GenerateStims.py

import opencortex.core as oc


def generate(cell_id, duration, reference, 
             Ensyn = 100, 
             bEnsyn = 200,
             Erate = 8,
             Irate = 8,
             st_onset = 200.0,
             st_duration = 200.0,
             EbGroundRate = 2,
             IbGroundRate = 2):

    Insyn = int(Ensyn * 0.2)
    bInsyn = int(bEnsyn * 0.2)
    
    cell_file = '%s.cell.nml'%cell_id

    nml_doc, network = oc.generate_network(reference, temperature='35degC')

    oc.include_neuroml2_cell_and_channels(nml_doc,cell_file,cell_id)
    
    oc.include_neuroml2_file(nml_doc,'AMPA_NMDA.synapse.nml')
    oc.include_neuroml2_file(nml_doc,'GABA.synapse.nml')

    ampa_nmda1 = oc.add_transient_poisson_firing_synapse(nml_doc,
                                       id="ampa_nmda1",
                                       average_rate="%s Hz"%Erate,
                                       synapse_id='AMPA_NMDA',
                                       delay='%s ms'%st_onset,
                                       duration='%s ms'%st_duration)

                                       
    gaba1 = oc.add_transient_poisson_firing_synapse(nml_doc,
                                       id="gaba1",
                                       average_rate="%s Hz"%Irate,
                                       synapse_id='GABA',
                                       delay='%s ms'%st_onset,
                                       duration='%s ms'%st_duration)

    ampa_nmda_b = oc.add_poisson_firing_synapse(nml_doc,
                                       id="ampa_nmda_b",
                                       average_rate="%s Hz"%EbGroundRate,
                                       synapse_id='AMPA_NMDA')
                                       
    gaba_b = oc.add_poisson_firing_synapse(nml_doc,
                                       id="gaba_b",
                                       average_rate="%s Hz"%IbGroundRate,
                                       synapse_id='GABA')


    pop = oc.add_single_cell_population(network,
                                        'L23_pop',
                                        cell_id)
    
            
    oc.add_targeted_inputs_to_population(network, 
                                         "Esyn",
                                         pop, 
                                         ampa_nmda1.id, 
                                         segment_group='dendrite_group',
                                         number_per_cell = Ensyn,
                                         all_cells=True)
            

    oc.add_targeted_inputs_to_population(network, 
                                         "Isyn",
                                         pop, 
                                         gaba1.id, 
                                         segment_group='dendrite_group',
                                         number_per_cell = Insyn,
                                         all_cells=True)
    
            
    oc.add_targeted_inputs_to_population(network, 
                                         "Ebsyn",
                                         pop, 
                                         ampa_nmda_b.id, 
                                         segment_group='dendrite_group',
                                         number_per_cell = bEnsyn,
                                         all_cells=True)
            
    oc.add_targeted_inputs_to_population(network, 
                                         "Ibsyn",
                                         pop, 
                                         gaba_b.id, 
                                         segment_group='dendrite_group',
                                         number_per_cell = bInsyn,
                                         all_cells=True)
                                

    nml_file_name = '%s.net.nml'%network.id
    oc.save_network(nml_doc, nml_file_name, validate=False)

    interesting_seg_ids = [0,200,1000,2000,2500,2949] # [soma, .. some dends .. , axon]

    to_plot = {'Some_voltages':[]}
    to_save = {'%s_voltages.dat'%cell_id:[]}

    for seg_id in interesting_seg_ids:
        to_plot.values()[0].append('%s/0/%s/%s/v'%(pop.id, pop.component,seg_id))
        to_save.values()[0].append('%s/0/%s/%s/v'%(pop.id, pop.component,seg_id))

    oc.generate_lems_simulation(nml_doc, 
                                network, 
                                nml_file_name, 
                                duration, 
                                dt = 0.025,
                               gen_plots_for_all_v = False,
                               plot_all_segments = False,
                               gen_plots_for_quantities = to_plot,   #  Dict with displays vs lists of quantity paths
                               gen_saves_for_all_v = False,
                               save_all_segments = False,
                               gen_saves_for_quantities = to_save)   #  Dict with file names vs lists of quantity paths)

    
if __name__ == "__main__":
    
    cell_id = 'L23_NoHotSpot'
    reference = "L23_Stim"
    duration = 600
        
    generate(cell_id, duration, reference, Ensyn=100, bEnsyn=200)