'''
Network parameters (netParams) script for Spinal Dorsal Horn Network Model
from Sekiguchi et al. (2021)
'''
from netpyne import specs, sim
from neuron import h
import numpy as np
import cells
from spkt_gen import *
import json
import sys
sys.path.insert(0, 'spkt') # adding path to spkt dir
import genrn
try:
from __main__ import cfg
except:
from cfg_mechanical import cfg
netParams = specs.NetParams()
#------------------------------------------------------------------------------
# Population
#------------------------------------------------------------------------------
### INPUT FREQUENCY FROM AFFERENT FIBERS WITH FIXED FACTOR ###
with open('spkt/spkt_SAI_%s.json' %(cfg.freq), 'rb') as spkt_SAI: spkt_SAI = json.load(spkt_SAI)
with open('spkt/spkt_SAII_%s.json' %(cfg.freq), 'rb') as spkt_SAII: spkt_SAII = json.load(spkt_SAII)
with open('spkt/spkt_Ad_%s.json' %(cfg.freq), 'rb') as spkt_Ad: spkt_Ad = json.load(spkt_Ad)
with open('spkt/spkt_C_%s.json' %(cfg.freq), 'rb') as spkt_C: spkt_C = json.load(spkt_C)
## PRIMARY AFFERENTS TIME-VARYING STIMULUS (NORMAL STIMULUS)
netParams.popParams['Ab_SAI'] = {'cellModel': 'VecStim', 'numCells': 10, 'spkTimes': spkt_SAI} # input from Ab_slow adapting type I
netParams.popParams['Ab_SAII'] = {'cellModel': 'VecStim', 'numCells': 10, 'spkTimes': spkt_SAII} # input from Ab_slow adapting type II
netParams.popParams['Ad'] = {'cellModel': 'VecStim', 'numCells': 20, 'spkTimes': spkt_Ad} # input from Adelta
netParams.popParams['C_PEP'] = {'cellModel': 'VecStim', 'numCells': 80, 'spkTimes': spkt_C} # input from peptidergic C fibers
netParams.popParams['C_NP'] = {'cellModel': 'VecStim', 'numCells': 80, 'spkTimes': spkt_C} # input from non-peptidergic C fibers
## SETTING OF SPINAL NEURONS
cells.PKCRule['conds'] = {'cellType': 'PKC'}
cells.INcellRule['conds'] = {'cellType': 'IN'}
cells.EXdelayedRule['conds'] = {'cellType': 'EXdl'}
cells.CRRule['conds'] = {'cellType': 'CR'}
cells.SOMRule['conds'] = {'cellType': 'SOM'}
cells.EXinitialRule['conds'] = {'cellType': 'EXib'}
cells.PROcellRule['conds'] = {'cellType': 'PRO'}
cells.PROcellRule['secs']['soma']['threshold'] = 0
netParams.cellParams['PKC'] = cells.PKCRule
netParams.cellParams['VGLUT3Rule'] = cells.EXdelayedRule
netParams.cellParams['PVRule'] = cells.INcellRule
netParams.cellParams['DORRule'] = cells.EXdelayedRule
netParams.cellParams['TrCRule'] = cells.EXinitialRule
netParams.cellParams['DYNRule'] = cells.INcellRule
netParams.cellParams['SOMRule'] = cells.SOMRule
netParams.cellParams['CRRule'] = cells.CRRule
netParams.cellParams['ISLETRule'] = cells.INcellRule
netParams.cellParams['NK1Rule'] = cells.PROcellRule
## SETTING POPULATION OF SPINAL NEURONS
netParams.popParams['PKC' ] = {'cellType': 'PKC', 'numCells': 30} # PKCg+ neurons (excitatory)
netParams.popParams['VGLUT3'] = {'cellType': 'EXdl', 'numCells': 4} # VGLUT3+ neurons (excitatory)
netParams.popParams['PV'] = {'cellType': 'IN', 'numCells': 15} # PV+ neurons (inhibitory)
netParams.popParams['DOR' ] = {'cellType': 'EXdl', 'numCells': 30} # DOR+ neurons (excitatory)
netParams.popParams['TrC'] = {'cellType': 'EXib', 'numCells': 10} # Transient Central neurons (excitatory)
netParams.popParams['DYN'] = {'cellType': 'IN', 'numCells': 60} # Central/DYN+ neurons (inhibitory)
netParams.popParams['SOM'] = {'cellType': 'SOM', 'numCells': 15} # SOM+ neurons (excitatory)
netParams.popParams['CR'] = {'cellType': 'CR', 'numCells': 20} # CR+ neurons (excitatory)
netParams.popParams['ISLET'] = {'cellType': 'IN', 'numCells': 15} # Islet-type neurons (inhibitory)
netParams.popParams['NK1'] = {'cellType': 'PRO', 'numCells': 10} # NK1+ neurons (projection)
###################################################################################################################################
# Synaptic Mechanisms
###################################################################################################################################
netParams.defaultThreshold = -30
netParams.synMechParams['AMPA'] = {'mod': 'AMPA_DynSyn' , 'tau_rise': 0.1, 'tau_decay': 5 }
netParams.synMechParams['NMDA'] = {'mod': 'NMDA_DynSyn' , 'tau_rise': 2 , 'tau_decay': 100 }
netParams.synMechParams['NK13'] = {'mod': 'NK1_DynSyn' , 'tau_rise': 100, 'tau_decay': 1000 }
netParams.synMechParams['NK23'] = {'mod': 'NK1_DynSyn' , 'tau_rise': 200, 'tau_decay': 3000 }
netParams.synMechParams['GABA'] = {'mod': 'GABAa_DynSyn' , 'tau_rise': 0.1, 'tau_decay': 20, 'e': -70 }
netParams.synMechParams['GLY'] = {'mod': 'Glycine_DynSyn', 'tau_rise': 0.1, 'tau_decay': 10, 'e': -70 }
###################################################################################################################################
# Connectivity Mechanisms
###################################################################################################################################
# From Abeta Fibres to Spinal Interneurons
netParams.connParams['Ab_SAI_AMPA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'PKC'},
'weight': cfg.Ab_EX_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAI_NMDA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'PKC'},
'weight': cfg.Ab_EX_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAI_AMPA->VGLUT3'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'VGLUT3'},
'weight': cfg.Ab_EX_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAI_NMDA->VGLUT3'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'VGLUT3'},
'weight': cfg.Ab_EX_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAI_AMPA->PV'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'PV'},
'weight': cfg.Ab_IN_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAI_NMDA->PV'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'PV'},
'weight': cfg.Ab_IN_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAI_AMPA->DYN'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAI'},
'postConds': {'popLabel': 'DYN'},
'weight': cfg.Ab_IN_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAII_AMPA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'PKC'},
'weight': cfg.Ab_EX_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAII_NMDA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'PKC'},
'weight': cfg.Ab_EX_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAII_AMPA->VGLUT3'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'VGLUT3'},
'weight': cfg.Ab_EX_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAII_NMDA->VGLUT3'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'VGLUT3'},
'weight': cfg.Ab_EX_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAII_AMPA->PV'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'PV'},
'weight': cfg.Ab_IN_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['Ab_SAII_NMDA->PV'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'PV'},
'weight': cfg.Ab_IN_NMDA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['Ab_SAII_AMPA->DYN'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ab_SAII'},
'postConds': {'popLabel': 'DYN'},
'weight': cfg.Ab_IN_AMPA,
'sec': 'dend',
'probability': 0.2,
'delay': 1.0,
'loc': 0.5,
'synMech': 'AMPA'}
# From Adelta to Spinal Interneurons
netParams.connParams['Ad_AMPA->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'DOR'},
'weight': cfg.Ad_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'AMPA'}
netParams.connParams['Ad_NMDA->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'DOR'},
'weight': cfg.Ad_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'NMDA'}
netParams.connParams['Ad_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.Ad_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'AMPA'}
netParams.connParams['Ad_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.Ad_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'NMDA'}
netParams.connParams['Ad_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.Ad_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'AMPA'}
netParams.connParams['Ad_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'Ad'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.Ad_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 5.0,
'loc': 0.50,
'synMech': 'NMDA'}
# From Peptidergic C (C,TRPV1) to Spinal Interneurons
netParams.connParams['C_PEP_AMPA->TrC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'TrC'},
'weight': cfg.C_TrC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.C_EX_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.C_EX_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['C_PEP_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.C_EX_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.C_EX_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['C_PEP_AMPA->DYN'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'DYN'},
'weight': cfg.C_DYN_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_AMPA->ISLET'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'ISLET'},
'weight': cfg.C_ISLET_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_AMPA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.C_NK1_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_PEP_NMDA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.C_NK1_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['C_PEP_NK1->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_PEP'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.C_NK1_NK1,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NK13'}
# From Non-Peptidergic C (C,IB4) to Spinal Interneurons
netParams.connParams['C_NP_AMPA->TrC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'TrC'},
'weight': cfg.C_TrC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_NP_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.C_EX_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_NP_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'SOM'},
'weight': cfg.C_EX_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['C_NP_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.C_EX_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_NP_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'CR'},
'weight': cfg.C_EX_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['C_NP_AMPA->DYN'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'DYN'},
'weight': cfg.C_DYN_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['C_NP_AMPA->ISLET'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'C_NP'},
'postConds': {'popLabel': 'ISLET'},
'weight': cfg.C_ISLET_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 10.0,
'loc': 0.5,
'synMech': 'AMPA'}
###################################################################################################################################
# Connectivity Betweeen Spinal Neurons (inh>ex, ex>ex, ex/inh>projection)
###################################################################################################################################
# TO ePKC NEURONS:
netParams.connParams['VGLUT3_AMPA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'PKC'},
'weight': cfg.VGLUT3_PKC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['VGLUT3_NMDA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'PKC'},
'weight': cfg.VGLUT3_PKC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['PV_GABA->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PV'},
'postConds': {'popLabel':'PKC'},
'weight': cfg.PV_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
netParams.connParams['PV_GLY->PKC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PV'},
'postConds': {'popLabel':'PKC'},
'weight': cfg.PV_GLY,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GLY'}
# TO eDOR NEURONS
netParams.connParams['PV_GABA->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PV'},
'postConds': {'popLabel':'DOR'},
'weight': cfg.PV_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
netParams.connParams['PV_GLY->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PV'},
'postConds': {'popLabel':'DOR'},
'weight': cfg.PV_GLY,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GLY'}
netParams.connParams['VGLUT3_AMPA->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'DOR'},
'weight': cfg.VGLUT3_PKC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['VGLUT3_NMDA->DOR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'DOR'},
'weight': cfg.VGLUT3_PKC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
# TO eTrC NEURONS
netParams.connParams['PKC_AMPA->TrC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PKC'},
'postConds': {'popLabel':'TrC'},
'weight': cfg.PKC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['ISLET_GABA->TrC'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'ISLET'},
'postConds': {'popLabel':'TrC'},
'weight': cfg.ISLET_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
# TO iISLET NEURONS
netParams.connParams['DYN_GABA->ISLET'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel':'ISLET'},
'weight': cfg.DYN_ISLET_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
# TO iDYN NEURONS
netParams.connParams['ISLET_GABA->DYN'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'ISLET'},
'postConds': {'popLabel':'DYN'},
'weight': cfg.ISLET_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
# TO eSOM NEURONS
netParams.connParams['DYN_GABA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.DYN_EX_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
netParams.connParams['DYN_GLY->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.DYN_EX_GLY,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GLY'}
netParams.connParams['TrC_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'TrC'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.TrC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['TrC_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'TrC'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.TrC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['PKC_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PKC'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.PKC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['PKC_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PKC'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.PKC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['VGLUT3_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.VGLUT3_SOM_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['VGLUT3_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'VGLUT3'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.VGLUT3_SOM_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['DOR_AMPA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DOR'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.DOR_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['DOR_NMDA->SOM'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DOR'},
'postConds': {'popLabel':'SOM'},
'weight': cfg.DOR_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
# TO eCR NEURONS
netParams.connParams['DYN_GABA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel':'CR'},
'weight': cfg.DYN_EX_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
netParams.connParams['DYN_GLY->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel':'CR'},
'weight': cfg.DYN_EX_GLY,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GLY'}
netParams.connParams['TrC_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'TrC'},
'postConds': {'popLabel':'CR'},
'weight': cfg.TrC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['TrC_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'TrC'},
'postConds': {'popLabel':'CR'},
'weight': cfg.TrC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['PKC_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PKC'},
'postConds': {'popLabel':'CR'},
'weight': cfg.PKC_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['PKC_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'PKC'},
'postConds': {'popLabel':'CR'},
'weight': cfg.PKC_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['DOR_AMPA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DOR'},
'postConds': {'popLabel':'CR'},
'weight': cfg.DOR_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['DOR_NMDA->CR'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DOR'},
'postConds': {'popLabel':'CR'},
'weight': cfg.DOR_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
# TO pNK1 NEURONS
netParams.connParams['SOM_AMPA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'SOM'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['SOM_NMDA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'SOM'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['SOM_NK1->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'SOM'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_NK1,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NK13'}
netParams.connParams['CR_AMPA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'CR'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_AMPA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'AMPA'}
netParams.connParams['CR_NMDA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'CR'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_NMDA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NMDA'}
netParams.connParams['CR_NK1->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'CR'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.EX_NK1_NK1,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'NK13'}
netParams.connParams['DYN_GABA->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.DYN_NK1_GABA,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GABA'}
netParams.connParams['DYN_GLY->NK1'] = {
'oneSynPerNetcon': True,
'preConds': {'popLabel': 'DYN'},
'postConds': {'popLabel': 'NK1'},
'weight': cfg.DYN_NK1_GLY,
'probability': 0.2,
'sec': 'dend',
'delay': 0.5,
'loc': 0.5,
'synMech': 'GLY'}