norse.torch.functional.lif_mc_feed_forward_step

norse.torch.functional.lif_mc_feed_forward_step(input_tensor: Tensor, state: LIFFeedForwardState, g_coupling: Tensor, p: LIFParameters = LIFParameters(tau_syn_inv=tensor(200.), tau_mem_inv=tensor(100.), v_leak=tensor(0.), v_th=tensor(1.), v_reset=tensor(0.), method='super', alpha=tensor(100.)), dt: float = 0.001) → Tuple[Tensor, LIFFeedForwardState]

Computes a single euler-integration feed forward step of a LIF multi-compartment neuron-model.

Parameters:

input_tensor (torch.Tensor): the (weighted) input spikes at the

current time step

s (LIFFeedForwardState): current state of the neuron g_coupling (torch.Tensor): conductances between the neuron compartments p (LIFParameters): neuron parameters dt (float): Integration timestep to use