def get_component():
subthreshold_regime = al.Regime(
name="subthreshold_regime",
time_derivatives=[
"dV/dt = (g_L*(E_L-V) + g_sfa*(E_sfa-V) + g_rr*(E_rr-V) + Isyn)/C",
"dg_sfa/dt = -g_sfa/tau_sfa",
"dg_rr/dt = -g_rr/tau_rr",
],
transitions=al.On("V> theta",
do=["g_sfa =g_sfa + q_sfa", "g_rr =g_rr + q_rr", "t_spike = t",
al.OutputEvent('spikeoutput')],
to="refractory_regime"),
)
refractory_regime = al.Regime(
name="refractory_regime",
transitions=al.On("t >= t_spike + t_ref",
to='subthreshold_regime'),
)
analog_ports = [al.SendPort("V"),
al.ReducePort("Isyn", reduce_op="+")]
c1 = al.ComponentClass("iaf_sfa_relref",
regimes=[subthreshold_regime, refractory_regime],
analog_ports=analog_ports,
)
return c1
def get_component():
parameters = [
'C_m', 'g_L', 'E_L', 'Delta', 'V_T', 'S', 'tau_ref', 'tau_w', 'a', 'b'
]
aeIF = al.ComponentClass(
"aeIF",
regimes=[
al.Regime(
name="subthresholdregime",
time_derivatives=[
"dV/dt = -g_L*(V-E_L)/C_m + g_L*Delta*exp((V-V_T)/Delta-w/S)/C_m+ Isyn/C_m",
"dw/dt = (a*(V-E_L)-w)/tau_w",
],
transitions=al.On(
"V > V_T",
do=["V = E_L", "w = w + b",
al.OutputEvent('spikeoutput')],
to="refractoryregime"),
),
al.Regime(
name="refractoryregime",
transitions=al.On("t>=tspike+trefractory",
to="subthresholdregime"),
)
],
analog_ports=[al.ReducePort("Isyn", reduce_op="+")])
return aeIF
def get_component():
subthreshold_regime = al.Regime(
name="subthreshold_regime",
time_derivatives=[
"dV/dt = (-gL*(V-vL) + Isyn)/C",
],
transitions=[
al.On("V> theta",
do=[
"t_spike = t", "V = V_reset",
al.OutputEvent('spikeoutput')
],
to="refractory_regime")
],
)
refractory_regime = al.Regime(
transitions=[al.On("t >= t_spike + t_ref", to='subthreshold_regime')],
name="refractory_regime")
analog_ports = [al.SendPort("V"), al.ReducePort("Isyn", reduce_op="+")]
c1 = al.ComponentClass("LeakyIAF",
regimes=[subthreshold_regime, refractory_regime],
analog_ports=analog_ports)
return c1
def get_component():
# Leaky iaf
regimes = [
al.Regime(
"dV/dt = (-gL*(V-vL) + Isyn)/C",
transitions=al.On(
"V>Vth", do=["tspike = t", "V = V_reset", al.OutputEvent('spikeoutput')], to="refractory-regime"),
name="sub-threshold-regime"
),
al.Regime(
transitions=al.On("t >= tspike + trefractory", to="sub-threshold-regime"),
name="refractory-regime"
)]
analog_ports = [al.SendPort("V"),
al.ReducePort("Isyn", reduce_op="+")]
leaky_iaf = al.ComponentClass("LeakyIAF", regimes=regimes, analog_ports=analog_ports)
# ampa
regimes = [
al.Regime(
"dg/dt = -g/tau",
transitions=al.On(al.SpikeInputEvent, do="g+=q")
)]
analog_ports = [al.RecvPort("V"),
al.SendPort("Isyn = g(E-V)")]
coba_syn = al.ComponentClass("CoBaSynapse", regimes=regimes, analog_ports=analog_ports)
def get_aeIF_component():
"""
Adaptive exponential integrate-and-fire neuron as described in
A. Destexhe, J COmput Neurosci 27: 493--506 (2009)
Author B. Kriener (Jan 2011)
## neuron model: aeIF
## variables:
## V: membrane potential
## w: adaptation variable
## parameters:
## C_m # specific membrane capacitance [muF/cm**2]
## g_L # leak conductance [mS/cm**2]
## E_L # resting potential [mV]
## Delta # steepness of exponential approach to threshold [mV]
## V_T # spike threshold [mV]
## S # membrane area [mum**2]
## trefractory # refractory time [ms]
## tspike # spike time [ms]
## tau_w # adaptation time constant
## a, b # adaptation parameters [muS, nA]
"""
parameters = [
'C_m', 'g_L', 'E_L', 'Delta', 'V_T', 'S', 'trefractory', 'tspike',
'tau_w', 'a', 'b'
]
aeIF = al.ComponentClass(
"aeIF",
regimes=[
al.Regime(
name="subthresholdregime",
time_derivatives=[
"dV/dt = -g_L*(V-E_L)/C_m + Isyn/C_m + g_L*Delta*exp((V-V_T)/Delta-w/S)/C_m",
"dw/dt = (a*(V-E_L)-w)/tau_w",
],
transitions=al.On(
"V > V_T",
do=["V = E_L", "w = w + b",
al.OutputEvent('spikeoutput')],
to="refractoryregime"),
),
al.Regime(
name="refractoryregime",
transitions=al.On("t>=tspike+trefractory",
to="subthresholdregime"),
)
],
analog_ports=[al.ReducePort("Isyn", reduce_op="+")])
return aeIF
def get_component():
aliases = [
"q10 := 3.0**((celsius - 6.3)/10.0)", # temperature correction factor
"alpha_m := -0.1*(V+40.0)/(exp(-(V+40.0)/10.0) - 1.0)", # m
"beta_m := 4.0*exp(-(V+65.0)/18.0)",
"mtau := 1/(q10*(alpha_m + beta_m))",
"minf := alpha_m/(alpha_m + beta_m)",
"alpha_h := 0.07*exp(-(V+65.0)/20.0)", # h
"beta_h := 1.0/(exp(-(V+35)/10.0) + 1.0)",
"htau := 1.0/(q10*(alpha_h + beta_h))",
"hinf := alpha_h/(alpha_h + beta_h)",
"alpha_n := -0.01*(V+55.0)/(exp(-(V+55.0)/10.0) - 1.0)", # n
"beta_n := 0.125*exp(-(V+65.0)/80.0)",
"ntau := 1.0/(q10*(alpha_n + beta_n))",
"ninf := alpha_n/(alpha_n + beta_n)",
"gna := gnabar*m*m*m*h", #
"gk := gkbar*n*n*n*n",
"ina := gna*(ena - V)", # currents
"ik := gk*(ek - V)",
"il := gl*(el - V )"
]
hh_regime = al.Regime("dn/dt = (ninf-n)/ntau",
"dm/dt = (minf-m)/mtau",
"dh/dt = (hinf-h)/htau",
"dV/dt = (ina + ik + il + Isyn)/C",
transitions=al.On("V > theta",
do=al.SpikeOutputEvent()))
# the rest are not "parameters" but aliases, assigned vars, state vars,
# indep vars, analog_analog_ports, etc.
parameters = [
'el',
'C',
'ek',
'ena',
'gkbar',
'gnabar',
'theta',
'gl',
'celsius',
]
analog_ports = [al.SendPort("V"), al.ReducePort("Isyn", reduce_op="+")]
c1 = al.ComponentClass("HodgkinHuxley",
parameters=parameters,
regimes=(hh_regime, ),
aliases=aliases,
analog_ports=analog_ports)
return c1
def get_component():
regimes = [
al.Regime(
name="subthreshold_regime",
time_derivatives=[
"dV/dt = 0.04*V*V + 5*V + 140.0 - U + Isyn",
"dU/dt = a*(b*V - U)"
],
transitions=[
al.On("V > theta",
do=["V = c", "U = U + d",
al.OutputEvent('spikeoutput')])
],
)
]
analog_ports = [al.SendPort("V"), al.ReducePort("Isyn", reduce_op="+")]
c1 = al.ComponentClass("Izhikevich",
regimes=regimes,
analog_ports=analog_ports)
return c1
# there may be a better way of doing this. this also does not clamp the individual v_i to
# v_reset durung the refractory period, it just doesn't sum over them.
regimes = [
nineml.Regime("dv/dt = Isyn",
transitions=nineml.On(
"V>Vth",
do=["tspike = t", "V = Vrest", nineml.SpikeOutputEvent],
to=refractory - regime),
name="sub-threshold-regime"),
nineml.Regime(transitions=nineml.On("t >= tspike + trefractory",
to="sub-threshold-regime"),
name="refractory-regime")
]
ports = [nineml.ReducePort("Isyn", op="+")]
leaky_iaf = nineml.Component("deltaLIFid5", regimes=regimes, ports=ports)
# delta jump synapses
regimes = [
nineml.Regime(
"dv/dt = -g*v",
transitions=nineml.On(nineml.SpikeInputEvent, do="g+=W"),
)
]
ports = [nineml.RecvPort("W"), nineml.SendPort("Isyn = dv/dt")]
# can i even send dv/dt as a variable?
Author: Abigail Morrison, 1/2011.
"""
import nineml.abstraction_layer as nineml
regimes = [
nineml.Regime("dV/dt = (Vrest - V)/(Rm*Cm) + Isyn/Cm",
transitions=nineml.On(
"V>Vth",
do=["tspike = t", "V = Vrest", nineml.SpikeOutputEvent]),
name="sub-threshold-regime")
]
ports = [nineml.SendPort("V"), nineml.ReducePort("Isyn", op="+")]
leaky_iaf = nineml.Component("gLIFid8", regimes=regimes, ports=ports)
# alpha conductances
regimes = [
nineml.Regime(
"dg_a/dt = -g_a/tau_a",
"dg/dt = g_a - g/tau_a",
transitions=nineml.On(nineml.SpikeInputEvent, do="g+=W"),
)
]
ports = [
nineml.RecvPort("V"),
hh_regime = al.Regime(
"dn/dt = (ninf(V)-n)/ntau(V)",
"dm/dt = (minf(V)-m)/mtau(V)",
"dh/dt = (hinf(V)-h)/htau(V)",
"dV/dt = (ina(m,h,V) + ik(n,V) + il(V) + Isyn - I)/C",
# I is a current injected as a function of orientation
name="hh_regime",
transitions=al.On("V > theta", do=[al.SpikeOutputEvent]))
parameters = [
'el', 'C', 'ek', 'ena', 'gkbar', 'gnabar', 'theta', 'gl', 'celsius'
]
ports = [
al.SendPort("V"),
al.ReducePort("Isyn", op="+"),
al.ReducePort("I", op="+"),
# "op" keyword argument determines how multiple inputs to this port are handled ?
]
c1 = al.Component("Hodgkin-Huxley-id14",
parameters=parameters,
regimes=(hh_regime, ),
aliases=aliases,
ports=ports)
# write to file object f if defined
try:
# This case is used in the test suite for examples.
c1.write(f)
except NameError: