Neurons display continuous subthreshold oscillations and discrete action potentials. When action potentials are phase-locked to the subthreshold oscillation, we hypothesize they represent two types of information: the presence/absence of a sensory feature and the phase of subthreshold oscillation. If subthreshold oscillation phases are neuron-specific, then the sources of action potentials can be recovered based on the action potential times. If the spatial information about the stimulus is converted to action potential phases, then action potentials from multiple neurons can be combined into a single axon and the spatial configuration reconstructed elsewhere. For the reconstruction to be successful, we introduce two assumptions: that a subthreshold oscillation field has a constant phase gradient and that coincidences between action potentials and intracellular subthreshold oscillations are neuron-specific as defined by the "interference principle." Under these assumptions, a phase coding model enables information transfer between structures and reproduces experimental phenomenons such as phase precession, grid cell architecture, and phase modulation of cortical spikes. This article reviews a recently proposed neuronal algorithm for information encoding and decoding from the phase of action potentials (Nadasdy 2009). The focus is given to the principles common across different systems instead of emphasizing system specific differences.