The brain acquires sensory signals and programs neural codes to manager cognitions and behaviors, to which the signal storage and encoding done by the neurons in brain circuits are essential. The elucidation of principles how the neurons encode and memorize input signals is basic to develop brain-simulated computers. Here, we briefly review the principles of neuron encoding and memory cell working, such as the conversion of analogue to digital signals, the compatible output of digital signals as well as the memory of input signals. The conversion of analogue-to-digital signal is influenced by the transmitter release pattern and probability from presynaptic terminals, the receptor responsiveness and density in postsynaptic spines as well as the number and ratio of excitatory versus inhibitory synapses. The integrated signals instigate the soma to encode digital spikes. When these spikes are propagated on axonal branches, their propagation efficiency is compatible with spiking ability in postsynaptic partner neurons. In terms of the storage and retrieval of newly acquired signals, the characteristics of associative memory cells include the followings. They are recruited to encode multiple signals being associated. They receive multiple synaptic inputs from the locations of signals’ origins. Their axons project toward the brain areas being associatively activated, as well as other brain regions for memory presentation. Their recruitments are downregulated by changing gene and protein expressions with microRNA manipulations or others. The upregulation or downregulation of these neurons, their synaptic inputs and axon projections changes memory capacity. Their axons project to the contralateral cortices and make the synapse innervations that send the acquired signals for unilateral learning toward bilateral memory.