Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics

• Published in: Frontiers in neuroscience Vol. 14; p. 358
• Main Authors: Mikhaylov, Alexey, Pimashkin, Alexey, Pigareva, Yana, Gerasimova, Svetlana, Gryaznov, Evgeny, Shchanikov, Sergey, Zuev, Anton, Talanov, Max, Lavrov, Igor, Demin, Vyacheslav, Erokhin, Victor, Lobov, Sergey, Mukhina, Irina, Kazantsev, Victor, Wu, Huaqiang, Spagnolo, Bernardo
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 28.04.2020; Frontiers Media S.A
• Subjects: Arrays; Artificial intelligence; Biochips; biosensor; Biosensors; Brain research; Cell culture; Cognitive ability; Energy efficiency; Firing pattern; Hippocampus; Information processing; Interfaces; memristor; Microfluidics; Neural networks; neuronal culture; Neurons; neuroprosthetics; Neuroscience; Nonlinear systems; Precision medicine; Prostheses; Prosthetics; R&D; Research & development; Sensors; Signal processing; spiking neural network; biosensor; neuroprosthetics; neuronal culture; spiking neural network; microfluidics; memristor
• ISSN: 1662-453X; 1662-4548; 1662-453X
• DOI: 10.3389/fnins.2020.00358

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.