Cargando…
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...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1783529158768328704 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7199501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT mikhaylovalexey neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT pimashkinalexey neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT pigarevayana neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT gerasimovasvetlana neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT gryaznovevgeny neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT shchanikovsergey neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT zuevanton neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT talanovmax neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT lavrovigor neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT deminvyacheslav neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT erokhinvictor neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT lobovsergey neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT mukhinairina neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT kazantsevvictor neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT wuhuaqiang neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics AT spagnolobernardo neurohybridmemristivecmosintegratedsystemsforbiosensorsandneuroprosthetics |