A video Time Encoding Machine

Time encoding is a real-time asynchronous mechanism of mapping analog amplitude information into multidimensional time sequences. We investigate the exact representation of analog video streams with a Time Encoding Machine realized with a population of spiking neurons. We also provide an algorithm that perfectly recovers streaming video from the spike trains of the neural population. Finally, we analyze the quality of recovery of a space-time separable video stream encoded with a population of integrate-and-fire neurons and demonstrate that the quality of recovery increases as a function of the population size.