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      Color‐Recognizing Si‐Based Photonic Synapse for Artificial Visual System

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          Abstract

          Recently, photonic synapses that can directly respond to light signals have attracted much attention due to their huge application potential in neuromorphic chips and artificial vision systems. However, the implementation of an artificial visual system based on a synapse remains a considerable challenge due to the limitation that most current photonic synapses fail to recognize color. Here, a photonic synapse with color recognition capability is proposed and demonstrated. Through the light‐induced adjustment of dangling bond defects inside the amorphous silicon (a‐Si) film, the device exhibits switchable volatile and nonvolatile photoconductivity (PC) behaviors at the wavelengths of 635 and 450 nm, respectively. Based on the dual PC, the photonic synapse enables dual synaptic plasticity depending on the stimulation light, allowing not only various synaptic functions, but also learning experiences, associative learning behaviors, and recognition of the red and blue colors. Moreover, the dual synaptic plasticity of the photonic synapse could be modulated via a voltage in the range below ≈1 V to realize the stable detection and precise extraction of the grayscale and color signals. With its simple structure and compatibility with existing Si‐complementary metal oxide semiconductor (CMOS) technology, this photonic synapse shows potential for application in neuromorphic computing and advanced robot vision systems.

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          Most cited references47

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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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            Synaptic plasticity: multiple forms, functions, and mechanisms.

            Experiences, whether they be learning in a classroom, a stressful event, or ingestion of a psychoactive substance, impact the brain by modifying the activity and organization of specific neural circuitry. A major mechanism by which the neural activity generated by an experience modifies brain function is via modifications of synaptic transmission; that is, synaptic plasticity. Here, we review current understanding of the mechanisms of the major forms of synaptic plasticity at excitatory synapses in the mammalian brain. We also provide examples of the possible developmental and behavioral functions of synaptic plasticity and how maladaptive synaptic plasticity may contribute to neuropsychiatric disorders.
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              Short-term plasticity and long-term potentiation mimicked in single inorganic synapses.

              Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag(2)S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag(2)S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag(2)S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory.
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                Author and article information

                Contributors
                Journal
                Advanced Intelligent Systems
                Advanced Intelligent Systems
                Wiley
                2640-4567
                2640-4567
                November 2020
                September 16 2020
                November 2020
                : 2
                : 11
                Affiliations
                [1 ] School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China
                [2 ] Key Laboratory of Information Materials of Sichuan Province and School of Preparatory Education Southwest Minzu University Chengdu 610041 China
                [3 ] State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu 610054 China
                Article
                10.1002/aisy.202000107
                fa9e87f2-280c-4bdd-bb3e-28a8ab6d8414
                © 2020

                http://creativecommons.org/licenses/by/4.0/

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