quantal_stp_synapse

quantal_stp_synapse#

class brainpy.state.quantal_stp_synapse(*args, **kwargs)#

Quantal (binomial) short-term-plasticity synapse spec.

Parameters:

  • weight (ArrayLike or Quantity, optional) – Per-edge, per-site weight (pA; the maximum delivered amplitude is n * weight). Default 1.0 pA.

  • delay (Quantity, optional) – Homogeneous axonal delay (> 0). Default 1.0 ms.

  • receptor_type (int, optional) – Postsynaptic receptor port (>= 0). Default 0.

  • U (float, optional) – Baseline release probability, in [0, 1]. Default 0.5.

  • u (float, optional) – Initial release probability, in [0, 1]. Defaults to U.

  • n (int, optional) – Number of release sites (static). Default 1.

  • a (int, optional) – Initial number of available sites. Defaults to n.

  • tau_rec (Quantity, optional) – Recovery constant (> 0). Default 800.0 ms.

  • tau_fac (Quantity, optional) – Facilitation constant (>= 0). Default 0.0 ms.

Notes

t_lastspike initialises to -1.0 (first spike skips decay/recovery). Facilitation uses a tau_fac < 1e-10 threshold (NOT exact equality, unlike tsodyks2_synapse). The delivered amplitude is n_rel * weight with no /n normalisation, and a is not hard-clamped (the dynamics keep it in [0, n]). Recovery and release use jax.random.binomial(), so the stream differs from NEST — compare distributionally.

References

Examples

>>> from brainpy.state import quantal_stp_synapse
>>> s = quantal_stp_synapse()
>>> s.stochastic
True
>>> s.n
1
>>> s.edge_state_init()['a']
1.0