def update(self, _t, _dt): in_interval = bm.logical_and(pre_stimulus_period < _t, _t < pre_stimulus_period + stimulus_period) prev_freq = bm.where(in_interval, self.freq[0], 0.) in_interval = bm.logical_and(in_interval, (_t - self.freq_t_last_change[0]) >= self.t_interval) self.freq[:] = bm.where(in_interval, self.rng.normal(self.freq_mean, self.freq_var), prev_freq) self.freq_t_last_change[:] = bm.where(in_interval, _t, self.freq_t_last_change[0]) self.spike.value = self.rng.random(self.num) < self.freq[0] * self.dt
def update(self, _t, _dt): V, self.W.value = self.integral(self.V, self.W, _t, self.input, dt=_dt) spike = bm.logical_and(self.V < self.V_th, V >= self.V_th) self.t_last_spike.value = bm.where(spike, _t, self.t_last_spike) self.V.value = V self.spike.value = spike self.input[:] = 0.
def update(self, _t, _dt):
V, w = self.integral(self.V, self.w, _t, self.input, dt=_dt)
self.spike.value = bm.logical_and(V >= self.Vth, self.V < self.Vth)
self.t_last_spike.value = bm.where(self.spike, _t, self.t_last_spike)
self.V.value = V
self.w.value = w
self.input[:] = 0.
def update(self, _t, _dt):
V, y, z = self.integral(self.V, self.y, self.z, _t, self.input, dt=_dt)
self.spike.value = bm.logical_and(V >= self.V_th, self.V < self.V_th)
self.t_last_spike.value = bm.where(self.spike, _t, self.t_last_spike)
self.V.value = V
self.y.value = y
self.z.value = z
self.input[:] = 0.
def update(self, _t, _dt):
h = self.int_h(self.h, _t, self.V, dt=_dt)
n = self.int_n(self.n, _t, self.V, dt=_dt)
V = self.int_V(self.V, _t, self.h, self.n, self.input, dt=_dt)
self.spike.value = bm.logical_and(self.V < self.V_th,
V >= self.V_th)
self.V.value = V
self.h.value = h
self.n.value = n
self.input[:] = 0.
def update(self, _t, _dt):
# update variables in channels
for ch in self.ion_channels.values():
ch.update(_t, _dt)
# update neuron variables
V = self.integral(self.V.value, _t, self.input.value, dt=_dt)
self.spike[:] = bm.logical_and(V >= self.V_th, self.V < self.V_th)
self.input[:] = 0.
self.V[:] = V
def update(self, _t, _dt):
V, m, h, n = self.integral(self.V,
self.m,
self.h,
self.n,
_t,
Isyn=self.input,
dt=_dt)
self.spike.value = bm.logical_and(self.V < V_th, V >= V_th)
self.m.value = m
self.h.value = h
self.n.value = n
self.V.value = V
self.input[:] = 0.
def update(self, _t, _dt):
if isinstance(self.int_V, bp.ode.ExpEulerAuto):
V = self.int_V(self.V, _t, self.y, self.z, self.input, dt=_dt)
self.y.value = self.int_y(self.y, _t, self.V, dt=_dt)
self.z.value = self.int_z(self.z, _t, self.V, dt=_dt)
else:
V, self.y.value, self.z.value = self.integral(self.V,
self.y,
self.z,
_t,
self.input,
dt=_dt)
self.spike.value = bm.logical_and((self.V < self.Vth), (V >= self.Vth))
self.V.value = V
self.input[:] = 0.
def update(self, _t, _dt):
V, m, h, n = self.integral(self.V,
self.m,
self.h,
self.n,
_t,
self.input,
dt=_dt)
self.spike.value = bm.logical_and(self.V < self.V_th, V >= self.V_th)
self.t_last_spike.value = bm.where(self.spike, _t, self.t_last_spike)
self.V.value = V
self.m.value = m
self.h.value = h
self.n.value = n
self.input[:] = 0.
def update(self, _t, _dt):
I1, I2, V_th, V = self.integral(self.I1,
self.I2,
self.V_th,
self.V,
_t,
self.input,
dt=_dt)
spike = self.V_th <= V
V = bm.where(spike, self.V_reset, V)
I1 = bm.where(spike, self.R1 * I1 + self.A1, I1)
I2 = bm.where(spike, self.R2 * I2 + self.A2, I2)
reset_th = bm.logical_and(V_th < self.V_th_reset, spike)
V_th = bm.where(reset_th, self.V_th_reset, V_th)
self.spike.value = spike
self.I1.value = I1
self.I2.value = I2
self.V_th.value = V_th
self.V.value = V
self.input[:] = 0.
def cond_fun(t): return bm.logical_and(self.i[0] < self.num_times, t >= self.times[self.i[0]])