Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics

Here we provide a perspective concept of neurohybrid memristive chip based on the combination of living neural networks cultivated in microfluidic/microelectrode system, metal-oxide memristive devices or arrays integrated with mixed-signal CMOS layer to control the analog memristive circuits, proces...

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Bibliographic Details
Main Authors: Alexey Mikhaylov, Alexey Pimashkin, Yana Pigareva, Svetlana Gerasimova, Evgeny Gryaznov, Sergey Shchanikov, Anton Zuev, Max Talanov, Igor Lavrov, Vyacheslav Demin, Victor Erokhin, Sergey Lobov, Irina Mukhina, Victor Kazantsev, Huaqiang Wu, Bernardo Spagnolo
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Neuroscience
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Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00358/full
Description
Summary:Here we provide a perspective concept of neurohybrid memristive chip based on the combination of living neural networks cultivated in microfluidic/microelectrode system, metal-oxide memristive devices or arrays integrated with mixed-signal CMOS layer to control the analog memristive circuits, process the decoded information, and arrange a feedback stimulation of biological culture as parts of a bidirectional neurointerface. Our main focus is on the state-of-the-art approaches for cultivation and spatial ordering of the network of dissociated hippocampal neuron cells, fabrication of a large-scale cross-bar array of memristive devices tailored using device engineering, resistive state programming, or non-linear dynamics, as well as hardware implementation of spiking neural networks (SNNs) based on the arrays of memristive devices and integrated CMOS electronics. The concept represents an example of a brain-on-chip system belonging to a more general class of memristive neurohybrid systems for a new-generation robotics, artificial intelligence, and personalized medicine, discussed in the framework of the proposed roadmap for the next decade period.
ISSN:1662-453X