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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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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199501/
https://www.ncbi.nlm.nih.gov/pubmed/32410943
http://dx.doi.org/10.3389/fnins.2020.00358
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author 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
author_facet 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
author_sort Mikhaylov, Alexey
collection PubMed
description 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.
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spelling pubmed-71995012020-05-14 Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics 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 Front Neurosci Neuroscience 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. Frontiers Media S.A. 2020-04-28 /pmc/articles/PMC7199501/ /pubmed/32410943 http://dx.doi.org/10.3389/fnins.2020.00358 Text en Copyright © 2020 Mikhaylov, Pimashkin, Pigareva, Gerasimova, Gryaznov, Shchanikov, Zuev, Talanov, Lavrov, Demin, Erokhin, Lobov, Mukhina, Kazantsev, Wu and Spagnolo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
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
Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title_full Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title_fullStr Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title_full_unstemmed Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title_short Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
title_sort neurohybrid memristive cmos-integrated systems for biosensors and neuroprosthetics
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199501/
https://www.ncbi.nlm.nih.gov/pubmed/32410943
http://dx.doi.org/10.3389/fnins.2020.00358
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