Computational models and hardware implementations for real-time neuron–machine interactions

Abstract

In this chapter, we review some mathematical models of neural circuits and their hardware implementations, which provide solutions capable of reverseengineering neural interconnections and modulating biological neural circuit dynamics with closed-loop neuro-silico integration. Such attempt requires advanced system identification algorithms and hardware systems that are competent to deliver such computation in real-time with ultra-low power architectures.