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hnn_simple.py
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"""
netParams.py
High-level specifications for HNN network model using NetPyNE
Contributors: [email protected]
"""
from netpyne import specs
import numpy as np
import itertools as it
"""
cfg.py
Simulationg configuration for NetPyNE-based HNN network model
Contributors: [email protected]
"""
from netpyne import specs
cfg = specs.SimConfig()
simConfig = cfg
cfg.checkErrors = False # True # leave as False to avoid extra printouts
# ############################################################################
#
# SIMULATION CONFIGURATION
#
# ############################################################################
# ----------------------------------------------------------------------------
#
# NetPyNE config parameters (not part of original HNN implementation)
#
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
# Run parameters
# ----------------------------------------------------------------------------
cfg.duration = 170
cfg.dt = 0.025
cfg.seeds = {'conn': 4321, 'stim': 1234, 'loc': 4321}
cfg.hParams['v_init'] = -65
cfg.verbose = 0
cfg.cvode_active = False
cfg.printRunTime = 0.1
cfg.printPopAvgRates = True
cfg.distributeSynsUniformly = False # one syn per section in list of sections
cfg.allowSelfConns = False # allow connections from a cell to itself
cfg.allowConnsWithWeight0 = False # do not allow conns with weight 0 (faster)
cfg.oneSynPerNetcon = False # allow using the same synapse for multiple netcons
# ----------------------------------------------------------------------------
# Recording
# ----------------------------------------------------------------------------
cfg.recordTraces = {'V_soma': {'sec': 'soma', 'loc': 0.5, 'var': 'v'}}
cfg.recordCells = [('L2Basket',0), ('L2Pyr',0), ('L5Basket',0), ('L5Pyr',0)]
cfg.recordStims = False
cfg.recordStep = 0.025
cfg.recordDipoles = {'L2': ['L2Pyr'], 'L5': ['L5Pyr']}
# cfg.recordLFP = [[50, 50, 50], [50, 1300, 50]]
# ----------------------------------------------------------------------------
# Saving
# ----------------------------------------------------------------------------
cfg.sim_prefix = cfg.simLabel = 'default'
cfg.saveFolder = '.'
cfg.savePickle = False
cfg.saveJson = False
cfg.saveDataInclude = ['simData', 'simConfig'] #, 'netParams', 'net']
# ----------------------------------------------------------------------------
# Analysis and plotting
# ----------------------------------------------------------------------------
pops = ['L2Basket', 'L2Pyr', 'L5Basket', 'L5Pyr']
evprox = ['evokedProximal_1_L2Basket', 'evokedProximal_1_L2Pyr', 'evokedProximal_1_L5Basket', 'evokedProximal_1_L5Pyr',
'evokedProximal_2_L2Basket', 'evokedProximal_2_L2Pyr', 'evokedProximal_2_L5Basket', 'evokedProximal_2_L5Pyr']
evdist = ['evokedDistal_1_L2Basket', 'evokedDistal_1_L2Pyr', 'evokedDistal_1_L5Basket', 'evokedDistal_1_L5Pyr']
popColors = {'L2Basket': [0.0, 0.0, 0.0], 'L2Pyr': [0.0, 0.6, 0.0], 'L5Basket': [0.0, 0.0, 1.0], 'L5Pyr': [1.0, 0.0, 0.0],
'Evoked proximal': [0.0, 1.0, 1.0], 'Evoked distal': [1.0, 1.0, 0.0]}
cfg.analysis['iplotTraces'] = {'include': [('L5Pyr',0) ], 'oneFigPer': 'cell', 'saveFig': False,
'showFig': True, 'timeRange': [0, cfg.duration]}
cfg.analysis['iplotRaster'] = {'include': pops, 'showFig': True, 'popColors': popColors, 'markerSize': 6, 'orderInverse': True}
cfg.analysis['iplotSpikeHist'] = {'include': [*pops, evprox, evdist, 'extRhythmicProximal', 'extRhythmicDistal'], 'legendLabels': pops + ['Evoked proximal', 'Evoked distal', 'Rhythmic proximal', 'Rhythmic distal'], 'popColors': popColors, 'yaxis': 'count', 'showFig': True}
cfg.analysis['iplotDipole'] = {'showFig': True}
cfg.analysis['iplotDipolePSD'] = {'showFig': True, 'maxFreq': 80} # change freq to 40 for alpha&beta tut
cfg.analysis['iplotDipoleSpectrogram'] = {'showFig': True, 'maxFreq': 80} # change freq to 40 for alpha&beta tut
cfg.analysis['iplotConn'] = {'includePre': pops, 'includePost': pops, 'feature': 'strength'}
# cfg.analysis['iplotLFP'] = {'showFig': True}
#cfg.analysis['iplotRatePSD'] = {'include': pops, 'showFig': True}
# ----------------------------------------------------------------------------
# Network parameters
# ----------------------------------------------------------------------------
cfg.gridSpacingPyr = 1 # 50
cfg.gridSpacingBasket = [1, 1, 3]
cfg.xzScaling = 1 #100
cfg.sizeY = 2000
cfg.localConn = True
cfg.rhythmicInputs = True
cfg.evokedInputs = True
cfg.tonicInputs = True
cfg.poissonInputs = True
cfg.gaussInputs = True
# ----------------------------------------------------------------------------
#
# HNN original config parameters (adapted to NetPyNE)
#
# ----------------------------------------------------------------------------
# Params from 'ERPYes100Trials.param'; copied from cfg.__dict__
cfg.__dict__.update({
'duration': 170.0,
'tstop': 170,
'dt': 0.05,
'hParams': {'celsius': 37, 'v_init': -65, 'clamp_resist': 0.001},
'cache_efficient': False,
'cvode_active': False,
'cvode_atol': 0.001,
'seeds': {'conn': 4321, 'stim': 1234, 'loc': 4321},
'rand123GlobalIndex': None,
'createNEURONObj': True,
'createPyStruct': True,
'addSynMechs': True,
'includeParamsLabel': True,
'gatherOnlySimData': False,
'compactConnFormat': False,
'connRandomSecFromList': True,
'distributeSynsUniformly': False,
'pt3dRelativeToCellLocation': True,
'invertedYCoord': True,
'allowSelfConns': False,
'allowConnsWithWeight0': False,
'oneSynPerNetcon': False,
'saveCellSecs': True,
'saveCellConns': True,
'timing': True,
'saveTiming': False,
'printRunTime': 0.1,
'printPopAvgRates': True,
'printSynsAfterRule': False,
'verbose': 0,
'recordCells': [('L2Basket', 0), ('L2Pyr', 0), ('L5Basket', 0), ('L5Pyr', 0)],
'recordTraces': {'V_soma': {'sec': 'soma', 'loc': 0.5, 'var': 'v'}},
'recordCellsSpikes': -1,
'recordStim': False,
'recordLFP': [],
'recordDipoles': {'L2': ['L2Pyr'], 'L5': ['L5Pyr']},
'saveLFPCells': False,
'recordStep': 0.05,
'recordTime': True,
'simLabel': 'default',
'saveFolder': '.',
'filename': './default',
'saveDataInclude': ['simData', 'simConfig'],
'timestampFilename': False,
'savePickle': False,
'saveJson': False,
'saveMat': False,
'saveCSV': False,
'saveDpk': False,
'saveHDF5': False,
'saveDat': False,
'backupCfgFile': [],
'checkErrors': False,
'checkErrorsVerbose': False,
'recordStims': False,
'sim_prefix': 'ERPYes100Trials',
'gridSpacingPyr': 1,
'gridSpacingBasket': [1, 1, 3],
'xzScaling': 1,
'sizeY': 2000,
'localConn': True,
'rhythmicInputs': True,
'evokedInputs': True,
'tonicInputs': True,
'poissonInputs': True,
'gaussInputs': True,
'EEgain': 1.0,
'EIgain': 1.0,
'IEgain': 1.0,
'IIgain': 1.0,
'celsius': 37.0,
'threshold': 0.0,
'L2Pyr_soma_L': 22.1,
'L2Pyr_soma_diam': 23.4,
'L2Pyr_soma_cm': 0.6195,
'L2Pyr_soma_Ra': 200.0,
'L2Pyr_dend_cm': 0.6195,
'L2Pyr_dend_Ra': 200.0,
'L2Pyr_apicaltrunk_L': 59.5,
'L2Pyr_apicaltrunk_diam': 4.25,
'L2Pyr_apical1_L': 306.0,
'L2Pyr_apical1_diam': 4.08,
'L2Pyr_apicaltuft_L': 238.0,
'L2Pyr_apicaltuft_diam': 3.4,
'L2Pyr_apicaloblique_L': 340.0,
'L2Pyr_apicaloblique_diam': 3.91,
'L2Pyr_basal1_L': 85.0,
'L2Pyr_basal1_diam': 4.25,
'L2Pyr_basal2_L': 255.0,
'L2Pyr_basal2_diam': 2.72,
'L2Pyr_basal3_L': 255.0,
'L2Pyr_basal3_diam': 2.72,
'L2Pyr_ampa_e': 0.0,
'L2Pyr_ampa_tau1': 0.5,
'L2Pyr_ampa_tau2': 5.0,
'L2Pyr_nmda_e': 0.0,
'L2Pyr_nmda_tau1': 1.0,
'L2Pyr_nmda_tau2': 20.0,
'L2Pyr_gabaa_e': -80.0,
'L2Pyr_gabaa_tau1': 0.5,
'L2Pyr_gabaa_tau2': 5.0,
'L2Pyr_gabab_e': -80.0,
'L2Pyr_gabab_tau1': 1.0,
'L2Pyr_gabab_tau2': 20.0,
'L2Pyr_soma_gkbar_hh2': 0.01,
'L2Pyr_soma_gnabar_hh2': 0.18,
'L2Pyr_soma_el_hh2': -65.0,
'L2Pyr_soma_gl_hh2': 4.26e-05,
'L2Pyr_soma_gbar_km': 250.0,
'L2Pyr_dend_gkbar_hh2': 0.01,
'L2Pyr_dend_gnabar_hh2': 0.15,
'L2Pyr_dend_el_hh2': -65.0,
'L2Pyr_dend_gl_hh2': 4.26e-05,
'L2Pyr_dend_gbar_km': 250.0,
'L5Pyr_soma_L': 39.0,
'L5Pyr_soma_diam': 28.9,
'L5Pyr_soma_cm': 0.85,
'L5Pyr_soma_Ra': 200.0,
'L5Pyr_dend_cm': 0.85,
'L5Pyr_dend_Ra': 200.0,
'L5Pyr_apicaltrunk_L': 102.0,
'L5Pyr_apicaltrunk_diam': 10.2,
'L5Pyr_apical1_L': 680.0,
'L5Pyr_apical1_diam': 7.48,
'L5Pyr_apical2_L': 680.0,
'L5Pyr_apical2_diam': 4.93,
'L5Pyr_apicaltuft_L': 425.0,
'L5Pyr_apicaltuft_diam': 3.4,
'L5Pyr_apicaloblique_L': 255.0,
'L5Pyr_apicaloblique_diam': 5.1,
'L5Pyr_basal1_L': 85.0,
'L5Pyr_basal1_diam': 6.8,
'L5Pyr_basal2_L': 255.0,
'L5Pyr_basal2_diam': 8.5,
'L5Pyr_basal3_L': 255.0,
'L5Pyr_basal3_diam': 8.5,
'L5Pyr_ampa_e': 0.0,
'L5Pyr_ampa_tau1': 0.5,
'L5Pyr_ampa_tau2': 5.0,
'L5Pyr_nmda_e': 0.0,
'L5Pyr_nmda_tau1': 1.0,
'L5Pyr_nmda_tau2': 20.0,
'L5Pyr_gabaa_e': -80.0,
'L5Pyr_gabaa_tau1': 0.5,
'L5Pyr_gabaa_tau2': 5.0,
'L5Pyr_gabab_e': -80.0,
'L5Pyr_gabab_tau1': 1.0,
'L5Pyr_gabab_tau2': 20.0,
'L5Pyr_soma_gkbar_hh2': 0.01,
'L5Pyr_soma_gnabar_hh2': 0.16,
'L5Pyr_soma_el_hh2': -65.0,
'L5Pyr_soma_gl_hh2': 4.26e-05,
'L5Pyr_soma_gbar_ca': 60.0,
'L5Pyr_soma_taur_cad': 20.0,
'L5Pyr_soma_gbar_kca': 0.0002,
'L5Pyr_soma_gbar_km': 200.0,
'L5Pyr_soma_gbar_cat': 0.0002,
'L5Pyr_soma_gbar_ar': 1e-06,
'L5Pyr_dend_gkbar_hh2': 0.01,
'L5Pyr_dend_gnabar_hh2': 0.14,
'L5Pyr_dend_el_hh2': -71.0,
'L5Pyr_dend_gl_hh2': 4.26e-05,
'L5Pyr_dend_gbar_ca': 60.0,
'L5Pyr_dend_taur_cad': 20.0,
'L5Pyr_dend_gbar_kca': 0.0002,
'L5Pyr_dend_gbar_km': 200.0,
'L5Pyr_dend_gbar_cat': 0.0002,
'L5Pyr_dend_gbar_ar': 1e-06,
'N_pyr_x': 10,
'N_pyr_y': 10,
'gbar_L2Pyr_L2Pyr_ampa': 0.0005,
'gbar_L2Pyr_L2Pyr_nmda': 0.0005,
'gbar_L2Basket_L2Pyr_gabaa': 0.05,
'gbar_L2Basket_L2Pyr_gabab': 0.05,
'gbar_L2Pyr_L2Basket': 0.0005,
'gbar_L2Basket_L2Basket': 0.02,
'gbar_L5Pyr_L5Pyr_ampa': 0.0005,
'gbar_L5Pyr_L5Pyr_nmda': 0.0005,
'gbar_L2Pyr_L5Pyr': 0.00025,
'gbar_L2Basket_L5Pyr': 0.001,
'gbar_L5Basket_L5Pyr_gabaa': 0.025,
'gbar_L5Basket_L5Pyr_gabab': 0.025,
'gbar_L5Basket_L5Basket': 0.02,
'gbar_L5Pyr_L5Basket': 0.0005,
'gbar_L2Pyr_L5Basket': 0.00025,
'L2Basket_Gauss_A_weight': 0.0,
'L2Basket_Gauss_mu': 2000.0,
'L2Basket_Gauss_sigma': 3.6,
'L2Basket_Pois_A_weight_ampa': 0.0,
'L2Basket_Pois_A_weight_nmda': 0.0,
'L2Basket_Pois_lamtha': 0.0,
'L2Pyr_Gauss_A_weight': 0.0,
'L2Pyr_Gauss_mu': 2000.0,
'L2Pyr_Gauss_sigma': 3.6,
'L2Pyr_Pois_A_weight_ampa': 0.0,
'L2Pyr_Pois_A_weight_nmda': 0.0,
'L2Pyr_Pois_lamtha': 0.0,
'L5Pyr_Gauss_A_weight': 0.0,
'L5Pyr_Gauss_mu': 2000.0,
'L5Pyr_Gauss_sigma': 4.8,
'L5Pyr_Pois_A_weight_ampa': 0.0,
'L5Pyr_Pois_A_weight_nmda': 0.0,
'L5Pyr_Pois_lamtha': 0.0,
'L5Basket_Gauss_A_weight': 0.0,
'L5Basket_Gauss_mu': 2000.0,
'L5Basket_Gauss_sigma': 2.0,
'L5Basket_Pois_A_weight_ampa': 0.0,
'L5Basket_Pois_A_weight_nmda': 0.0,
'L5Basket_Pois_lamtha': 0.0,
't0_pois': 0.0,
'T_pois': -1,
'distribution_prox': 'normal',
't0_input_prox': 1000.0,
'tstop_input_prox': 1001,
'f_input_prox': 10.0,
'f_stdev_prox': 20.0,
'events_per_cycle_prox': 2,
'repeats_prox': 10,
't0_input_stdev_prox': 0.0,
'distribution_dist': 'normal',
't0_input_dist': 1000,
'tstop_input_dist': 1001,
'f_input_dist': 10.0,
'f_stdev_dist': 20.0,
'events_per_cycle_dist': 2,
'repeats_dist': 10,
't0_input_stdev_dist': 0.0,
'input_prox_A_weight_L2Pyr_ampa': 0.0,
'input_prox_A_weight_L2Pyr_nmda': 0.0,
'input_prox_A_weight_L5Pyr_ampa': 0.0,
'input_prox_A_weight_L5Pyr_nmda': 0.0,
'input_prox_A_weight_L2Basket_ampa': 0.0,
'input_prox_A_weight_L2Basket_nmda': 0.0,
'input_prox_A_weight_L5Basket_ampa': 0.0,
'input_prox_A_weight_L5Basket_nmda': 0.0,
'input_prox_A_delay_L2': 0.1,
'input_prox_A_delay_L5': 1.0,
'input_dist_A_weight_L2Pyr_ampa': 0.0,
'input_dist_A_weight_L2Pyr_nmda': 0.0,
'input_dist_A_weight_L5Pyr_ampa': 0.0,
'input_dist_A_weight_L5Pyr_nmda': 0.0,
'input_dist_A_weight_L2Basket_ampa': 0.0,
'input_dist_A_weight_L2Basket_nmda': 0.0,
'input_dist_A_delay_L2': 5.0,
'input_dist_A_delay_L5': 5.0,
'dt_evprox0_evdist': (-1,),
'dt_evprox0_evprox1': (-1,),
'sync_evinput': 0,
'inc_evinput': 0.0,
'Itonic_A_L2Pyr_soma': 0.0,
'Itonic_t0_L2Pyr_soma': 0.0,
'Itonic_T_L2Pyr_soma': -1.0,
'Itonic_A_L2Basket': 0.0,
'Itonic_t0_L2Basket': 0.0,
'Itonic_T_L2Basket': -1.0,
'Itonic_A_L5Pyr_soma': 0.0,
'Itonic_t0_L5Pyr_soma': 0.0,
'Itonic_T_L5Pyr_soma': -1.0,
'Itonic_A_L5Basket': 0.0,
'Itonic_t0_L5Basket': 0.0,
'Itonic_T_L5Basket': -1.0,
'save_spec_data': 0,
'f_max_spec': 100,
'dipole_scalefctr': 3000,
'dipole_smooth_win': 30,
'save_figs': 0,
'save_vsoma': 0,
'N_trials': 100,
'prng_state': None,
'prng_seedcore_input_prox': 4,
'prng_seedcore_input_dist': 4,
'prng_seedcore_extpois': 4,
'prng_seedcore_extgauss': 4,
'expmt_groups': '{ERPYes100Trials}',
'prng_seedcore_evprox_1': 4,
'prng_seedcore_evdist_1': 4,
'prng_seedcore_evprox_2': 4,
'prng_seedcore_evdist_2': 0,
't_evprox_1': 26.61,
'sigma_t_evprox_1': 2.47,
'numspikes_evprox_1': 1,
'gbar_evprox_1_L2Pyr_ampa': 0.01525,
'gbar_evprox_1_L2Pyr_nmda': 0.0,
'gbar_evprox_1_L2Basket_ampa': 0.08831,
'gbar_evprox_1_L2Basket_nmda': 0.0,
'gbar_evprox_1_L5Pyr_ampa': 0.00865,
'gbar_evprox_1_L5Pyr_nmda': 0.0,
'gbar_evprox_1_L5Basket_ampa': 0.19934,
'gbar_evprox_1_L5Basket_nmda': 0.0,
't_evdist_1': 63.53,
'sigma_t_evdist_1': 3.85,
'numspikes_evdist_1': 1,
'gbar_evdist_1_L2Pyr_ampa': 7e-06,
'gbar_evdist_1_L2Pyr_nmda': 0.004317,
'gbar_evdist_1_L2Basket_ampa': 0.006562,
'gbar_evdist_1_L2Basket_nmda': 0.019482,
'gbar_evdist_1_L5Pyr_ampa': 0.1423,
'gbar_evdist_1_L5Pyr_nmda': 0.080074,
't_evprox_2': 137.12,
'sigma_t_evprox_2': 8.33,
'numspikes_evprox_2': 1,
'gbar_evprox_2_L2Pyr_ampa': 1.43884,
'gbar_evprox_2_L2Pyr_nmda': 0.0,
'gbar_evprox_2_L2Basket_ampa': 3e-06,
'gbar_evprox_2_L2Basket_nmda': 0.0,
'gbar_evprox_2_L5Pyr_ampa': 0.684013,
'gbar_evprox_2_L5Pyr_nmda': 0.0,
'gbar_evprox_2_L5Basket_ampa': 0.008958,
'gbar_evprox_2_L5Basket_nmda': 0.0})
# ----------------------------------------------------------------------------
# Cell parameters
# ----------------------------------------------------------------------------
# dictionary to store cellParams (cell property rules)
cellParams = specs.CellParams()
# ------------------------------------------------------------------------------------
# L2 Pyr cell rule
# ------------------------------------------------------------------------------------
cellParams['L2Pyr'] = {
'secLists': {
'apical': ['apical_trunk', 'apical_1', 'apical_tuft', 'apical_oblique'],
'basal': ['basal_1', 'basal_2', 'basal_3']},
'secs': {
'soma': {
'geom': {'L': cfg.L2Pyr_soma_L,
'Ra': cfg.L2Pyr_soma_Ra,
'cm': cfg.L2Pyr_soma_cm,
'diam': cfg.L2Pyr_soma_diam,
'nseg': 1,
'pt3d': [[0.0, 0.0, 0.0, cfg.L2Pyr_soma_diam],
[0.0, 0.0+cfg.L2Pyr_soma_L, 0.0, cfg.L2Pyr_soma_diam]]},
'ions': {
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0, 'o': 140.0}
},
'mechs': {
'dipole': {},
'hh2': {'el': cfg.L2Pyr_soma_el_hh2,
'gkbar': cfg.L2Pyr_soma_gkbar_hh2,
'gl': cfg.L2Pyr_soma_gl_hh2,
'gnabar': cfg.L2Pyr_soma_gnabar_hh2},
'km': {'gbar': cfg.L2Pyr_soma_gbar_km}},
'topol': {}
},
'apical_1': {
'geom': {'L': cfg.L2Pyr_apical1_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_apical1_diam,
'nseg': 7,
'pt3d': [
[0.0, 48.0, 0.0, cfg.L2Pyr_apical1_diam],
[0.0, 48.0+cfg.L2Pyr_apical1_L, 0.0, cfg.L2Pyr_apical1_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_trunk', 'parentX': 1.0}
},
'apical_oblique': {
'geom': {'L': cfg.L2Pyr_apicaloblique_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_apicaloblique_diam,
'nseg': 7,
'pt3d': [[0.0, 48.0, 0.0, cfg.L2Pyr_apicaloblique_diam],
[0.0-cfg.L2Pyr_apicaloblique_L, 48.0, 0.0, cfg.L2Pyr_apicaloblique_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_trunk', 'parentX': 1.0}
},
'apical_trunk': {
'geom': {'L': cfg.L2Pyr_apicaltrunk_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_apicaltrunk_diam,
'nseg': 1,
'pt3d': [
[0.0, 13.0, 0.0, cfg.L2Pyr_apicaltrunk_diam],
[0.0, 13.0+cfg.L2Pyr_apicaltrunk_L, 0.0, cfg.L2Pyr_apicaltrunk_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'soma', 'parentX': 1.0}
},
'apical_tuft': {
'geom': {'L': cfg.L2Pyr_apicaltuft_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_apicaltuft_diam,
'nseg': 5,
'pt3d': [[0.0, 228.0, 0.0, cfg.L2Pyr_apicaltuft_diam],
[0.0, 228.0+cfg.L2Pyr_apicaltuft_L, 0.0, cfg.L2Pyr_apicaltuft_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_1', 'parentX': 1.0}
},
'basal_1': {
'geom': {'L': cfg.L2Pyr_basal1_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_basal1_diam,
'nseg': 1,
'pt3d': [[0.0, 0.0, 0.0, cfg.L2Pyr_basal1_diam],
[0.0, 0.0-cfg.L2Pyr_basal1_L, 0.0, cfg.L2Pyr_basal1_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'soma', 'parentX': 0.0}
},
'basal_2': {
'geom': {
'L': cfg.L2Pyr_basal2_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_basal2_diam,
'nseg': 5,
'pt3d': [[0.0, -50.0, 0.0, cfg.L2Pyr_basal2_diam],
[0.0-cfg.L2Pyr_basal2_L/np.sqrt(2), -50.0-cfg.L2Pyr_basal2_L/np.sqrt(2), 0.0, cfg.L2Pyr_basal2_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'basal_1', 'parentX': 1.0}
},
'basal_3': {
'geom': {'L': cfg.L2Pyr_basal3_L,
'Ra': cfg.L2Pyr_dend_Ra,
'cm': cfg.L2Pyr_dend_cm,
'diam': cfg.L2Pyr_basal3_diam,
'nseg': 5,
'pt3d': [[0.0, -50.0, 0.0, cfg.L2Pyr_basal3_diam],
[float(0.0+cfg.L2Pyr_basal3_L/np.sqrt(2)), float(-50.0-cfg.L2Pyr_basal3_L/np.sqrt(2)), 0.0, cfg.L2Pyr_basal3_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'basal_1', 'parentX': 1.0}
}}}
## add biophysics (ions and mechs) to L2Pyr dendrites
somaL = cellParams['L2Pyr']['secs']['soma']['geom']['L']
for sec in [sec for secName, sec in cellParams['L2Pyr']['secs'].items() if secName != 'soma']:
sec['ions'] = {
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0, 'o': 140.0}}
sec['mechs'] = {
'dipole': {},
'hh2': {'el': cfg.L2Pyr_dend_el_hh2,
'gkbar': cfg.L2Pyr_dend_gkbar_hh2,
'gl': cfg.L2Pyr_dend_gl_hh2,
'gnabar': cfg.L2Pyr_dend_gnabar_hh2},
'km': {'gbar': cfg.L2Pyr_dend_gbar_km}}
## set vinit
for sec in cellParams['L2Pyr']['secs'].values():
sec['vinit'] = -71.46
# ------------------------------------------------------------------------------------
# L2 Basket cell rule
# ------------------------------------------------------------------------------------
cellParams['L2Basket'] = {
'secs': {
'soma': {
'geom': {'L': 39.0,
'Ra': 200.0,
'cm': 0.85,
'diam': 20.0,
'nseg': 1},
'ions': {
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0,'o': 140.0}},
'mechs': {
'hh2': {'el': -54.3,
'gkbar': 0.036,
'gl': 0.0003,
'gnabar': 0.12}},
'topol': {}
}}}
## set vinit
for secName,sec in cellParams['L2Basket']['secs'].items():
sec['vinit'] = -64.9737
# ------------------------------------------------------------------------------------
# L5 Pyramidal cell rule
# ------------------------------------------------------------------------------------
cellParams['L5Pyr'] = {
'secLists': {
'apical': ['apical_trunk', 'apical_1', 'apical_2', 'apical_tuft', 'apical_oblique'],
'basal': ['basal_1', 'basal_2', 'basal_3']},
'secs': {
'soma': {
'geom': {'L': cfg.L5Pyr_soma_L,
'Ra': cfg.L5Pyr_soma_Ra,
'cm': cfg.L5Pyr_soma_cm,
'diam': cfg.L5Pyr_soma_diam,
'nseg': 1,
'pt3d': [[0.0, 0.0, 0.0, cfg.L5Pyr_soma_diam],
[0.0, 0.0+cfg.L5Pyr_soma_L, 0.0, cfg.L5Pyr_soma_diam]]},
'ions': {
'ca': {'e': 132.4579341637009, 'i': 5e-05, 'o': 2.0},
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0, 'o': 140.0}},
'mechs': {
'ar_hnn': {'gbar': cfg.L5Pyr_soma_gbar_ar},
'ca_hnn': {'gbar': cfg.L5Pyr_soma_gbar_ca},
'cad': {'taur': cfg.L5Pyr_soma_taur_cad},
'cat_hnn': {'gbar': cfg.L5Pyr_soma_gbar_cat},
'dipole': {},
'hh2': {'el': cfg.L5Pyr_soma_el_hh2,
'gkbar': cfg.L5Pyr_soma_gkbar_hh2,
'gl': cfg.L5Pyr_soma_gl_hh2,
'gnabar': cfg.L5Pyr_soma_gnabar_hh2},
'kca': {'gbar': cfg.L5Pyr_soma_gbar_kca},
'km': {'gbar': cfg.L5Pyr_soma_gbar_km}},
'topol': {}
},
'apical_1': {
'geom': {'L': cfg.L5Pyr_apical1_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_apical1_diam,
'nseg': 13,
'pt3d': [[0.0, 83.0, 0.0, cfg.L5Pyr_apical1_diam],
[0.0, 83.0+cfg.L5Pyr_apical1_L, 0.0, cfg.L5Pyr_apical1_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_trunk','parentX': 1.0}
},
'apical_2': {
'geom': {'L': cfg.L5Pyr_apical2_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_apical2_diam,
'nseg': 13,
'pt3d': [[0.0, 483.0, 0.0, cfg.L5Pyr_apical2_diam],
[0.0, 483.0+cfg.L5Pyr_apical2_L, 0.0, cfg.L5Pyr_apical2_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_1', 'parentX': 1.0}
},
'apical_oblique': {
'geom': {'L': cfg.L5Pyr_apicaloblique_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_apicaloblique_diam,
'nseg': 5,
'pt3d': [[0.0, 83.0, 0.0, cfg.L5Pyr_apicaloblique_diam],
[0.0-cfg.L5Pyr_apicaloblique_L, 83.0, 0.0, cfg.L5Pyr_apicaloblique_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_trunk', 'parentX': 1.0}
},
'apical_trunk': {
'geom': {'L': cfg.L5Pyr_apicaltrunk_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_apicaltrunk_diam,
'nseg': 3,
'pt3d': [[0.0, 23.0, 0.0, cfg.L5Pyr_apicaltrunk_diam ],
[0.0, 23.0+cfg.L5Pyr_apicaltrunk_L, 0.0, cfg.L5Pyr_apicaltrunk_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'soma', 'parentX': 1.0}
},
'apical_tuft': {
'geom': {'L': cfg.L5Pyr_apicaltuft_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_apicaltuft_diam,
'nseg': 9,
'pt3d': [[0.0, 883.0, 0.0, cfg.L5Pyr_apicaltuft_diam],
[0.0, 883.0+cfg.L5Pyr_apicaltuft_L, 0.0, cfg.L5Pyr_apicaltuft_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'apical_2', 'parentX': 1.0}
},
'basal_1': {
'geom': {'L': cfg.L5Pyr_basal1_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_basal1_diam,
'nseg': 1,
'pt3d': [[0.0, 0.0, 0.0, cfg.L5Pyr_basal1_diam],
[0.0, 0.0-cfg.L5Pyr_basal1_L, 0.0, cfg.L5Pyr_basal1_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'soma', 'parentX': 0.0}
},
'basal_2': {
'geom': {'L': cfg.L5Pyr_basal2_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_basal2_diam,
'nseg': 5,
'pt3d': [[0.0, -50.0, 0.0, cfg.L5Pyr_basal2_diam],
[float(0.0-cfg.L5Pyr_basal2_L/np.sqrt(2)), float(-50-cfg.L5Pyr_basal2_L/np.sqrt(2)), 0.0, cfg.L5Pyr_basal2_diam]]},
'topol': {'childX': 0.0, 'parentSec': 'basal_1', 'parentX': 1.0}
},
'basal_3': {
'geom': {'L': cfg.L5Pyr_basal3_L,
'Ra': cfg.L5Pyr_dend_Ra,
'cm': cfg.L5Pyr_dend_cm,
'diam': cfg.L5Pyr_basal3_diam,
'nseg': 5,
'pt3d': [[0.0, -50.0, 0.0, cfg.L5Pyr_basal3_diam],
[float(0.0+cfg.L5Pyr_basal2_L/np.sqrt(2)), float(-50-cfg.L5Pyr_basal2_L/np.sqrt(2)), 0.0, cfg.L5Pyr_basal3_diam]]},
'topol': {
'childX': 0.0,
'parentSec': 'basal_1',
'parentX': 1.0}
}}}
## add biophysics (ions and mechs) to L5Pyr dendrites
gbar_ar = { # values calculated for each segment as: seg.gbar_ar = 1e-6 * np.exp(3e-3 * h.distance(seg.x)) (from orig HNN)
'apical_trunk': [1.1829366e-06, 1.3099645e-06, 1.450633e-06],
'apical_1': [1.6511327e-06, 1.9316694e-06, 2.2598709e-06, 2.6438357e-06, 3.0930382e-06, 3.6185628e-06, 4.2333769e-06, 4.9526514e-06, 5.7941347e-06, 6.7785908e-06, 7.9303114e-06, 9.2777159e-06, 1.0854052e-05],
'apical_2': [1.2698216e-05, 1.4855715e-05, 1.7379784e-05, 2.0332707e-05, 2.3787348e-05, 2.7828952e-05, 3.2557247e-05, 3.8088907e-05, 4.4560426e-05, 5.2131493e-05, 6.0988926e-05, 7.1351287e-05, 8.3474272e-05],
'apical_tuft': [9.6914906e-05, 0.00011166463, 0.00012865915, 0.00014824011, 0.00017080115, 0.0001967958, 0.00022674665, 0.0002612558, 0.00030101698], 'apical_oblique': [1.6478971e-06, 1.9203357e-06, 2.2378151e-06, 2.6077819e-06, 3.0389133e-06],
'basal_1': [1.1359849e-06],
'basal_2': [1.3930561e-06, 1.6233631e-06, 1.8917456e-06, 2.2044984e-06, 2.5689571e-06],
'basal_3': [1.3930561e-06, 1.6233631e-06, 1.8917456e-06, 2.2044984e-06, 2.5689571e-06]}
somaL = cellParams['L5Pyr']['secs']['soma']['geom']['L']
for secName, sec in [(secName, sec) for secName, sec in cellParams['L5Pyr']['secs'].items() if secName != 'soma']:
sec['ions'] = {
'ca': {'e': 132.4579341637009, 'i': 5e-05, 'o': 2.0},
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0, 'o': 140.0}}
L = sec['geom']['L']
nseg = sec['geom']['nseg']
sec['mechs'] = {
# gbar_ar value depends of distance from soma
'ar_hnn': {'gbar': gbar_ar[secName]}, #[1e-6*np.exp(3e-3 * ((L/nseg)*i+(L/nseg)/2)) for i in range(nseg)]},
'ca_hnn': {'gbar': cfg.L5Pyr_dend_gbar_ca},
'cad': {'taur': cfg.L5Pyr_dend_taur_cad},
'cat_hnn': {'gbar': cfg.L5Pyr_dend_gbar_cat},
'dipole': {},
'hh2': {'el': cfg.L5Pyr_dend_el_hh2,
'gkbar': cfg.L5Pyr_dend_gkbar_hh2,
'gl': cfg.L5Pyr_dend_gl_hh2,
'gnabar': cfg.L5Pyr_dend_gnabar_hh2},
'kca': {'gbar': cfg.L5Pyr_dend_gbar_kca},
'km': {'gbar': cfg.L5Pyr_dend_gbar_km}}
## set vinit
for secName,sec in cellParams['L5Pyr']['secs'].items():
if secName == 'apical_1':
sec['vinit'] = -71.32
elif secName == 'apical_2':
sec['vinit'] = -69.08
elif secName == 'apical_tuft':
sec['vinit'] = -67.30
else:
sec['vinit'] = -72.
# ------------------------------------------------------------------------------------
# L5 Basket cell rule
# ------------------------------------------------------------------------------------
cellParams['L5Basket'] = {
'secs': {
'soma': {
'geom': {'L': 39.0,
'Ra': 200.0,
'cm': 0.85,
'diam': 20.0,
'nseg': 1},
'ions': {
'k': {'e': -77.0, 'i': 54.4, 'o': 2.5},
'na': {'e': 50.0, 'i': 10.0,'o': 140.0}},
'mechs': {
'hh2': {'el': -54.3,
'gkbar': 0.036,
'gl': 0.0003,
'gnabar': 0.12}},
'topol': {}
}}}
## set vinit
for secName,sec in cellParams['L5Basket']['secs'].items():
sec['vinit'] = -64.9737
# ----------------------------------------------------------------------------
#
# NETWORK PARAMETERS
#
# ----------------------------------------------------------------------------
netParams = specs.NetParams() # object of class NetParams to store the network parameters
#------------------------------------------------------------------------------
# General network parameters
#------------------------------------------------------------------------------
netParams.sizeX = ((cfg.N_pyr_x * cfg.gridSpacingPyr) - 1) * cfg.xzScaling # x-dimension (horizontal length) size in um
netParams.sizeY = cfg.sizeY # y-dimension (vertical height or cortical depth) size in um
netParams.sizeZ = ((cfg.N_pyr_y * cfg.gridSpacingPyr) - 1) * cfg.xzScaling # z-dimension (horizontal depth) size in um
netParams.shape = 'cuboid'
netParams.cellsVisualizationSpacingMultiplier = [50, 1, 50]
# ----------------------------------------------------------------------------
# Cell parameters
# ----------------------------------------------------------------------------
netParams.cellParams = cellParams
# ----------------------------------------------------------------------------
# Population parameters
# ----------------------------------------------------------------------------
# layer locations
layersE = {'L2': [0.0*cfg.sizeY, 0.0*cfg.sizeY], 'L5': [0.654*cfg.sizeY, 0.654*cfg.sizeY]} # 0.654 = 1308/2000
layersI = {'L2': [0.0*cfg.sizeY-00.0, 0.0*cfg.sizeY-00.0], 'L5': [0.654*cfg.sizeY-00.0, 0.654*cfg.sizeY-00.0]}
# Create list of locations for Basket cells based on original ad hoc rules
# define relevant x spacings for basket cells
xzero = np.arange(0, cfg.N_pyr_x, 3)
xone = np.arange(1, cfg.N_pyr_x, 3)
yeven = np.arange(0, cfg.N_pyr_y, 2)
yodd = np.arange(1, cfg.N_pyr_y, 2)
coords = [pos for pos in it.product(xzero, yeven)] + [pos for pos in it.product(xone, yodd)]
coords_sorted = sorted(coords, key=lambda pos: pos[1])
L2BasketLocs = [{'x': int(coord[0]*cfg.xzScaling), 'y': int(layersI['L2'][0]), 'z': int(coord[1]*cfg.xzScaling)} for coord in coords_sorted]
L5BasketLocs = [{'x': int(coord[0]*cfg.xzScaling), 'y': int(layersI['L5'][0]), 'z': int(coord[1]*cfg.xzScaling)} for coord in coords_sorted]
# create popParams
netParams.popParams['L2Basket'] = {'cellType': 'L2Basket', 'cellModel': 'HH_simple', 'numCells': len(L2BasketLocs), 'cellsList': L2BasketLocs}
netParams.popParams['L2Pyr'] = {'cellType': 'L2Pyr', 'cellModel': 'HH_reduced', 'yRange': layersE['L2'], 'gridSpacing': cfg.gridSpacingPyr*cfg.xzScaling}
netParams.popParams['L5Basket'] = {'cellType': 'L5Basket', 'cellModel': 'HH_simple', 'numCells': len(L5BasketLocs), 'cellsList': L5BasketLocs}
netParams.popParams['L5Pyr'] = {'cellType': 'L5Pyr', 'cellModel': 'HH_reduced', 'yRange': layersE['L5'], 'gridSpacing': cfg.gridSpacingPyr*cfg.xzScaling}
# create variables useful for connectivity
pops = list(netParams.popParams.keys())
cellsPerPop = {}
cellsPerPop['L2Pyr'] = cellsPerPop['L5Pyr'] = int(cfg.N_pyr_x * cfg.N_pyr_x)
cellsPerPop['L2Basket'] = cellsPerPop['L5Basket'] = int(np.ceil(cfg.N_pyr_x * cfg.N_pyr_x / cfg.gridSpacingBasket[2]) + 1)
#------------------------------------------------------------------------------
# Synaptic mechanism parameters
#------------------------------------------------------------------------------
netParams.synMechParams['L2Pyr_AMPA'] = {'mod':'Exp2Syn', 'tau1': cfg.L2Pyr_ampa_tau1, 'tau2': cfg.L2Pyr_ampa_tau2, 'e': cfg.L2Pyr_ampa_e}
netParams.synMechParams['L2Pyr_NMDA'] = {'mod': 'Exp2Syn', 'tau1': cfg.L2Pyr_nmda_tau1, 'tau2': cfg.L2Pyr_nmda_tau2, 'e': cfg.L2Pyr_nmda_e}
netParams.synMechParams['L2Pyr_GABAA'] = {'mod':'Exp2Syn', 'tau1': cfg.L2Pyr_gabaa_tau1, 'tau2': cfg.L2Pyr_gabaa_tau2, 'e': cfg.L2Pyr_gabaa_e}
netParams.synMechParams['L2Pyr_GABAB'] = {'mod':'Exp2Syn', 'tau1': cfg.L2Pyr_gabab_tau1, 'tau2': cfg.L2Pyr_gabab_tau2, 'e': cfg.L2Pyr_gabab_e}
netParams.synMechParams['L5Pyr_AMPA'] = {'mod':'Exp2Syn', 'tau1': cfg.L5Pyr_ampa_tau1, 'tau2': cfg.L5Pyr_ampa_tau2, 'e': cfg.L5Pyr_ampa_e}
netParams.synMechParams['L5Pyr_NMDA'] = {'mod': 'Exp2Syn', 'tau1': cfg.L5Pyr_nmda_tau1, 'tau2': cfg.L5Pyr_nmda_tau2, 'e': cfg.L5Pyr_nmda_e}
netParams.synMechParams['L5Pyr_GABAA'] = {'mod':'Exp2Syn', 'tau1': cfg.L5Pyr_gabaa_tau1, 'tau2': cfg.L5Pyr_gabaa_tau2, 'e': cfg.L5Pyr_gabaa_e}
netParams.synMechParams['L5Pyr_GABAB'] = {'mod':'Exp2Syn', 'tau1': cfg.L5Pyr_gabab_tau1, 'tau2': cfg.L5Pyr_gabab_tau2, 'e': cfg.L5Pyr_gabab_e}
netParams.synMechParams['AMPA'] = {'mod':'Exp2Syn', 'tau1': 0.5, 'tau2': 5.0, 'e': 0}
netParams.synMechParams['NMDA'] = {'mod': 'Exp2Syn', 'tau1': 1, 'tau2': 20, 'e': 0}
netParams.synMechParams['GABAA'] = {'mod':'Exp2Syn', 'tau1': 0.5, 'tau2': 5, 'e': -80}
netParams.synMechParams['GABAB'] = {'mod':'Exp2Syn', 'tau1': 1, 'tau2': 20, 'e': -80}
#------------------------------------------------------------------------------
# Local connectivity parameters
#------------------------------------------------------------------------------
# Weight and delay distance-dependent functions (as strings) to use in conn rules
weightDistFunc = '{A_weight} * exp(-(dist_2D**2) / ({lamtha}**2))'
delayDistFunc = '{A_delay} / exp(-(dist_2D**2) / ({lamtha}**2))'
if cfg.localConn:
# L2 Pyr -> L2 Pyr
synParamsList = [{'synMech': 'L2Pyr_AMPA',
'A_weight': cfg.EEgain * cfg.gbar_L2Pyr_L2Pyr_ampa,
'A_delay': 1.,
'lamtha': 3.},
{'synMech': 'L2Pyr_NMDA',
'A_weight': cfg.EEgain * cfg.gbar_L2Pyr_L2Pyr_nmda,
'A_delay': 1.,
'lamtha': 3.}]
for i,synParams in enumerate(synParamsList):
netParams.connParams['L2Pyr->L2Pyr_%d'%(i)] = {
'preConds': {'pop': 'L2Pyr'},
'postConds': {'pop': 'L2Pyr'},
'synMech': synParams['synMech'],
'weight': weightDistFunc.format(**synParams), # equivalent to weightDistFunc.format(A_weight=cfg.gbar_L2Pyr_L2Pyr_ampa, lamtha=1.)
'delay': delayDistFunc.format(**synParams),
'synsPerConn': 3,
'sec': ['basal_2', 'basal_3','apical_oblique', ]}
# L2 Basket -> L2 Pyr
synParamsList = [{'synMech': 'L2Pyr_GABAA',
'A_weight': cfg.IEgain * cfg.gbar_L2Basket_L2Pyr_gabaa,
'A_delay': 1.,
'lamtha': 50.},
{'synMech': 'L2Pyr_GABAB',
'A_weight': cfg.IEgain * cfg.gbar_L2Basket_L2Pyr_gabab,
'A_delay': 1.,
'lamtha': 50.}]
for i,synParams in enumerate(synParamsList):
netParams.connParams['L2Basket->L2Pyr_%d'%(i)] = {
'preConds': {'pop': 'L2Basket'},
'postConds': {'pop': 'L2Pyr'},
'synMech': synParams['synMech'],
'weight': weightDistFunc.format(**synParams),
'delay': delayDistFunc.format(**synParams),
'synsPerConn': 1,
'sec': ['soma']}
# L2 Pyr -> L2 Basket
synParams = {'synMech': 'AMPA',
'A_weight': cfg.EIgain * cfg.gbar_L2Pyr_L2Basket,
'A_delay': 1.,
'lamtha': 3.}
netParams.connParams['L2Pyr->L2Basket_%s'%(synParams['synMech'])] = {
'preConds': {'pop': 'L2Pyr'},
'postConds': {'pop': 'L2Basket'},
'synMech': synParams['synMech'],
'weight': weightDistFunc.format(**synParams),
'delay': delayDistFunc.format(**synParams),
'synsPerConn': 1,
'sec': ['soma']}
# L2 Basket -> L2 Basket
synParams = {'synMech': 'GABAA',
'A_weight': cfg.IIgain * cfg.gbar_L2Basket_L2Basket,
'A_delay': 1.,
'lamtha': 20.}
netParams.connParams['L2Basket->L2Basket'] = {
'preConds': {'pop': 'L2Basket'},
'postConds': {'pop': 'L2Basket'},
'synMech': synParams['synMech'],
'weight': weightDistFunc.format(**synParams),
'delay': delayDistFunc.format(**synParams),
'synsPerConn': 1,
'sec': ['soma']}
# L5 Pyr -> L5 Pyr
synParamsList = [{'synMech': 'L5Pyr_AMPA',
'A_weight': cfg.EEgain * cfg.gbar_L5Pyr_L5Pyr_ampa,
'A_delay': 1.,
'lamtha': 3.},
{'synMech': 'L5Pyr_NMDA',
'A_weight': cfg.EEgain * cfg.gbar_L5Pyr_L5Pyr_nmda,
'A_delay': 1.,
'lamtha': 3.}]
for i,synParams in enumerate(synParamsList):
netParams.connParams['L5Pyr->L5Pyr_%d'%(i)] = {
'preConds': {'pop': 'L5Pyr'},
'postConds': {'pop': 'L5Pyr'},
'synMech': synParams['synMech'],
'weight': weightDistFunc.format(**synParams),
'delay': delayDistFunc.format(**synParams),
'synsPerConn': 3,
'sec': ['basal_2', 'basal_3', 'apical_oblique']}
# L5 Basket -> L5 Pyr
synParamsList = [{'synMech': 'L5Pyr_GABAA',
'A_weight': cfg.IEgain * cfg.gbar_L5Basket_L5Pyr_gabaa,
'A_delay': 1.,
'lamtha': 70.},
{'synMech': 'L5Pyr_GABAB',
'A_weight': cfg.IEgain * cfg.gbar_L5Basket_L5Pyr_gabab,