class brainpy.dyn.STD(size, keep_size=False, sharding=None, method='exp_auto', name=None, mode=None, tau=200.0, U=0.07)[source]#

Synaptic output with short-term depression.

This model filters the synaptic current by the following equation:

\[I_{syn}^+(t) = I_{syn}^-(t) * x\]

where \(x\) is the normalized variable between 0 and 1, and \(I_{syn}^-(t)\) and \(I_{syn}^+(t)\) are the synaptic currents before and after STD filtering.

Moreover, \(x\) is updated according to the dynamics of:

\[\frac{dx}{dt} = \frac{1-x}{\tau} - U * x * \delta(t-t_{spike})\]

where \(U\) is the fraction of resources used per action potential, \(\tau\) is the time constant of recovery of the synaptic vesicles.

reset_state(batch_or_mode=None, **kwargs)[source]#

Reset function which resets local states in this model.

Simply speaking, this function should implement the logic of resetting of local variables in this node.

See for details.


The function to specify the updating rule.