  Developing intelligent neuromorphic solutions remains a challenging
endeavour. It requires a solid conceptual understanding of the hardware's
fundamental building blocks. Beyond this, accessible and user-friendly
prototyping is crucial to speed up the design pipeline. We developed an open
source Loihi emulator based on the neural network simulator Brian that can
easily be incorporated into existing simulation workflows. We demonstrate
errorless Loihi emulation in software for a single neuron and for a recurrently
connected spiking neural network. On-chip learning is also reviewed and
implemented, with reasonable discrepancy due to stochastic rounding. This work
provides a coherent presentation of Loihi's computational unit and introduces a
new, easy-to-use Loihi prototyping package with the aim to help streamline
conceptualisation and deployment of new algorithms.
