  The leaky integrate and fire (LIF) neuron represents standard neuronal model
used for numerical simulations. The leakage is implemented in the model as
exponential decay of trans-membrane voltage towards its resting value. This
makes inevitable the usage of machine floating point numbers in the course of
simulation. It is known that machine floating point arithmetic is subjected to
small inaccuracies, which prevent from exact comparison of floating point
quantities. In particular, it is incorrect to decide whether two separate in
time states of a simulated system composed of LIF neurons are exactly
identical. However, decision of this type is necessary, e.g. to figure periodic
dynamical regimes in a reverberating network. Here we offer a simulation
paradigm of a LIF neuron, in which neuronal states are described by whole
numbers. Within this paradigm, the LIF neuron behaves exactly the same way as
does the standard floating point simulated LIF, although exact comparison of
states becomes correctly defined.
