Multichannel time encoding with integrate-and-fire neurons

Time encoding is a mechanism of mapping amplitude information into a time sequence. We show that multichannel time encoding using filter banks and integrate-and-fire neurons provides, under natural conditions, an invertible representation of information, i.e., a sensory stimulus can be recovered from its multidimensional spike train representation loss-free. We describe an algorithm for perfect stimulus recovery and derive conditions that guarantee its convergence.