def connectUsingSynChan(self, synName, prePath, post_path
, weight, threshold, delay
):
"""
Connect two compartments using SynChan
"""
postcomp = moose.Compartment(post_path)
# We usually try to reuse an existing SynChan - event based SynChans
# have an array of weights and delays and can represent multiple
# synapses i.e. a new element of the weights and delays array is
# created every time a 'synapse' message connects to the SynChan (from
# 'event' of spikegen) BUT for a graded synapse with a lookup table
# output connected to 'activation' message, not to 'synapse' message, we
# make a new synapse everytime ALSO for a saturating synapse i.e.
# KinSynChan, we always make a new synapse as KinSynChan is not meant to
# represent multiple synapses
libsyn = moose.SynChan(self.libraryPath+'/'+synName)
gradedchild = utils.get_child_Mstring(libsyn, 'graded')
# create a new synapse
if libsyn.className == 'KinSynChan' or gradedchild.value == 'True':
synNameFull = moose_methods.moosePath(synName
, utils.underscorize(prePath)
)
synObj = self.makeNewSynapse(synName, postcomp, synNameFull)
else:
# See debug/bugs for more details.
# NOTE: Change the debug/bugs to enable/disable this bug.
if bugs.BUG_NetworkML_500:
utils.dump("INFO"
, "See the code. There might be a bug here"
, frame = inspect.currentframe()
)
synNameFull = moose_methods.moosePath(synName
, utils.underscorize(prePath)
)
synObj = self.makeNewSynapse(synName, postcomp, synNameFull)
else: # If the above bug is fixed.
synNameFull = synName
if not moose.exists(post_path+'/'+synNameFull):
synObj = self.makeNewSynapse(synName, postcomp, synNameFull)
# wrap the synapse in this compartment
synPath = moose_methods.moosePath(post_path, synNameFull)
syn = moose.SynChan(synPath)
gradedchild = utils.get_child_Mstring(syn, 'graded')
# weights are set at the end according to whether the synapse is graded
# or event-based
# connect pre-comp Vm (if graded) OR spikegen/timetable (if event-based)
# to the synapse
# graded synapse
if gradedchild.value=='True':
table = moose.Table(syn.path+"/graded_table")
# always connect source to input - else 'cannot create message'
# error.
precomp = moose.Compartment(prePath)
self.connectWrapper(precomp, "VmOut", table, "msgInput")
# since there is no weight field for a graded synapse
# (no 'synapse' message connected),
# I set the Gbar to weight*Gbar
syn.Gbar = weight * syn.Gbar
# Event based synapse
else:
# synapse could be connected to spikegen at pre-compartment OR a
# file!
if 'file' not in prePath:
precomp = moose.Compartment(prePath)
if not moose.exists(prePath+'/IaF_spikegen'):
# if spikegen for this synapse doesn't exist in this
# compartment, create it spikegens for different synapse_types
# can have different thresholds
if not moose.exists(prePath+'/'+synName+'_spikegen'):
spikegen = moose.SpikeGen(prePath+'/'+synName+'_spikegen')
# spikegens for different synapse_types can have different
# thresholds
spikegen.threshold = threshold
# This ensures that spike is generated only on leading edge.
spikegen.edgeTriggered = 1
# usually events are raised at every time step that Vm >
# Threshold, can set either edgeTriggered as above or
# refractT
#spikegen.refractT = 0.25e-3
# wrap the spikegen in this compartment
spikegen = moose.SpikeGen(prePath+'/'+synName+'_spikegen')
else:
spikegen = moose.SpikeGen(prePath+'/IaF_spikegen')
# connect the spikegen to the synapse note that you need to use
# Synapse (auto-created) under SynChan to get/set weights ,
# addSpike-s etc. can get the Synapse element by
# moose.Synapse(syn.path+'/synapse') or syn.synapse Synpase is
# an array element, first add to it, to addSpike-s, get/set
# weights, etc.
syn.numSynapses += 1
m = self.connectSynapse(spikegen, syn)
else:
# if connected to a file, create a timetable,
# put in a field specifying the connected filenumbers to this segment,
# and leave it for simulation-time connection
## prePath is 'file[+<glomnum>]_<filenum1>[_<filenum2>...]' i.e. glomnum could be present
filesplit = prePath.split('+')
if len(filesplit) == 2:
glomsplit = filesplit[1].split('_', 1)
glomstr = '_'+glomsplit[0]
filenums = glomsplit[1]
else:
glomstr = ''
filenums = prePath.split('_', 1)[1]
tt_path = postcomp.path+'/'+synNameFull+glomstr+'_tt'
if not moose.exists(tt_path):
# if timetable for this synapse doesn't exist in this
# compartment, create it, and add the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
tt.addField('fileNumbers')
tt.setField('fileNumbers',filenums)
# Be careful to connect the timetable only once while
# creating it as below: note that you need to use Synapse
# (auto-created) under SynChan to get/set weights ,
# addSpike-s etc. can get the Synapse element by
# moose.Synapse(syn.path+'/synapse') or syn.synapse Synpase
# is an array element, first add to it, to addSpike-s,
# get/set weights, etc.
syn.numSynapses += 1
m = self.connectSynapse(spikegen, syn.synapse)
else:
# if it exists, append file number to the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
# append filenumbers from
# 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
filenums = moose_methods.moosePath(tt.getField('fileNumbers')
, filenums)
tt.setField('fileNumbers', filenums)
# syn.Gbar remains the same, but we play with the weight which is a
# factor to Gbar The delay and weight can be set only after
# connecting a spike event generator. delay and weight are arrays:
# multiple event messages can be connected to a single synapse first
# argument below is the array index, we connect to the latest
# synapse created above But KinSynChan ignores weight of the
# synapse, so set the Gbar for it
if libsyn.className == 'KinSynChan':
syn.Gbar = weight*syn.Gbar
else:
# note that you need to use Synapse (auto-created) under SynChan
# to get/set weights , addSpike-s etc. can get the Synpase
# element by moose.Synapse(syn.path+'/synapse') or syn.synapse
syn.synapse[-1].weight = weight
syn.synapse[-1].delay = delay # seconds
def connect(self, syn_name, pre_path, post_path, weight, threshold, delay):
postcomp = moose.Compartment(post_path)
## We usually try to reuse an existing SynChan & SynHandler -
## event based SynHandlers have an array of weights and delays and can represent multiple synapses,
## so a new element of the weights and delays array is created
## every time a 'synapse' message connects to the SynHandler (from 'event' of spikegen)
## BUT for a graded synapse with a lookup table output connected to 'activation' message,
## not to 'synapse' message, we make a new synapse everytime
## ALSO for a saturating synapse i.e. KinSynChan, we always make a new synapse
## as KinSynChan is not meant to represent multiple synapses
libsyn = moose.SynChan('/library/' + syn_name)
gradedchild = utils.get_child_Mstring(libsyn, 'graded')
if libsyn.className == 'KinSynChan' or gradedchild.value == 'True': # create a new synapse
syn_name_full = syn_name + '_' + utils.underscorize(pre_path)
make_new_synapse(syn_name, postcomp, syn_name_full,
self.nml_params)
else:
## if syn doesn't exist in this compartment, create it
syn_name_full = syn_name
if not moose.exists(post_path + '/' + syn_name_full):
make_new_synapse(syn_name, postcomp, syn_name_full,
self.nml_params)
## moose.element is a function that checks if path exists,
## and returns the correct object, here SynChan
syn = moose.element(
post_path + '/' +
syn_name_full) # wrap the SynChan in this compartment
synhandler = moose.element(post_path + '/' + syn_name_full +
'/handler') # wrap the SynHandler
gradedchild = utils.get_child_Mstring(syn, 'graded')
#### weights are set at the end according to whether the synapse is graded or event-based
#### If graded, connect pre-comp Vm to the table which is connected to SynChan's activation
#### If event-based, connect spikegen/timetable's spikeOut to Simple/STDP SynHandler's addSpike
## I rely on second term below not being evaluated if first term is None;
## otherwise None.value gives error.
if gradedchild is not None and gradedchild.value == 'True': # graded synapse
interpol = moose.element(syn.path + "/graded_table")
#### always connect source to input - else 'cannot create message' error.
precomp = moose.Compartment(pre_path)
moose.connect(precomp, "VmOut", interpol, "input")
try:
tau_table = moose.element(syn.path + '/tau_table')
tau_table_present = True
except ValueError:
tau_table_present = False
# if tau_table is not found, don't connect it
if tau_table_present:
moose.connect(precomp, 'VmOut', tau_table, 'input')
## since there is no weight field for a graded synapse
## (no 'synapse' message connected),
## I set the Gbar to weight*Gbar
syn.Gbar = weight * syn.Gbar
else: # Event based synapse
## synapse could be connected to either spikegen at pre-compartment OR to a file!
if 'file' not in pre_path:
## element() can return either Compartment() or IzhikevichNrn(),
## since it queries and wraps the actual object
precomp = moose.element(pre_path)
## if spikegen for this synapse doesn't exist in this compartment, create it
## spikegens for different synapse_types can have different thresholds
## but an integrate and fire spikegen supercedes all other spikegens
if 'IF' in precomp.className: # intfire LIF
spikegen = precomp # LIF has a spikeOut message
else:
if not moose.exists(pre_path + '/' + syn_name +
'_spikegen'):
## create new spikegen
spikegen = moose.SpikeGen(pre_path + '/' + syn_name +
'_spikegen')
## connect the compartment Vm to the spikegen
moose.connect(precomp, "VmOut", spikegen, "Vm")
## spikegens for different synapse_types can have different thresholds
spikegen.threshold = threshold
spikegen.edgeTriggered = 1 # This ensures that spike is generated only on leading edge.
## usually events are raised at every time step that Vm > Threshold,
## can set either edgeTriggered as above or refractT
#spikegen.refractT = 0.25e-3
## wrap the existing or newly created spikegen in this compartment
spikegen = moose.SpikeGen(pre_path + '/' + syn_name +
'_spikegen')
## connect the spikegen to the SynHandler
## note that you need to use Synapse (auto-created) under SynHandler
## to get/set weights , addSpike-s etc.
## wrap Synapse element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
synhandler.numSynapses += 1
## see Demos/snippets/synapse.py for an example of
## how to connect multiple SpikeGens to the same SynChan
m = moose.connect(spikegen, 'spikeOut', synhandler.synapse[-1],
'addSpike', 'Single')
else:
## if connected to a file, create a timetable,
## put in a field specifying the connected filenumbers to this segment,
## and leave it for simulation-time connection
## pre_path is 'file[+<glomnum>]_<filenum1>[_<filenum2>...]' i.e. glomnum could be present
## hack for my (Aditya's) OB model to use files in NeuroML, should not affect others
filesplit = pre_path.split('+')
if len(filesplit) == 2:
glomsplit = filesplit[1].split('_', 1)
glomstr = '_' + glomsplit[0]
filenums = glomsplit[1]
else:
glomstr = ''
filenums = pre_path.split('_', 1)[1]
tt_path = postcomp.path + '/' + syn_name_full + glomstr + '_tt'
if not moose.exists(tt_path):
## if timetable for this synapse doesn't exist in this compartment, create it,
## and add the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
tt_filenums = moose.Mstring(tt_path + '/fileNumbers')
tt_filenums.value = filenums
## Be careful to connect the timetable only once while creating it as below:
## note that you need to use Synapse (auto-created) under SynChan
## to get/set weights , addSpike-s etc.
## wrap Synapse element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
synhandler.numSynapses += 1
m = moose.connect(tt, "eventOut", synhandler.synapse[-1],
"addSpike", "Single")
else:
## if it exists, append file number to the field 'fileNumbers'
## append filenumbers from 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
tt_filenums = moose.Mstring(tt_path + '/fileNumbers')
tt_filenums.value += '_' + filenums
#### syn.Gbar remains the same, but we play with the weight which is a factor to Gbar
#### The delay and weight can be set only after connecting a spike event generator.
#### delay and weight are arrays: multiple event messages can be connected to a single synapse
## first argument below is the array index, we connect to the latest synapse created above
## But KinSynChan ignores weight of the synapse, so set the Gbar for it
if libsyn.className == 'KinSynChan':
syn.Gbar = weight * syn.Gbar
else:
## note that you need to use Synapse (auto-created) under SynHandler
## to get/set weights , addSpike-s etc.
## wrap Synpase element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
synhandler.synapse[-1].weight = weight
synhandler.synapse[-1].delay = delay # seconds
def connectUsingSynChan(self, synName, prePath, post_path, weight,
threshold, delay):
"""
Connect two compartments using SynChan
"""
postcomp = moose.Compartment(post_path)
# We usually try to reuse an existing SynChan - event based SynChans
# have an array of weights and delays and can represent multiple
# synapses i.e. a new element of the weights and delays array is
# created every time a 'synapse' message connects to the SynChan (from
# 'event' of spikegen) BUT for a graded synapse with a lookup table
# output connected to 'activation' message, not to 'synapse' message, we
# make a new synapse everytime ALSO for a saturating synapse i.e.
# KinSynChan, we always make a new synapse as KinSynChan is not meant to
# represent multiple synapses
libsyn = moose.SynChan(self.libraryPath + '/' + synName)
gradedchild = utils.get_child_Mstring(libsyn, 'graded')
# create a new synapse
if libsyn.className == 'KinSynChan' or gradedchild.value == 'True':
synNameFull = moose_methods.moosePath(synName,
utils.underscorize(prePath))
synObj = self.makeNewSynapse(synName, postcomp, synNameFull)
else:
# See debug/bugs for more details.
# NOTE: Change the debug/bugs to enable/disable this bug.
if bugs.BUG_NetworkML_500:
utils.dump("INFO",
"See the code. There might be a bug here",
frame=inspect.currentframe())
synNameFull = moose_methods.moosePath(
synName, utils.underscorize(prePath))
synObj = self.makeNewSynapse(synName, postcomp, synNameFull)
else: # If the above bug is fixed.
synNameFull = synName
if not moose.exists(post_path + '/' + synNameFull):
synObj = self.makeNewSynapse(synName, postcomp,
synNameFull)
# wrap the synapse in this compartment
synPath = moose_methods.moosePath(post_path, synNameFull)
syn = moose.SynChan(synPath)
gradedchild = utils.get_child_Mstring(syn, 'graded')
# weights are set at the end according to whether the synapse is graded
# or event-based
# connect pre-comp Vm (if graded) OR spikegen/timetable (if event-based)
# to the synapse
# graded synapse
if gradedchild.value == 'True':
table = moose.Table(syn.path + "/graded_table")
# always connect source to input - else 'cannot create message'
# error.
precomp = moose.Compartment(prePath)
self.connectWrapper(precomp, "VmOut", table, "msgInput")
# since there is no weight field for a graded synapse
# (no 'synapse' message connected),
# I set the Gbar to weight*Gbar
syn.Gbar = weight * syn.Gbar
# Event based synapse
else:
# synapse could be connected to spikegen at pre-compartment OR a
# file!
if 'file' not in prePath:
precomp = moose.Compartment(prePath)
if not moose.exists(prePath + '/IaF_spikegen'):
# if spikegen for this synapse doesn't exist in this
# compartment, create it spikegens for different synapse_types
# can have different thresholds
if not moose.exists(prePath + '/' + synName + '_spikegen'):
spikegen = moose.SpikeGen(prePath + '/' + synName +
'_spikegen')
# spikegens for different synapse_types can have different
# thresholds
spikegen.threshold = threshold
# This ensures that spike is generated only on leading edge.
spikegen.edgeTriggered = 1
# usually events are raised at every time step that Vm >
# Threshold, can set either edgeTriggered as above or
# refractT
#spikegen.refractT = 0.25e-3
# wrap the spikegen in this compartment
spikegen = moose.SpikeGen(prePath + '/' + synName +
'_spikegen')
else:
spikegen = moose.SpikeGen(prePath + '/IaF_spikegen')
# connect the spikegen to the synapse note that you need to use
# Synapse (auto-created) under SynChan to get/set weights ,
# addSpike-s etc. can get the Synapse element by
# moose.Synapse(syn.path+'/synapse') or syn.synapse Synpase is
# an array element, first add to it, to addSpike-s, get/set
# weights, etc.
syn.numSynapses += 1
m = self.connectSynapse(spikegen, syn)
else:
# if connected to a file, create a timetable,
# put in a field specifying the connected filenumbers to this segment,
# and leave it for simulation-time connection
## prePath is 'file[+<glomnum>]_<filenum1>[_<filenum2>...]' i.e. glomnum could be present
filesplit = prePath.split('+')
if len(filesplit) == 2:
glomsplit = filesplit[1].split('_', 1)
glomstr = '_' + glomsplit[0]
filenums = glomsplit[1]
else:
glomstr = ''
filenums = prePath.split('_', 1)[1]
tt_path = postcomp.path + '/' + synNameFull + glomstr + '_tt'
if not moose.exists(tt_path):
# if timetable for this synapse doesn't exist in this
# compartment, create it, and add the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
tt.addField('fileNumbers')
tt.setField('fileNumbers', filenums)
# Be careful to connect the timetable only once while
# creating it as below: note that you need to use Synapse
# (auto-created) under SynChan to get/set weights ,
# addSpike-s etc. can get the Synapse element by
# moose.Synapse(syn.path+'/synapse') or syn.synapse Synpase
# is an array element, first add to it, to addSpike-s,
# get/set weights, etc.
syn.numSynapses += 1
m = self.connectSynapse(spikegen, syn.synapse)
else:
# if it exists, append file number to the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
# append filenumbers from
# 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
filenums = moose_methods.moosePath(
tt.getField('fileNumbers'), filenums)
tt.setField('fileNumbers', filenums)
# syn.Gbar remains the same, but we play with the weight which is a
# factor to Gbar The delay and weight can be set only after
# connecting a spike event generator. delay and weight are arrays:
# multiple event messages can be connected to a single synapse first
# argument below is the array index, we connect to the latest
# synapse created above But KinSynChan ignores weight of the
# synapse, so set the Gbar for it
if libsyn.className == 'KinSynChan':
syn.Gbar = weight * syn.Gbar
else:
# note that you need to use Synapse (auto-created) under SynChan
# to get/set weights , addSpike-s etc. can get the Synpase
# element by moose.Synapse(syn.path+'/synapse') or syn.synapse
syn.synapse[-1].weight = weight
syn.synapse[-1].delay = delay # seconds
def connect(self, syn_name, pre_path, post_path, weight, threshold, delay):
postcomp = moose.Compartment(post_path)
## We usually try to reuse an existing SynChan & SynHandler -
## event based SynHandlers have an array of weights and delays and can represent multiple synapses,
## so a new element of the weights and delays array is created
## every time a 'synapse' message connects to the SynHandler (from 'event' of spikegen)
## BUT for a graded synapse with a lookup table output connected to 'activation' message,
## not to 'synapse' message, we make a new synapse everytime
## ALSO for a saturating synapse i.e. KinSynChan, we always make a new synapse
## as KinSynChan is not meant to represent multiple synapses
libsyn = moose.SynChan('/library/'+syn_name)
gradedchild = utils.get_child_Mstring(libsyn,'graded')
if libsyn.className == 'KinSynChan' or gradedchild.value == 'True': # create a new synapse
syn_name_full = syn_name+'_'+utils.underscorize(pre_path)
make_new_synapse(syn_name, postcomp, syn_name_full, self.nml_params)
else:
## if syn doesn't exist in this compartment, create it
syn_name_full = syn_name
if not moose.exists(post_path+'/'+syn_name_full):
make_new_synapse(syn_name, postcomp, syn_name_full, self.nml_params)
## moose.element is a function that checks if path exists,
## and returns the correct object, here SynChan
syn = moose.element(post_path+'/'+syn_name_full) # wrap the SynChan in this compartment
synhandler = moose.element(post_path+'/'+syn_name_full+'/handler') # wrap the SynHandler
gradedchild = utils.get_child_Mstring(syn,'graded')
#### weights are set at the end according to whether the synapse is graded or event-based
#### If graded, connect pre-comp Vm to the table which is connected to SynChan's activation
#### If event-based, connect spikegen/timetable's spikeOut to Simple/STDP SynHandler's addSpike
## I rely on second term below not being evaluated if first term is None;
## otherwise None.value gives error.
if gradedchild is not None and gradedchild.value=='True': # graded synapse
interpol = moose.element(syn.path+"/graded_table")
#### always connect source to input - else 'cannot create message' error.
precomp = moose.Compartment(pre_path)
moose.connect(precomp,"VmOut",interpol,"input")
try:
tau_table = moose.element(syn.path+'/tau_table')
tau_table_present = True
except ValueError:
tau_table_present = False
# if tau_table is not found, don't connect it
if tau_table_present:
moose.connect(precomp,'VmOut',tau_table,'input')
## since there is no weight field for a graded synapse
## (no 'synapse' message connected),
## I set the Gbar to weight*Gbar
syn.Gbar = weight*syn.Gbar
else: # Event based synapse
## synapse could be connected to either spikegen at pre-compartment OR to a file!
if 'file' not in pre_path:
## element() can return either Compartment() or IzhikevichNrn(),
## since it queries and wraps the actual object
precomp = moose.element(pre_path)
## if spikegen for this synapse doesn't exist in this compartment, create it
## spikegens for different synapse_types can have different thresholds
## but an integrate and fire spikegen supercedes all other spikegens
if 'IF' in precomp.className: # intfire LIF
spikegen = precomp # LIF has a spikeOut message
else:
if not moose.exists(pre_path+'/'+syn_name+'_spikegen'):
## create new spikegen
spikegen = moose.SpikeGen(pre_path+'/'+syn_name+'_spikegen')
## connect the compartment Vm to the spikegen
moose.connect(precomp,"VmOut",spikegen,"Vm")
## spikegens for different synapse_types can have different thresholds
spikegen.threshold = threshold
spikegen.edgeTriggered = 1 # This ensures that spike is generated only on leading edge.
## usually events are raised at every time step that Vm > Threshold,
## can set either edgeTriggered as above or refractT
#spikegen.refractT = 0.25e-3
## wrap the existing or newly created spikegen in this compartment
spikegen = moose.SpikeGen(pre_path+'/'+syn_name+'_spikegen')
## connect the spikegen to the SynHandler
## note that you need to use Synapse (auto-created) under SynHandler
## to get/set weights , addSpike-s etc.
## wrap Synapse element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
synhandler.numSynapses += 1
## see Demos/snippets/synapse.py for an example of
## how to connect multiple SpikeGens to the same SynChan
m = moose.connect(spikegen, 'spikeOut',
synhandler.synapse[-1], 'addSpike', 'Single')
else:
## if connected to a file, create a timetable,
## put in a field specifying the connected filenumbers to this segment,
## and leave it for simulation-time connection
## pre_path is 'file[+<glomnum>]_<filenum1>[_<filenum2>...]' i.e. glomnum could be present
## hack for my (Aditya's) OB model to use files in NeuroML, should not affect others
filesplit = pre_path.split('+')
if len(filesplit) == 2:
glomsplit = filesplit[1].split('_',1)
glomstr = '_'+glomsplit[0]
filenums = glomsplit[1]
else:
glomstr = ''
filenums = pre_path.split('_',1)[1]
tt_path = postcomp.path+'/'+syn_name_full+glomstr+'_tt'
if not moose.exists(tt_path):
## if timetable for this synapse doesn't exist in this compartment, create it,
## and add the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
tt_filenums = moose.Mstring(tt_path+'/fileNumbers')
tt_filenums.value = filenums
## Be careful to connect the timetable only once while creating it as below:
## note that you need to use Synapse (auto-created) under SynChan
## to get/set weights , addSpike-s etc.
## wrap Synapse element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
synhandler.numSynapses += 1
m = moose.connect(tt,"eventOut",synhandler.synapse[-1],"addSpike","Single")
else:
## if it exists, append file number to the field 'fileNumbers'
## append filenumbers from 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
tt_filenums = moose.Mstring(tt_path+'/fileNumbers')
tt_filenums.value += '_' + filenums
#### syn.Gbar remains the same, but we play with the weight which is a factor to Gbar
#### The delay and weight can be set only after connecting a spike event generator.
#### delay and weight are arrays: multiple event messages can be connected to a single synapse
## first argument below is the array index, we connect to the latest synapse created above
## But KinSynChan ignores weight of the synapse, so set the Gbar for it
if libsyn.className == 'KinSynChan':
syn.Gbar = weight*syn.Gbar
else:
## note that you need to use Synapse (auto-created) under SynHandler
## to get/set weights , addSpike-s etc.
## wrap Synpase element by moose.Synapse(synhandler.path+'/synapse') or synhandler.synapse
synhandler.synapse[-1].weight = weight
synhandler.synapse[-1].delay = delay # seconds
def connect(self, syn_name, pre_path, post_path, weight, threshold, delay):
postcomp = moose.Compartment(post_path)
## We usually try to reuse an existing SynChan -
## event based SynChans have an array of weights and delays and can represent multiple synapses i.e.
## a new element of the weights and delays array is created
## every time a 'synapse' message connects to the SynChan (from 'event' of spikegen)
## BUT for a graded synapse with a lookup table output connected to 'activation' message,
## not to 'synapse' message, we make a new synapse everytime
## ALSO for a saturating synapse i.e. KinSynChan, we always make a new synapse
## as KinSynChan is not meant to represent multiple synapses
libsyn = moose.SynChan('/library/'+syn_name)
gradedchild = utils.get_child_Mstring(libsyn,'graded')
if libsyn.className == 'KinSynChan' or gradedchild.value == 'True': # create a new synapse
syn_name_full = syn_name+'_'+utils.underscorize(pre_path)
self.make_new_synapse(syn_name, postcomp, syn_name_full)
else:
##### BUG BUG BUG in MOOSE:
##### Subhasis said addSpike below always adds to the first element in syn.synapse
##### So here, create a new SynChan everytime.
syn_name_full = syn_name+'_'+utils.underscorize(pre_path)
self.make_new_synapse(syn_name, postcomp, syn_name_full)
##### Once above bug is resolved in MOOSE, revert to below:
### if syn doesn't exist in this compartment, create it
#syn_name_full = syn_name
#if not moose.exists(post_path+'/'+syn_name_full):
# self.make_new_synapse(syn_name, postcomp, syn_name_full)
syn = moose.SynChan(post_path+'/'+syn_name_full) # wrap the synapse in this compartment
gradedchild = utils.get_child_Mstring(syn,'graded')
#### weights are set at the end according to whether the synapse is graded or event-based
#### connect pre-comp Vm (if graded) OR spikegen/timetable (if event-based) to the synapse
if gradedchild.value=='True': # graded synapse
table = moose.Table(syn.path+"/graded_table")
#### always connect source to input - else 'cannot create message' error.
precomp = moose.Compartment(pre_path)
moose.connect(precomp,"VmOut",table,"msgInput")
## since there is no weight field for a graded synapse
## (no 'synapse' message connected),
## I set the Gbar to weight*Gbar
syn.Gbar = weight*syn.Gbar
else: # Event based synapse
## synapse could be connected to spikegen at pre-compartment OR a file!
if 'file' not in pre_path:
precomp = moose.Compartment(pre_path)
## if spikegen for this synapse doesn't exist in this compartment, create it
## spikegens for different synapse_types can have different thresholds
if not moose.exists(pre_path+'/'+syn_name+'_spikegen'):
spikegen = moose.SpikeGen(pre_path+'/'+syn_name+'_spikegen')
## connect the compartment Vm to the spikegen
moose.connect(precomp,"VmOut",spikegen,"Vm")
## spikegens for different synapse_types can have different thresholds
spikegen.threshold = threshold
spikegen.edgeTriggered = 1 # This ensures that spike is generated only on leading edge.
#spikegen.refractT = 0.25e-3 ## usually events are raised at every time step that Vm > Threshold, can set either edgeTriggered as above or refractT
spikegen = moose.SpikeGen(pre_path+'/'+syn_name+'_spikegen') # wrap the spikegen in this compartment
## connect the spikegen to the synapse
## note that you need to use Synapse (auto-created) under SynChan
## to get/set weights , addSpike-s etc.
## can get the Synapse element by moose.Synapse(syn.path+'/synapse') or syn.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
syn.synapse.num += 1
##### BUG BUG BUG in MOOSE:
##### Subhasis said addSpike always adds to the first element in syn.synapse
##### Create a new synapse above everytime
moose.connect(spikegen,"event",syn.synapse[-1],"addSpike")
else:
# if connected to a file, create a timetable,
# put in a field specifying the connected filenumbers to this segment,
# and leave it for simulation-time connection
## pre_path is 'file[+<glomnum>]_<filenum1>[_<filenum2>...]' i.e. glomnum could be present
filesplit = pre_path.split('+')
if len(filesplit) == 2:
glomsplit = filesplit[1].split('_',1)
glomstr = '_'+glomsplit[0]
filenums = glomsplit[1]
else:
glomstr = ''
filenums = pre_path.split('_',1)[1]
tt_path = postcomp.path+'/'+syn_name_full+glomstr+'_tt'
if not moose.exists(tt_path):
# if timetable for this synapse doesn't exist in this compartment, create it,
# and add the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
tt.addField('fileNumbers')
tt.setField('fileNumbers',filenums)
# Be careful to connect the timetable only once while creating it as below:
## note that you need to use Synapse (auto-created) under SynChan
## to get/set weights , addSpike-s etc.
## can get the Synapse element by moose.Synapse(syn.path+'/synapse') or syn.synapse
## Synpase is an array element, first add to it, to addSpike-s, get/set weights, etc.
syn.synapse.num += 1
##### BUG BUG BUG in MOOSE:
##### Subhasis said addSpike always adds to the first element in syn.synapse
##### Create a new synapse above everytime
m = moose.connect(tt,"event",syn.synapse[-1],"addSpike")
else:
# if it exists, append file number to the field 'fileNumbers'
tt = moose.TimeTable(tt_path)
# append filenumbers from 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
filenums = tt.getField('fileNumbers') + '_' + filenums
tt.setField('fileNumbers',filenums)
#### syn.Gbar remains the same, but we play with the weight which is a factor to Gbar
#### The delay and weight can be set only after connecting a spike event generator.
#### delay and weight are arrays: multiple event messages can be connected to a single synapse
## first argument below is the array index, we connect to the latest synapse created above
## But KinSynChan ignores weight of the synapse, so set the Gbar for it
if libsyn.className == 'KinSynChan':
syn.Gbar = weight*syn.Gbar
else:
## note that you need to use Synapse (auto-created) under SynChan
## to get/set weights , addSpike-s etc.
## can get the Synpase element by moose.Synapse(syn.path+'/synapse') or syn.synapse
syn.synapse[-1].weight = weight
syn.synapse[-1].delay = delay # seconds
