Example: stopping (misc)ΒΆ
Network to demonstrate stopping a simulation during a run
Have a fully connected network of integrate and fire neurons with input fed by a group of Poisson neurons with a steadily increasing rate, want to determine the point in time at which the network of integrate and fire neurons switches from no firing to all neurons firing, so we have a network_operation called stop_condition that calls the stop() function if the monitored network firing rate is above a minimum threshold.
from brian import *
clk = Clock()
Vr = 0 * mV
El = 0 * mV
Vt = 10 * mV
tau = 10 * ms
weight = 0.2 * mV
duration = 100 * msecond
max_input_rate = 10000 * Hz
num_input_neurons = 1000
input_connection_p = 0.1
rate_per_neuron = max_input_rate / (num_input_neurons * input_connection_p)
P = PoissonGroup(num_input_neurons, lambda t: rate_per_neuron * (t / duration))
G = NeuronGroup(1000, model='dV/dt=-(V-El)/tau : volt', threshold=Vt, reset=Vr)
G.V = Vr + (Vt - Vr) * rand(len(G))
CPG = Connection(P, G, weight=weight, sparseness=input_connection_p)
CGG = Connection(G, G, weight=weight)
MP = PopulationRateMonitor(G, bin=1 * ms)
@network_operation
def stop_condition():
if MP.rate[-1] * Hz > 10 * Hz:
stop()
run(duration)
print "Reached population rate>10 Hz by time", clk.t, "+/- 1 ms."