#!/usr/bin/env python
'''
Phase locking in leaky integrate-and-fire model
-----------------------------------------------
Fig. 2A from:
Brette R (2004). Dynamics of one-dimensional spiking neuron models.
J Math Biol 48(1): 38-56.

This shows the phase-locking structure of a LIF driven by a sinusoidal
current. When the current crosses the threshold (a<3), the model
almost always phase locks (in a measure-theoretical sense).
'''
from brian2 import *

# defaultclock.dt = 0.01*ms  # for a more precise picture
N = 2000
tau = 100*ms
freq = 1/tau

eqs = '''
dv/dt = (-v + a + 2*sin(2*pi*t/tau))/tau : 1
a : 1
'''

neurons = NeuronGroup(N, eqs, threshold='v>1', reset='v=0', method='euler')
neurons.a = linspace(2, 4, N)

run(5*second, report='text')  # discard the first spikes (wait for convergence)
S = SpikeMonitor(neurons)
run(5*second, report='text')

i, t = S.it
plot((t % tau)/tau, neurons.a[i], '.')
xlabel('Spike phase')
ylabel('Parameter a')
show()
