Spiking Neural Predictive Coding for Continual Learning from Data Streams. (arXiv:1908.08655v3 [cs.NE] UPDATED)

For energy-efficient computation in specialized neuromorphic hardware, we
present spiking neural coding, an instantiation of a family of artificial
neural models grounded in the theory of predictive coding. This model, the
first of its kind, works by operating in a never-ending process of
"guess-and-check", where neurons predict the activity values of one another and
then adjust their own activities to make better future predictions. The
interactive, iterative nature of our system fits well into the continuous time
formulation of sensory …

arxiv coding continual data data streams learning predictive