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      A bioinspired analogous nerve towards artificial intelligence

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          Abstract

          A bionic artificial device commonly integrates various distributed functional units to mimic the functions of biological sensory neural system, bringing intricate interconnections, complicated structure, and interference in signal transmission. Here we show an all-in-one bionic artificial nerve based on a separate electrical double-layers structure that integrates the functions of perception, recognition, and transmission. The bionic artificial nerve features flexibility, rapid response (<21 ms), high robustness, excellent durability (>10,000 tests), personalized cutability, and no energy consumption when no mechanical stimulation is being applied. The response signals are highly regionally differentiated for the mechanical stimulations, which enables the bionic artificial nerve to mimic the spatiotemporally dynamic logic of a biological neural network. Multifunctional touch interactions demonstrate the enormous potential of the bionic artificial nerve for human-machine hybrid perceptual enhancement. By incorporating the spatiotemporal resolution function and algorithmic analysis, we hope that bionic artificial nerves will promote further development of sophisticated neuroprosthetics and intelligent robotics.

          Abstract

          Designing artificial sensory neural system for neuroprosthetics and smart robotics applications remains a challenge. Here, the authors demonstrate an all-in-one bionic sensory transmission nerve capable integrating the functions of perception, recognition and transmission of mechano-sensitive signal.

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          Most cited references26

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          Short-term synaptic plasticity.

          Synaptic transmission is a dynamic process. Postsynaptic responses wax and wane as presynaptic activity evolves. This prominent characteristic of chemical synaptic transmission is a crucial determinant of the response properties of synapses and, in turn, of the stimulus properties selected by neural networks and of the patterns of activity generated by those networks. This review focuses on synaptic changes that result from prior activity in the synapse under study, and is restricted to short-term effects that last for at most a few minutes. Forms of synaptic enhancement, such as facilitation, augmentation, and post-tetanic potentiation, are usually attributed to effects of a residual elevation in presynaptic [Ca(2+)]i, acting on one or more molecular targets that appear to be distinct from the secretory trigger responsible for fast exocytosis and phasic release of transmitter to single action potentials. We discuss the evidence for this hypothesis, and the origins of the different kinetic phases of synaptic enhancement, as well as the interpretation of statistical changes in transmitter release and roles played by other factors such as alterations in presynaptic Ca(2+) influx or postsynaptic levels of [Ca(2+)]i. Synaptic depression dominates enhancement at many synapses. Depression is usually attributed to depletion of some pool of readily releasable vesicles, and various forms of the depletion model are discussed. Depression can also arise from feedback activation of presynaptic receptors and from postsynaptic processes such as receptor desensitization. In addition, glial-neuronal interactions can contribute to short-term synaptic plasticity. Finally, we summarize the recent literature on putative molecular players in synaptic plasticity and the effects of genetic manipulations and other modulatory influences.
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            Noise in the nervous system.

            Noise--random disturbances of signals--poses a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the nervous system have only recently been addressed in a quantitative manner. Experimental and computational methods have shown that multiple noise sources contribute to cellular and behavioural trial-to-trial variability. We review the sources of noise in the nervous system, from the molecular to the behavioural level, and show how noise contributes to trial-to-trial variability. We highlight how noise affects neuronal networks and the principles the nervous system applies to counter detrimental effects of noise, and briefly discuss noise's potential benefits.
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              Restoring cortical control of functional movement in a human with quadriplegia.

              Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic 'neural bypass' to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant's forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5-C6) to the seventh cervical to first thoracic (C7-T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.
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                Author and article information

                Contributors
                liaoxinqin677@163.com
                yjzheng@ntu.edu.sg
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                14 January 2020
                14 January 2020
                2020
                : 11
                : 268
                Affiliations
                [1 ]ISNI 0000 0001 2224 0361, GRID grid.59025.3b, School of Electrical and Electronic Engineering, , Nanyang Technological University, 50 Nanyang Avenue, ; Singapore, 639798 Singapore
                [2 ]ISNI 0000 0001 1431 9176, GRID grid.24695.3c, Department of Acupuncture and Moxibustion, Dongzhimen Hospital, , Beijing University of Chinese Medicine, Hai Yun Cang on the 5th Zip, ; Beijing, 100700 China
                [3 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Department of Biomedical Engineering, , National University of Singapore, ; 21 Lower Kent Ridge Road, Singapore, 119077 Singapore
                [4 ]ISNI 0000 0000 8841 6246, GRID grid.43555.32, Beijing Engineering Research Centre of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, 5 Zhongguancun South Street, ; Beijing, 100081 China
                [5 ]ISNI 0000 0000 9382 8202, GRID grid.443244.1, AICFVE of Beijing Film Academy, ; 4 Xitucheng Road, Beijing, 100088 China
                Author information
                http://orcid.org/0000-0001-7772-3280
                http://orcid.org/0000-0002-6488-1551
                http://orcid.org/0000-0001-9422-0888
                Article
                14214
                10.1038/s41467-019-14214-x
                6959309
                31937777
                988eb8a1-a660-4c6f-be3f-ed0950610366
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 September 2019
                : 16 December 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: No. 61661146002
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                electrical and electronic engineering,sensors and biosensors
                Uncategorized
                electrical and electronic engineering, sensors and biosensors

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