def plasticity_test(model, syncomp=None, syn_pop=None, stimtimes=None):
syntype = model.CaPlasticityParams.Plas_syn.Name
if stimtimes is None:
stimtimes = [.1, .12]
if syncomp is None:
path = model.neurons[list(model.neurons)[0]].path
syncomp = moose.wildcardFind(path + '/##/' + syntype +
'[ISA=SynChan]')[0].parent
plast = {}
stimtab = {}
if model.calYN and model.plasYN:
neu = moose.Neutral('/input')
for neurtype in util.neurontypes(model.param_cond):
stimtab[neurtype] = moose.TimeTable('%s/TimTab%s' %
(neu.path, neurtype))
stimtab[neurtype].vector = stimtimes
print('**** plasticity test ********', syntype, neurtype, syncomp)
#synchan=moose.element(syn_pop[neurtype][syntype][syncomp])
synchan = moose.element(syncomp.path + '/' + syntype)
sh = synchan.children[0]
log.info('Synapse added to {.path}', synchan)
connect.synconn(sh, 0, stimtab[neurtype], model.param_syn)
###Synaptic Plasticity
plast[neurtype] = plasticity.plasticity2(
synchan, model.CaPlasticityParams.Plas_syn)
return plast, stimtab
def HookUpDend(model,dendrite,container):
if model.Stimulation.StimLoc.spine_density>0:
num_spines,synchans=enumerate_spine_synchans(model,dendrite)
tt_root_name=container.path+'/TimTab'+dendrite.name
else:
num_spines=1
synchans={dendrite.name:[dendrite.path+'/'+model.Stimulation.StimLoc.syntype]}
tt_root_name=container.path+'/TimTab'
print('HookUpDend, syn:', synchans,num_spines)
if getattr(model.Stimulation.StimLoc,'weight',None):
weight=model.Stimulation.StimLoc.weight
else:
weight=1
time_tables = MakeTimeTables(model.Stimulation,num_spines)
freq=model.Stimulation.Paradigm.f_pulse
print('HookUpDend, tt:', time_tables)
stimtab = {}
stim_syn = {}
for spine in time_tables:
stimtab[spine] = moose.TimeTable('%s_%s_%s' % (tt_root_name,str(spine),str(int(freq))))
stimtab[spine].vector = np.array(time_tables[spine])
print('HUD,stimtab {} '.format(stimtab))
for synchan in synchans[spine]:
synapse = moose.element(synchan+'/SH')
print('**** ready to connect',synapse.path,stimtab[spine].vector,model.Stimulation.Paradigm.name,model.Stimulation.StimLoc.stim_dendrites,'weight=',weight)
#connect.plain_synconn(synapse,stimtab[spine],0)
connect.synconn(synapse.path,0,stimtab[spine],model.param_syn,weight=weight)
stim_syn[synchan]=(stimtab[spine],synapse,synapse.synapse.num-1)
return stimtab,synchans,stim_syn
def plasticity_test(model, syncomp=None, syn_pop=None, stimtimes=None):
syntype = model.CaPlasticityParams.Plas_syn.Name
if stimtimes is None:
stimtimes = [.1,.12]
if syncomp is None:
path = model.neurons[list(model.neurons)[0]].path
syncomp = moose.wildcardFind(path+'/##/'+syntype+'[ISA=SynChan]')[0].parent
plast={}
stimtab={}
if model.calYN and model.plasYN:
neu = moose.Neutral('/input')
for neurtype in util.neurontypes(model.param_cond):
stimtab[neurtype]=moose.TimeTable('%s/TimTab%s' % (neu.path, neurtype))
stimtab[neurtype].vector = stimtimes
print('**** plasticity test ********',syntype,neurtype,syncomp)
#synchan=moose.element(syn_pop[neurtype][syntype][syncomp])
synchan=moose.element(syncomp.path+'/'+syntype)
sh = synchan.children[0]
log.info('Synapse added to {.path}', synchan)
connect.synconn(sh,0,stimtab[neurtype], model.param_syn)
###Synaptic Plasticity
plast[neurtype] = plasticity.plasticity2(synchan,model.CaPlasticityParams.Plas_syn)
return plast, stimtab
def HookUpDend(model,dendrite,container):
if model.Stimulation.StimLoc.spine_density>0:
num_spines,synchans=enumerate_spine_synchans(model,dendrite)
tt_root_name=container.path+'/TimTab'+dendrite.name
else:
num_spines=1
synchans={dendrite.name:[dendrite.path+'/'+model.Stimulation.StimLoc.syntype]}
tt_root_name=container.path+'/TimTab'
print('HookUpDend, syn:', synchans,num_spines)
if getattr(model.Stimulation.StimLoc,'weight',None):
weight=model.Stimulation.StimLoc.weight
else:
weight=1
time_tables = MakeTimeTables(model.Stimulation,num_spines)
freq=model.Stimulation.Paradigm.f_pulse
print('HookUpDend, tt:', time_tables)
stimtab = {}
stim_syn = {}
for spine in time_tables:
stimtab[spine] = moose.TimeTable('%s_%s_%s' % (tt_root_name,str(spine),str(int(freq))))
stimtab[spine].vector = np.array(time_tables[spine])
stimtab[spine].tick=7#moose.element(synchans[spine][0]).tick
print('HUD,stimtab {} '.format(stimtab),'tick',stimtab[spine].tick)
for synchan in synchans[spine]:
synapse = moose.element(synchan+'/SH')
print('**** ready to connect',synapse.path,stimtab[spine].vector,model.Stimulation.Paradigm.name,model.Stimulation.StimLoc.stim_dendrites,'weight=',weight)
#connect.plain_synconn(synapse,stimtab[spine],0)
connect.synconn(synapse.path,0,stimtab[spine],model.param_syn,weight=weight)
stim_syn[synchan]=(stimtab[spine],synapse,synapse.synapse.num-1)
return stimtab,synchans,stim_syn
def createTimeTables(inputList,
model,
n_per_syn=1,
start_time=0.05,
freq=500.0):
from moose_nerp.prototypes import connect
num = len(inputList)
for i, input in enumerate(inputList):
sh = moose.element(input.path + '/SH')
tt = moose.TimeTable(input.path + '/tt')
tt.vector = [
start_time + i * 1. / freq + j * num * 1. / freq
for j in range(n_per_syn)
]
#print(tt.vector)
connect.synconn(sh.path, False, tt, model.param_syn, mindel=0)
def plasticity_test(model, syncomp, syn_pop, stimtimes):
plast = {}
stimtab = {}
if model.calYN and model.plasYN:
neu = moose.Neutral('/input')
for neurtype in model.neurontypes():
stimtab[neurtype] = moose.TimeTable('%s/TimTab%s' %
(neu.path, neurtype))
stimtab[neurtype].vector = stimtimes
syntype = model.CaPlasticityParams.Plas_syn.Name
print(syntype, neurtype, syncomp)
synchan = moose.element(syn_pop[neurtype][syntype][syncomp])
log.info('Synapse added to {.path}', synchan)
connect.synconn(synchan, 0, stimtab[neurtype], model.param_syn)
###Synaptic Plasticity
plast[neurtype] = plasticity.plasticity(
synchan, model.CaPlasticityParams.Plas_syn)
return plast, stimtab