def __init__(self, associated_neurons, duration=duration, spiking_rate=spiking_rate):
"""
Creates a PoissonGroup connected to the associated_neurons
one-to-one. associated_neurons should come from the
corresponding context.
"""
self.weight = normalvariate_vec(1, 0.1, len(associated_neurons))
self.duration = duration
self.spiking_rate = spiking_rate
self.associated_neurons = associated_neurons
self.poisson_gen = PoissonGroup(len(associated_neurons), rates=0*Hz)
# plastic synapses
weight = normalvariate_vec(1, 0.1, len(associated_neurons))
self.poisson_con = Synapses(self.poisson_gen, associated_neurons, \
pre='Gexc_post += w', model='w : 1')
self.poisson_con.connect_one_to_one(self.poisson_gen, associated_neurons)
self.poisson_con.w[:,:] = weight
def __init__(self, name, associated_neurons, spiking_rate=spiking_rate, weight=None):
"""
Initialise a context, creating PoissonGroup connected to
associated_neurons. Plasticity possible.
"""
self.name = name
self.spiking_rate = spiking_rate
self.associated_neurons = associated_neurons
self.poisson_gen = PoissonGroup(len(associated_neurons), rates=0*Hz)
if weight == None:
# plastic synapses
weight = normalvariate_vec(1, 0.1, len(associated_neurons))
self.poisson_con = Synapses(self.poisson_gen, associated_neurons, \
pre='Gexc_post += w', model='w : 1')
self.poisson_con.connect_one_to_one(self.poisson_gen, associated_neurons)
self.poisson_con.w[:,:] = weight
else:
# static connections
self.poisson_con = IdentityConnection(self.poisson_gen, associated_neurons, \
'Gexc', weight=weight)
