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Memristive Integrative Sensors for Neuronal Activity by Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis is a scholarly article available to read on EtoBox.

What is Memristive Integrative Sensors for Neuronal Activity about?

The advent of advanced neuronal interfaces offers great promise for linking brain functions to electronics. A major bottleneck in achieving this is real-time processing of big data that imposes excessive requirements on bandwidth, energy and computation capacity; limiting the overall number of bio-electronic links. Here, we present a novel monitoring system concept that exploits the intrinsic properties of memristors for processing neural information in real time. We demonstrate that the inherent voltage thresholds of solid-state TiOx memristors can be useful for discriminating significant neural activity, i.e. spiking events, from noise. When compared with a multi-dimensional, principal component feature space threshold detector, our system is capable of recording the majority of significant events, without resorting to computationally heavy off-line processing. We also show a memristive integrating sensing array that discriminates neuronal activity recorded in-vitro. We prove that information on spiking event amplitude is simultaneously transduced and stored as non-volatile resistive state transitions, allowing for more efficient data compression, demonstrating the memristors' po

Author

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

Published

2015

Language

EN