministic_stoch": true,
        "procedure_type": "validation_sim",
        "gjc": 0.2,
        "load_g_pas_file": "/gpfs/bbp.cscs.ch/project/proj55/amsalem/gap_junctions/circ19_11_2019_gjs_19_20_20/rm_correction/Circ_mc2_Rt_Remove_ch_all_Det_stoch_True_Dis_holding_False_Correc_type_impedance_tool_Cm0p01_Num_iter_10/num_0/g_pas_passive.hdf5",
        "manual_MEComboInfo_file": "/gpfs/bbp.cscs.ch/project/proj55/amsalem/gap_junctions/circ19_11_2019_gjs_19_20_20_new_holding/find_holding_current/vc_ampFile/Circ_mc2_Rt_Remove_ch_none_Det_stoch_True_Dis_holding_False_gjc0p2_Change_mecomb_False_manual_MEComboInfoFile_False_Load_g_pas_True_Correc_iter_loadlast/num_0/holding_per_gid.hdf5"
    },
}

An example from my test config file /gpfs/bbp.cscs.ch/home/weji/JIRA/thalamus_elsabetta/0/simulation_config.json

Also cc @PolinaL

[WeinaJi]

Very cool, a bit off-topic, but there is also the code that generates the GJs and use them. I'll try to get it on github and we can refer to it.

That will be great. Please let me know if you would like to push something in this repo. I can give you the write permission.

In fact, I have another version of your script which includes these commented code:

# if load_g_pas_correction_file:
#     logging.info("Loading g_pas_correction_file")
#     exec(open('/gpfs/bbp.cscs.ch/home/amsalem/Dropbox/Blue_Brain/Experiments_Reproduction/Coupling_Coefficient/pylibs/gap_junction_conductance_search_damus.py').read())

Is it still needed? I can't find the script gap_junction_conductance_search_damus.py any more.

[ferdonline]

Some nitpicks, but it might be worth to a wider round of checks for naming and other small inconsistencies. vars starting in upcase remember class variables or constants

[bbpbuildbot]

Logfiles from GitLab pipeline #236165 (:white_check_mark:) have been uploaded here!

Status and direct links:

• ✅ docs
• ✅ test-unit
• ✅ test-integration
• ✅ test-integration-e2e
• ✅ test-scientific
• ✅ test-scientific-ngv
• ✅ set_alt_branches
• ✅ build-package
• ⚙️ publish-package
• ⚙️ publish-docs

[WeinaJi]

Very cool, a bit off-topic, but there is also the code that generates the GJs and use them. I'll try to get it on github and we can refer to it.

Hello @orena1, have you managed to test this branch on bb5? Or would you like to add your code in it?
As BBP closure is approaching, I would like to merge this feature into the main branch although it is still in "beta_futures". In this way, @PolinaL could check it out in another computing cluster after bb5 to continue her simulation.

[orena1]

Hi, sorry for the late response, this file is probably relevant for the process, in general the whole Coupling_Coefficient directory
https://github.com/orena1/Experiments_Reproduction/blob/master/Coupling_Coefficient/send_sim_to_share_v1.py