FacetsPythonCourse2008: adaptive_threshold.py

'''
A model with adaptive threshold (increases with each spike)
'''
from brian import *

eqs='''
dv/dt = -v/(10*ms) : volt
dvt/dt = (10*mV-vt)/(15*ms) : volt
'''

def myreset(P, spikes):
    P.v[spikes]=0*mV
    P.vt[spikes]+=3*mV
    
IF = NeuronGroup(1, model=eqs,
        reset=myreset,
        threshold=lambda v,vt:v>=vt)
IF.rest()
PG = PoissonGroup(1, 500*Hz)

C = Connection(PG, IF, 'v')
C.connect_full(PG, IF, 3*mV)

Mv = StateMonitor(IF, 'v', record=True)
Mvt = StateMonitor(IF, 'vt', record=True)

run(100*ms)

plot(Mv.times/ms, Mv[0]/mV)
plot(Mvt.times/ms, Mvt[0]/mV)

show()