def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
lsyn = h.int2pyr(sec_x, sec=sec_id)
if syn_params.get('AlphaTmax_gaba'):
lsyn.AlphaTmax_gaba = float(syn_params['AlphaTmax_gaba']) # par.x(21)
if syn_params.get('Beta_gaba'):
lsyn.Beta_gaba = float(syn_params['Beta_gaba']) # par.x(22)
if syn_params.get('Cdur_gaba'):
lsyn.Cdur_gaba = float(syn_params['Cdur_gaba']) # par.x(23)
if syn_params.get('gbar_gaba'):
lsyn.gbar_gaba = float(syn_params['gbar_gaba']) # par.x(24)
if syn_params.get('Erev_gaba'):
lsyn.Erev_gaba = float(syn_params['Erev_gaba']) # par.x(16)
if syn_params.get('initW'):
m = 1
s = 0.02
mean = np.log(m) - 0.5 * np.log((s/m)**2+1)
std = np.sqrt(np.log((s/m)**2 + 1))
lsyn.initW = float(np.random.lognormal(mean,std)) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
if syn_params.get('Wmax'):
lsyn.Wmax = float(syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
lsyn = h.int2pyr(sec_x, sec=sec_id)
if syn_params.get('AlphaTmax_ampa'):
lsyn.AlphaTmax_ampa = float(syn_params['AlphaTmax_ampa']) # par.x(21)
if syn_params.get('Beta_ampa'):
lsyn.Beta_ampa = float(syn_params['Beta_ampa']) # par.x(22)
if syn_params.get('Cdur_ampa'):
lsyn.Cdur_ampa = float(syn_params['Cdur_ampa']) # par.x(23)
if syn_params.get('gbar_ampa'):
lsyn.gbar_ampa = float(syn_params['gbar_ampa']) # par.x(24)
if syn_params.get('Erev_ampa'):
lsyn.Erev_ampa = float(syn_params['Erev_ampa']) # par.x(16)
if syn_params.get('AlphaTmax_nmda'):
lsyn.AlphaTmax_nmda = float(syn_params['AlphaTmax_nmda']) # par.x(25)
if syn_params.get('Beta_nmda'):
lsyn.Beta_nmda = float(syn_params['Beta_nmda']) # par.x(26)
if syn_params.get('Cdur_nmda'):
lsyn.Cdur_nmda = float(syn_params['Cdur_nmda']) # par.x(27)
if syn_params.get('gbar_nmda'):
lsyn.gbar_nmda = float(syn_params['gbar_nmda']) # par.x(28)
if syn_params.get('Erev_nmda'):
lsyn.Erev_nmda = float(syn_params['Erev_nmda']) # par.x(16)
if syn_params.get('initW'):
#lsyn.initW = float(syn_params['initW']) * random.uniform(0.5,1.0) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
lsyn.initW = float(pyrWeight)
if syn_params.get('Wmax'):
lsyn.Wmax = float(
syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(
syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
lsyn = h.int2pyr(sec_x, sec=sec_id)
h.distance(sec=sec_id.cell().soma[0])
dist = h.distance(sec_id(sec_x))
fullsecname = sec_id.name()
sec_type = fullsecname.split(".")[1][:4]
#sec_id = int(fullsecname.split("[")[-1].split("]")[0])
#Assigns random generator of release probability.
r = h.Random()
r.MCellRan4()
r.uniform(0, 1)
lsyn.setRandObjRef(r)
generators.append(r)
#Assigns release probabilty and conductance based on location of the synapse.
if sec_type == "soma":
lsyn.P_0 = np.clip(np.random.normal(0.877, 0.052), 0, 1)
lsyn.initW = 44.75 #62.31
if sec_type == "dend":
if dist <= 50:
lsyn.P_0 = np.clip(np.random.normal(0.877, 0.052), 0, 1)
lsyn.initW = 54.75 #62.31
else:
lsyn.P_0 = np.clip(np.random.normal(0.72, 0.1), 0, 1)
lsyn.initW = 42.6 #66.6
if sec_type == "apic":
lsyn.P_0 = np.clip(np.random.normal(0.3, 0.08), 0, 1)
lsyn.initW = 118.7 #168.7
#Short Term Plasticity
#######################
# SOM+
# d1: 0.96, tauD1: 40
# PV+
# d1: 0.6, tauD1: 50
#######################
#if sec_type == "soma":
# #PV+
# lsyn.d1 = 0.6
# lsyn.tauD1 = 50
#if sec_type == "dend":
# if dist <= 50:
# #PV+
# lsyn.d1 = 0.6
# lsyn.tauD1 = 50
# else:
# #SOM+
# lsyn.d1 = 0.96
# lsyn.tauD1 = 40
#if sec_type == "apic":
# #SOM+
# lsyn.d1 = 0.96
# lsyn.tauD1 = 40
if syn_params.get('AlphaTmax_ampa'):
lsyn.AlphaTmax_ampa = float(syn_params['AlphaTmax_ampa']) # par.x(21)
if syn_params.get('Beta_ampa'):
lsyn.Beta_ampa = float(syn_params['Beta_ampa']) # par.x(22)
if syn_params.get('Cdur_ampa'):
lsyn.Cdur_ampa = float(syn_params['Cdur_ampa']) # par.x(23)
if syn_params.get('gbar_ampa'):
lsyn.gbar_ampa = float(syn_params['gbar_ampa']) # par.x(24)
if syn_params.get('Erev_ampa'):
lsyn.Erev_ampa = float(syn_params['Erev_ampa']) # par.x(16)
if syn_params.get('AlphaTmax_nmda'):
lsyn.AlphaTmax_nmda = float(syn_params['AlphaTmax_nmda']) # par.x(25)
if syn_params.get('Beta_nmda'):
lsyn.Beta_nmda = float(syn_params['Beta_nmda']) # par.x(26)
if syn_params.get('Cdur_nmda'):
lsyn.Cdur_nmda = float(syn_params['Cdur_nmda']) # par.x(27)
if syn_params.get('gbar_nmda'):
lsyn.gbar_nmda = float(syn_params['gbar_nmda']) # par.x(28)
if syn_params.get('Erev_nmda'):
lsyn.Erev_nmda = float(syn_params['Erev_nmda']) # par.x(16)
# if syn_params.get('initW'):
# #lsyn.initW = float(syn_params['initW']) * random.uniform(0.5,1.0) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
# lsyn.initW = 3*float(max(np.random.normal(36, 18), 0.01))#2 * float(np.random.normal(12, np.sqrt(2)))#float(pyrWeight)
if syn_params.get('Wmax'):
lsyn.Wmax = float(
syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(
syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
# trg_cell_nid = int(str(sec_id).split("[")[1].split("]")[0])
# # if trg_cell_nid > 0:
# # import pdb; pdb.set_trace()
# if trg_cell_nid in weight_means["inh"].keys():
# mean_weight = weight_means["inh"][trg_cell_nid]
# else:
# weight_means["inh"][trg_cell_nid] = mean_weight = np.random.uniform(3.171729 - 1.5, 3.171729 + 0.1)
lsyn = h.int2pyr(sec_x, sec=sec_id)
#Assigns random generator of release probability.
r = h.Random()
r.MCellRan4()
r.uniform(0,1)
lsyn.setRandObjRef(r)
generators.append(r)
h.distance(sec=sec_id.cell().soma[0])
dist = h.distance(sec_id(sec_x))
fullsecname = sec_id.name()
sec_type = fullsecname.split(".")[1][:4]
#######################
# SOM+
# d1: 0.96, tauD1: 40
# PV+
# d1: 0.6, tauD1: 50
#######################
# if sec_type == "soma":
# #PV+
# lsyn.d1 = 0.6
# lsyn.tauD1 = 50
# if sec_type == "dend":
# if dist <= 50:
# #PV+
# lsyn.d1 = 0.6
# lsyn.tauD1 = 50
# else:
# #SOM+
# lsyn.d1 = 0.96
# lsyn.tauD1 = 40
# if sec_type == "apic":
# #SOM+
# lsyn.d1 = 0.96
# lsyn.tauD1 = 40
if syn_params.get('AlphaTmax_ampa'):
lsyn.AlphaTmax_ampa = float(syn_params['AlphaTmax_ampa']) # par.x(21)
if syn_params.get('Beta_ampa'):
lsyn.Beta_ampa = float(syn_params['Beta_ampa']) # par.x(22)
if syn_params.get('Cdur_ampa'):
lsyn.Cdur_ampa = float(syn_params['Cdur_ampa']) # par.x(23)
if syn_params.get('gbar_ampa'):
lsyn.gbar_ampa = float(syn_params['gbar_ampa']) # par.x(24)
if syn_params.get('Erev_ampa'):
lsyn.Erev_ampa = float(syn_params['Erev_ampa']) # par.x(16)
if syn_params.get('AlphaTmax_nmda'):
lsyn.AlphaTmax_nmda = float(syn_params['AlphaTmax_nmda']) # par.x(25)
if syn_params.get('Beta_nmda'):
lsyn.Beta_nmda = float(syn_params['Beta_nmda']) # par.x(26)
if syn_params.get('Cdur_nmda'):
lsyn.Cdur_nmda = float(syn_params['Cdur_nmda']) # par.x(27)
if syn_params.get('gbar_nmda'):
lsyn.gbar_nmda = float(syn_params['gbar_nmda']) # par.x(28)
if syn_params.get('Erev_nmda'):
lsyn.Erev_nmda = float(syn_params['Erev_nmda']) # par.x(16)
if syn_params.get('initW'):
#lsyn.initW = float(syn_params['initW']) * random.uniform(0.5,1.0) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
#lsyn.initW = float(min(lognormal(0.11, 0.05), 5) * scale)
lsyn.initW = 12#float(min(lognormal(0.4, 0.09), 5) * scale)
#float(lognormal(3.171729, 0.5173616067) * scale * 20)
#lsyn.initW = float(lognormal(mean_weight, 0.5173616067) * scale)
#lsyn.initW = min(float(lognormal(mean_weight, 1)), 11) * scale
#lsyn.initW = 3.171729*10
if syn_params.get('Wmax'):
lsyn.Wmax = float(syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
lsyn = h.int2pyr(sec_x, sec=sec_id)
h.distance(sec=sec_id.cell().soma[0])
dist = h.distance(sec_id(sec_x))
fullsecname = sec_id.name()
sec_type = fullsecname.split(".")[1][:4]
#sec_id = int(fullsecname.split("[")[-1].split("]")[0])
#Assigns random generator of release probability.
r = h.Random()
r.MCellRan4()
r.uniform(0, 1)
lsyn.setRandObjRef(r)
generators.append(r)
#lsyn.P_0 = np_gen.uniform(0.16,0.9)#np.random.uniform(0.16, 0.9)
if sec_type == "soma":
lsyn.P_0 = max(np.random.normal(0.877, 0.052), 0)
if sec_type == "dend":
if dist <= 50:
lsyn.P_0 = max(np.random.normal(0.877, 0.052), 0)
else:
lsyn.P_0 = max(np.random.normal(0.72, 0.1), 0)
if sec_type == "apic":
lsyn.P_0 = max(np.random.normal(0.3, 0.08), 0)
if syn_params.get('AlphaTmax_ampa'):
lsyn.AlphaTmax_ampa = float(syn_params['AlphaTmax_ampa']) # par.x(21)
if syn_params.get('Beta_ampa'):
lsyn.Beta_ampa = float(syn_params['Beta_ampa']) # par.x(22)
if syn_params.get('Cdur_ampa'):
lsyn.Cdur_ampa = float(syn_params['Cdur_ampa']) # par.x(23)
if syn_params.get('gbar_ampa'):
lsyn.gbar_ampa = float(syn_params['gbar_ampa']) # par.x(24)
if syn_params.get('Erev_ampa'):
lsyn.Erev_ampa = float(syn_params['Erev_ampa']) # par.x(16)
if syn_params.get('AlphaTmax_nmda'):
lsyn.AlphaTmax_nmda = float(syn_params['AlphaTmax_nmda']) # par.x(25)
if syn_params.get('Beta_nmda'):
lsyn.Beta_nmda = float(syn_params['Beta_nmda']) # par.x(26)
if syn_params.get('Cdur_nmda'):
lsyn.Cdur_nmda = float(syn_params['Cdur_nmda']) # par.x(27)
if syn_params.get('gbar_nmda'):
lsyn.gbar_nmda = float(syn_params['gbar_nmda']) # par.x(28)
if syn_params.get('Erev_nmda'):
lsyn.Erev_nmda = float(syn_params['Erev_nmda']) # par.x(16)
if syn_params.get('initW'):
#lsyn.initW = float(syn_params['initW']) * random.uniform(0.5,1.0) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
lsyn.initW = float(lognormal(pyrWeight_m,
pyrWeight_s)) #float(pyrWeight)
if syn_params.get('Wmax'):
lsyn.Wmax = float(
syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(
syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
def Int2Pyr(syn_params, sec_x, sec_id):
"""Create a int2pyr synapse
:param syn_params: parameters of a synapse
:param sec_x: normalized distance along the section
:param sec_id: target section
:return: NEURON synapse object
"""
trg_cell_nid = int(str(sec_id).split("[")[1].split("]")[0])
# if trg_cell_nid > 0:
# import pdb; pdb.set_trace()
if trg_cell_nid in weight_means["inh"].keys():
mean_weight = weight_means["inh"][trg_cell_nid]
else:
weight_means["inh"][trg_cell_nid] = mean_weight = np.random.uniform(
0.2, 0.35)
lsyn = h.int2pyr(sec_x, sec=sec_id)
if syn_params.get('AlphaTmax_ampa'):
lsyn.AlphaTmax_ampa = float(syn_params['AlphaTmax_ampa']) # par.x(21)
if syn_params.get('Beta_ampa'):
lsyn.Beta_ampa = float(syn_params['Beta_ampa']) # par.x(22)
if syn_params.get('Cdur_ampa'):
lsyn.Cdur_ampa = float(syn_params['Cdur_ampa']) # par.x(23)
if syn_params.get('gbar_ampa'):
lsyn.gbar_ampa = float(syn_params['gbar_ampa']) # par.x(24)
if syn_params.get('Erev_ampa'):
lsyn.Erev_ampa = float(syn_params['Erev_ampa']) # par.x(16)
if syn_params.get('AlphaTmax_nmda'):
lsyn.AlphaTmax_nmda = float(syn_params['AlphaTmax_nmda']) # par.x(25)
if syn_params.get('Beta_nmda'):
lsyn.Beta_nmda = float(syn_params['Beta_nmda']) # par.x(26)
if syn_params.get('Cdur_nmda'):
lsyn.Cdur_nmda = float(syn_params['Cdur_nmda']) # par.x(27)
if syn_params.get('gbar_nmda'):
lsyn.gbar_nmda = float(syn_params['gbar_nmda']) # par.x(28)
if syn_params.get('Erev_nmda'):
lsyn.Erev_nmda = float(syn_params['Erev_nmda']) # par.x(16)
if syn_params.get('initW'):
#lsyn.initW = float(syn_params['initW']) * random.uniform(0.5,1.0) # par.x(0) * rC.uniform(0.5,1.0)//rand.normal(0.5,1.5) //`rand.repick()
lsyn.initW = float(min(lognormal(mean_weight, 0.1), 5) * scale)
#float(lognormal(3.171729, 0.5173616067) * scale * 20)
#lsyn.initW = float(lognormal(mean_weight, 0.5173616067) * scale)
#lsyn.initW = min(float(lognormal(mean_weight, 1)), 11) * scale
#lsyn.initW = 3.171729*10
if syn_params.get('Wmax'):
lsyn.Wmax = float(
syn_params['Wmax']) * lsyn.initW # par.x(1) * lsyn.initW
if syn_params.get('Wmin'):
lsyn.Wmin = float(
syn_params['Wmin']) * lsyn.initW # par.x(2) * lsyn.initW
#delay = float(syn_params['initW']) # par.x(3) + delayDistance
#lcon = new NetCon(&v(0.5), lsyn, 0, delay, 1)
if syn_params.get('lambda1'):
lsyn.lambda1 = float(syn_params['lambda1']) # par.x(6)
if syn_params.get('lambda2'):
lsyn.lambda2 = float(syn_params['lambda2']) # par.x(7)
if syn_params.get('threshold1'):
lsyn.threshold1 = float(syn_params['threshold1']) # par.x(8)
if syn_params.get('threshold2'):
lsyn.threshold2 = float(syn_params['threshold2']) # par.x(9)
if syn_params.get('tauD1'):
lsyn.tauD1 = float(syn_params['tauD1']) # par.x(10)
if syn_params.get('d1'):
lsyn.d1 = float(syn_params['d1']) # par.x(11)
if syn_params.get('tauD2'):
lsyn.tauD2 = float(syn_params['tauD2']) # par.x(12)
if syn_params.get('d2'):
lsyn.d2 = float(syn_params['d2']) # par.x(13)
if syn_params.get('tauF'):
lsyn.tauF = float(syn_params['tauF']) # par.x(14)
if syn_params.get('f'):
lsyn.f = float(syn_params['f']) # par.x(15)
return lsyn
