Emulation of Learning Behavior in the Hippocampus: From Memristive Learning to Behavioral Tests

Abstract

AbstractNeuromorphic engineering is concerned with the emulation of biological learning and memory processes in hardware. The use of memristive devices, i.e., non-volatile memory devices, has given this field a significant boost in the last decade. However, most of today's efforts are aimed at the hardware implementation of artificial intelligence computational methods, while the emulation of biological computational methods is less pursued. In the latter, however, there is enormous potential for information technology. For this, however, network-dependent cognitive functionalities from biology must be identified and transferred to technical systems. In this chapter, we will show a possible approach. Using the hippocampus, which is the central structure of the mammalian brain responsible for learning new information, as an example, it is shown how elementary cognitive functions can be investigated by behavioral tests in humans and how their functionality can be broken down to the network dependent functionalities. Furthermore, it is shown how these functionalities can be technically reproduced in a memristive network model.