This paper deals with a synthesis of Pulsed Para-Neural Networks (PPNN) in a 3-D Cellular Automata space. In its essence, PPNN is a set of simple processing units that change their states only in certain discrete moments of time. A given unit may send a pulse to and only to its nearest neighbors. There are three kinds of processing units: red cells, yellow cells, and blue cells. A red cell cumulates excitation/inhibition in both time and space. It emits a pulse if and only if the value of its counter at t+1 gets equal to or greater than 2, where the state of the counter for t+1 is the state for t plus the weighted sum of pulses incoming in t. Each weight is associated with one and only one inlet to the cell and may be equal to 1, 0 or ?1. The counter is zeroed after every pulse emission. A yellow cell represents a formal neuron whose inputs provide a pre-synaptic inhibition to all other inputs. A string of adjacent blue cells constitutes an axon.A number of useful devices has been created in its framework. We present (1) an associative memory to be filled via reinforcement learning (what is remembered is a set of phases of pulses circulating in closed loops made of cells), and (2) a spiking neuron that non-linearly cumulates excitation and responds with a changeable frequency of produced pulses, (3) an adjustable timer and (4) an object location recognizer. We also present tools and methods used for PPNN synthesis.