Example: STDP2 (plasticity)

Spike-timing dependent plasticity Adapted from Song, Miller and Abbott (2000), Song and Abbott (2001) and van Rossum et al (2000).

This simulation takes a long time!

from brian import *
from time import time

N = 1000
taum = 10 * ms
tau_pre = 20 * ms
tau_post = tau_pre
Ee = 0 * mV
vt = -54 * mV
vr = -60 * mV
El = -74 * mV
taue = 5 * ms
gmax = 0.01
F = 15 * Hz
dA_pre = .01
dA_post = -dA_pre * tau_pre / tau_post * 2.5

eqs_neurons = '''
dv/dt=(ge*(Ee-vr)+El-v)/taum : volt   # the synaptic current is linearized
dge/dt=-ge/taue : 1
'''

input = PoissonGroup(N, rates=F)
neurons = NeuronGroup(1, model=eqs_neurons, threshold=vt, reset=vr)
synapses = Connection(input, neurons, 'ge', weight=rand(len(input), len(neurons)) * gmax,
                    structure='dense')
neurons.v = vr

stdp = ExponentialSTDP(synapses, tau_pre, tau_post, dA_pre, dA_post, wmax=gmax, update='mixed')

rate = PopulationRateMonitor(neurons)

start_time = time()
run(100 * second, report='text')
print "Simulation time:", time() - start_time

subplot(311)
plot(rate.times / second, rate.smooth_rate(100 * ms))
subplot(312)
plot(synapses.W.todense() / gmax, '.')
subplot(313)
hist(synapses.W.todense() / gmax, 20)
show()