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The human brain is able to process a myriad of information in a flexible and stable way and is therefore able to react adequately to ever changing environmental influences. An important building block for this is non-linear dynamics. This enables to integrate the multitude of information in an enormous and massively parallel network of neurons that are divided into functionally specialized regions such as the visual cortex, auditory cortex, or dorsolateral prefrontal cortex. Each of these regions participates as a context-dependent, self-organized, and transient subnetwork, which can be shifted by changes in attention every 0.5 to 2 s. Even if the underlying mechanisms are only partially understood, the importance of the interaction between dynamics and topology has been identified as one of the essential building blocks in recent years. In this context, memristive devices integrated in neuromorphic computing systems offer a new degree of freedom.

In this lecture, Martin Ziegler will discuss the challenges and prospects of memristive devices for neuromorphic computing in general and at several selected examples. He presents redox-based memristive elements and shows how their properties can be tailored by systematic design variations for applications in neuromorphic computing architectures. Furthermore, he will show how resistance changes of memristive devices affect the dynamics of networks, but also how network dynamics influence the network connectivity.

Important requirements for memristive devices will be discussed and it will be shown how a new way of information processing beyond current approaches can be enabled to opens a new pathway toward the construction of cognitive electronics. This work was partially funded by the Carl-Zeiss Foundation via the Project MemWerk and the German Research Foundation (DFG) through the CRC 1461 "Neurotronics – Bio-Inspired Information Pathway".