lin_rate_opn

lin_rate_opn#

class brainpy.state.lin_rate_opn(in_size, tau=Quantity(10., 'ms'), sigma=1.0, mu=0.0, g=1.0, mult_coupling=False, g_ex=1.0, g_in=1.0, theta_ex=0.0, theta_in=0.0, linear_summation=True, rate_initializer=Constant(value=0.0), noise_initializer=Constant(value=0.0), noisy_rate_initializer=Constant(value=0.0), name=None)#

NEST-compatible lin_rate_opn linear rate neuron with output noise.

Description

lin_rate_opn implements NEST’s linear rate neuron with output noise:

\[\tau \frac{dX(t)}{dt} = -X(t) + \mu + \phi(\cdot), \qquad X_\mathrm{noisy}(t)=X(t)+\sqrt{\frac{\tau}{h}}\sigma\xi(t)\]

with \(\phi(h)=g\,h\) and piecewise-constant Gaussian noise.

Update ordering (matching NEST ``rate_neuron_opn``)

For each simulation step:

  1. Draw noise = sigma * xi and build noisy_rate from current rate.

  2. Propagate deterministic intrinsic dynamics.

  3. Read delayed and instantaneous rate-event buffers.

  4. Apply linear input nonlinearity and optional multiplicative coupling.

  5. Store outputs analogous to NEST events: both delayed_rate and instant_rate carry noisy_rate.

:param Same as lin_rate_ipn: :param except: :param - no lambda_ parameter (fixed leak form): :param : :param - no output rectification parameters.:

init_state(**kwargs)[source]#

State initialization function.