SpikeCurrentMixin

class SpikeCurrentMixin(currents: Tensor, spikes: Tensor, current_interp: Interpolation, current_interp_kwargs: dict[str, Any], spike_interp: Interpolation, spike_interp_kwargs: dict[str, Any], current_overbound: float | None, spike_overbound: bool | None, tolerance: float)[source]

Bases: CurrentMixin, SpikeMixin

Mixin for synapses with primitive current and spikes.

Parameters:

  • currents (torch.Tensor) – initial synaptic currents, in \(\text{nA}\).

  • spikes (torch.Tensor) – initial input spikes.

  • current_interp (Interpolation) – interpolation function used when selecting prior currents.

  • current_interp_kwargs (dict[str, Any]) – keyword arguments passed into the interpolation function for currents.

  • spike_interp (Interpolation) – interpolation function used when selecting prior spikes.

  • spike_interp_kwargs (dict[str, Any]) – keyword arguments passed into the interpolation function for spikes.

  • current_overbound (float | None) – value to replace currents out of bounds, uses values at observation limits if None.

  • spike_overbound (bool | None) – value to replace spikes out of bounds, uses values at observation limits if None.

  • tolerance (float) – maximum difference in time from an observation to treat as co-occurring, in \(\text{ms}\).