Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics

被引:136
|
作者
Mikhaylov, Alexey [1 ]
Pimashkin, Alexey [1 ]
Pigareva, Yana [1 ]
Gerasimova, Svetlana [1 ]
Gryaznov, Evgeny [1 ]
Shchanikov, Sergey [2 ]
Zuev, Anton [2 ]
Talanov, Max [3 ]
Lavrov, Igor [4 ,5 ]
Demin, Vyacheslav [6 ]
Erokhin, Victor [3 ,6 ,7 ]
Lobov, Sergey [1 ,8 ]
Mukhina, Irina [1 ,9 ]
Kazantsev, Victor [1 ,8 ]
Wu, Huaqiang [10 ]
Spagnolo, Bernardo [1 ,11 ,12 ,13 ]
机构
[1] Lobachevsky State Univ Nizhny Novgorod, Nizhnii Novgorod, Russia
[2] Vladimir State Univ, Dept Informat Technol, Murom, Russia
[3] Kazan Fed Univ, Neurosci Lab, 3, Kazan, Russia
[4] Mayo Clin, Dept Neurol Surg, Rochester, MN USA
[5] Kazan Fed Univ, Lab Motor Neurorehabil, Kazan, Russia
[6] Kurchatov Inst, Moscow, Russia
[7] Italian Natl Res Council, Inst Mat Elect & Magnetism, CNR, Parma, Italy
[8] Innopolis Univ, Ctr Technol Robot & Mechatron Components, Innopolis, Russia
[9] Privolzhsky Res Med Univ, Cell Technol Grp, Nizhnii Novgorod, Russia
[10] Tsinghua Univ, Inst Microelect, Beijing, Peoples R China
[11] Univ Palermo, Dipartimento Fis & Chim Emilio Segre, Grp Interdisciplinary Theoret Phys, Palermo, Italy
[12] CNISM, Unita Palermo, Palermo, Italy
[13] Ist Nazl Fis Nucl, Sez Catania, Catania, Italy
基金
俄罗斯基础研究基金会; 俄罗斯科学基金会;
关键词
memristor; neuronal culture; spiking neural network; microfluidics; biosensor; neuroprosthetics; PATTERN-FORMATION; NEURAL-NETWORKS; NOISE; BEHAVIOR; MODEL; NEUROSTIMULATION; NEUROMODULATION; CLASSIFICATION; CONNECTIVITY; SIMULATION;
D O I
10.3389/fnins.2020.00358
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.
引用
收藏
页数:14
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