About this Research Topic
The fascinating structural and functional interplay between the extraordinary complexity and computational capabilities of a biological neural network and in-materia artificial data processing systems at different length scale draws the attention of both fundamental studies and technological applications, in a multidisciplinary context ranging from physics, biology, material and computer science. Memristors and more in general materials based on non-linear dynamics (physical reservoirs) can be exploited for the development of intelligent devices which perform data processing beyond Von-Neumann architecture, by exploiting spontaneous activity of the materials and employing low power consumption. A case of interest is the biological-artificial system interface: in particular the possibility to engineer the development of in real-time processing systems which allow the transfer of the information encoded in neuronal network signaling into a response of the neuromorphic artificial material.
Keywords: bio-artificial interface, neuromorphic systems, in-materia data processing, non-linear dynamics, reservoir computing, real-time neural spiking transducer, memristive switching, memristive crossbar arrays
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