# Author Michele Mattioni
# Thu Mar 19 10:40:51 GMT 2009
from neuron import h
class Synapse(object):
"""Synapse object class. Usually created in the spine"""
def __init__(self, chan_type, section, position=0.5):
self.chan_type = chan_type
self.section = section
self.chan = self.create_channel(chan_type, position)
self.vecs = {} # Dictionary to record all the vectors
self.weight = [[],[]]
self.stims = []
def create_channel(self, chan_type, position):
"""Create the NMDA or AMPA channel"""
if chan_type == 'ampa':
chan = h.AMPA(position, sec = self.section)
elif chan_type == 'nmda':
chan = h.NMDA(position, sec = self.section)
elif chan_type == 'gaba':
chan = h.GABA(position, sec = self.section)
return chan
def create_stimul(self, array_inputs, neuron_time_resolution):
"""Create a netStim object and assign it to the synapse together with
a NetConnect one.
:params
array_inputs - Array which holds the inputs time
neuron_time_resolution - resolution of the vectors when saving results"""
# Removing duplicates
array_inputs = list(set(array_inputs))
# Ordering the inputs
array_inputs.sort()
print "Creating vecStim for syn Channel %s, %s Array input: %s" %(self.chan,
self.chan_type,
array_inputs)
vecStim = h.VecStim()
self.vec = h.Vector(array_inputs)
vecStim.play(self.vec)
self.vecStim = vecStim
# NetCon obj
netCon = h.NetCon(vecStim, self.chan, 0, 0, 1) #Setting the weight
#netCon.weight[0] = 1
self.netCon = netCon # assign the point to the class as attribute
#for thread safe reason
self.netCon.delay = 1
self.createVec(neuron_time_resolution) # Recording the synapse
def createVec(self, neuron_time_resolution):
"""Create the vector to measure the activity of the synapse
:param syn - The synapse to record
Remember: The weight on the synapse is a special one and holds the time
(from Neuron) and the corrispondent value.
"""
# Record the stimuls
# The NetCon needs a record allocated to use to record the stuff
stimul = "stimul_" + self.chan_type
self.vecs[stimul] = h.Vector()
self.netCon.record(self.vecs[stimul])
# Record the current into the synaptic chan
i = "i_" + self.chan_type
g = "g_" + self.chan_type
itmp = "itmp_" + self.chan_type
scale = "scale_" + self.chan_type
scale_ref = "scale_ref_" + self.chan_type
self.vecs[i] = h.Vector()
self.vecs[g] = h.Vector()
self.vecs[itmp] = h.Vector()
self.vecs[scale] = h.Vector()
if neuron_time_resolution is None:
self.vecs[i].record(self.chan, self.chan._ref_i)
self.vecs[g].record(self.chan, self.chan._ref_g)
self.vecs[itmp].record(self.chan, self.chan._ref_itmp)
self.vecs[scale].record(self.chan, self.chan._ref_scale)
else:
self.vecs[i].record(self.chan, self.chan._ref_i, neuron_time_resolution)
self.vecs[g].record(self.chan, self.chan._ref_g, neuron_time_resolution)
self.vecs[itmp].record(self.chan, self.chan._ref_itmp, neuron_time_resolution)
self.vecs[scale].record(self.chan, self.chan._ref_scale, neuron_time_resolution)
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