Results 281 to 290 of about 85,686 (325)

Dual‐Modal Optoelectronic Synaptic Devices with Versatile Synaptic Plasticity

Advanced Functional Materials, 2021
AbstractOptoelectronic synaptic devices that mimic biological synapses are critical building blocks of artificial neural networks (ANN) based on optoelectronic integration. Here it is shown that an optoelectronic synaptic device based on the hybrid structure of silicon nanocrystals (Si NCs) and poly(3‐hexylthiophene) (P3HT) can work with dual modes ...
Yue Wang, Yiyue Zhu, Yayao Li, Yiqiang Zhang, Deren Yang, Xiaodong Pi   +5 more
openaire   +1 more source

Optogenetics-Inspired Fluorescent Synaptic Devices with Nonvolatility

ACS Nano, 2023
Given the synergy of optogenetics and bioimaging in neuroscience, it is possible for light to simultaneously modulate and visualize synaptic events of optoelectronic synaptic devices, which are building blocks of a neuromorphic computing system with optoelectronic integration.
Yue Wang, Kun Wang, Xiangyu Hu, Ya’kun Wang, Wandong Gao, Yiqiang Zhang, Zhenghui Liu, Yi Zheng, Ke Xu, Deren Yang, Xiaodong Pi   +10 more
openaire   +2 more sources

Silicon-based optoelectronic synaptic devices*

Chinese Physics B, 2020
High-performance neuromorphic computing (i.e., brain-like computing) is envisioned to seriously demand optoelectronically integrated artificial neural networks (ANNs) in the future. Optoelectronic synaptic devices are critical building blocks for optoelectronically integrated ANNs.
Lei Yin, Xiaodong Pi, Deren Yang
openaire   +1 more source

Zero-power optoelectronic synaptic devices

Nano Energy, 2020
Abstract Synaptic devices for neuromorphic computing have been recently on the fast track of development. One of the most prominent features of synaptic devices is their potentially ultra-low energy consumption. However, relatively large energy has always been consumed to induce the postsynaptic current (PSC) of a synaptic device up to now.
Wen Huang, Pengjie Hang, Yue Wang, Kun Wang, Shihao Han, Zerui Chen, Wenbing Peng, Yiyue Zhu, Mingsheng Xu, Yiqiang Zhang, Yanjun Fang, Xuegong Yu, Deren Yang, Xiaodong Pi   +13 more
openaire   +1 more source

Synaptic Depression as a Timing Device

Physiology, 2005
A depressing synapse transforms a time interval into a voltage amplitude. The effect of that transformation on the output of the neuron and network depends on the kinetics of synaptic depression and properties of the postsynaptic neuron and network.
Lucinda A, Grande, William J, Spain
openaire   +2 more sources

Synaptic electronics: materials, devices and applications

Nanotechnology, 2013
In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological synaptic plasticity and learning are described. The material properties and electrical switching characteristics of a variety of synaptic devices are discussed, with a focus on the use of synaptic devices for neuromorphic or brain-inspired computing ...
Duygu, Kuzum, Shimeng, Yu, H-S Philip, Wong   +2 more
openaire   +2 more sources

Emulating Bilingual Synaptic Response Using a Junction-Based Artificial Synaptic Device

ACS Nano, 2017
Excitatory and inhibitory postsynaptic potentials are the two fundamental categories of synaptic responses underlying the diverse functionalities of the mammalian nervous system. Recent advances in neuroscience have revealed the co-release of both glutamate and GABA neurotransmitters from a single axon terminal in neurons at the ventral tegmental area ...
He Tian, Xi Cao, Yujun Xie, Xiaodong Yan, Andrew Kostelec, Don DiMarzio, Cheng Chang, Li-Dong Zhao, Wei Wu, Jesse Tice, Judy J. Cha, Jing Guo, Han Wang   +12 more
openaire   +2 more sources

Synaptic Metaplasticity Realized in Oxide Memristive Devices

Advanced Materials, 2015
Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-timing-dependent plasticity, are systematically investigated.
Zheng-Hua, Tan, Rui, Yang, Kazuya, Terabe, Xue-Bing, Yin, Xiao-Dong, Zhang, Xin, Guo   +5 more
openaire   +2 more sources

TaOx-/TiO2-Based Synaptic Devices

2017
The development of a high-density, low-power, and reliable synaptic device is essential in the implementation of highly anticipated hardware neural networks. Hence, numerous studies have investigated suitable two-terminal synaptic devices that precisely mimic biological synaptic features.
I-Ting Wang, Tuo-Hung Hou
openaire   +1 more source

Pr0.7Ca0.3MnO3 (PCMO)-Based Synaptic Devices

2017
On the basis of its operation mechanism, the RRAM can be briefly classified as filamentary type and interfacial type. Comparing to the interfacial-type RRAM, faster switching speed and higher scalability of the filamentary-type RRAM have been demonstrated for NVM applications.
Daeseok Lee, Hyunsang Hwang
openaire   +1 more source