Asymmetric electrode geometry induced photovoltaic behavior for self-powered organic artificial synapses

Author(s):  
Shizan Zou ◽  
Hengyuan Wang ◽  
Jianhang Guo ◽  
Sai Jiang ◽  
Ziqian Hao ◽  
...  

Abstract Optoelectronic synapses have attracted considerable attention because of their promising potential in artificial visual perception systems for neuromorphic computing. Despite remarkable progress in mimicking synaptic functions, reduction of energy consumption of artificial synapses is still a substantial obstacle that is required to be overcome to promote advanced emerging applications. Herein, we propose a zero-power artificial optoelectrical synapses using ultrathin organic crystalline semiconductors, which can be self-driven by exploiting the photovoltaic effect induced by asymmetric electrode geometry contacts. The photogenerated charge carrier collection at the two electrodes is unbalanced due to the asymmetric contacts, leading to the in-plane current without bias voltage. Our devices successfully mimic a range of important synaptic functions, such as paired-pulse facilitation (PPF) and spike rate-dependent plasticity (SRDP). Furthermore, we demonstrate that our devices can realize the simulation of image sharpening under self-driven optical-sensing synaptic operations, offering prospects for the development of retinomorphic visual systems.

2020 ◽  
Vol 67 (8) ◽  
pp. 3451-3458
Author(s):  
Pavan Kumar Reddy Boppidi ◽  
Bharathwaj Suresh ◽  
Ainur Zhussupbekova ◽  
Pranab Biswas ◽  
Daragh Mullarkey ◽  
...  

2021 ◽  
Vol 47 (2) ◽  
pp. 1785-1791
Author(s):  
Chun-Ying Huang ◽  
Kuan-Chieh Chen ◽  
Chih-Jung Chang

2019 ◽  
Vol 1 (6) ◽  
pp. 845-853 ◽  
Author(s):  
Peng Huang ◽  
Zefan Li ◽  
Zhen Dong ◽  
Runze Han ◽  
Zheng Zhou ◽  
...  

Author(s):  
Vishal Gyanchandani ◽  
Sayed Nahiyan Masabi ◽  
Hailing Fu

1983 ◽  
Vol 50 (4) ◽  
pp. 798-818 ◽  
Author(s):  
R. W. McCarley ◽  
O. Benoit ◽  
G. Barrionuevo

The relationship between behavioral state, discharge pattern, and discharge rate was investigated in 26 lateral geniculate nucleus (LGN) units recorded in cats in the dark during waking (W), synchronized sleep (S), and desynchronized sleep (D). A distinctive state-dependent discharge pattern was the presence of stereotyped bursts of 2-7 spikes that occurred in 63% of the units. These bursts were most frequent in S, much less frequent in D, and rarely occurred in W. Lack of association with discharge rate changes between states showed the bursting to be a true state-dependent phenomenon. A burst consisted of 2-7 spikes, with each successive interspike interval being longer than the preceding one; in the 200 ms prior to burst occurrence, discharge probability decreased markedly. This structure of burst organization suggested a model of generation wherein each burst was caused by a unitary event of varying intensity, perhaps a rebound following a hyperpolarization. Spectral and autocorrelational analyses showed bursts occurred rhythmically in three cells at a frequency of 3-4 Hz and in two cells at a frequency of 10-12 Hz, indicating a possible linkage with slow-wave generators. While the number of bursts in the various behavioral states was a state-dependent phenomena, other aspects of discharge pattern were shown to be rate dependent. To evaluate discharge pattern apart from the occurrence of bursts, a "primary event spike train" was formed; this consisted of individual spikes and the first spike of each burst. This analysis showed that, within S, the probability of burst occurrence was highest when the primary spike rate was low. Quantitative analyses showed that first-order pattern measures (the form of the interspike interval histogram, IH) were dependent on the mean interspike interval (ISI, the inverse of mean rate). This association explained 83-89% of the variance in a power series approximation of IH form. Joint interval histograms (JIH) were used to evaluate the signature of bursts and of the form of the primary spike train. As with interval histograms, the main features of the form of the primary spike JIH were dependent on the primary spike rate. Thus, we concluded that first- and second-order discharge patterns of primary events were rate dependent and not state dependent. Our data are compatible with a model where in the absence of retinal input, the frequency of LGN primary spikes over behavioral state changes is largely determined by brain stem reticular formation input.(ABSTRACT TRUNCATED AT 400 WORDS)


2016 ◽  
Vol 2 (6) ◽  
pp. e1501326 ◽  
Author(s):  
Wentao Xu ◽  
Sung-Yong Min ◽  
Hyunsang Hwang ◽  
Tae-Woo Lee

Emulation of biological synapses is an important step toward construction of large-scale brain-inspired electronics. Despite remarkable progress in emulating synaptic functions, current synaptic devices still consume energy that is orders of magnitude greater than do biological synapses (~10 fJ per synaptic event). Reduction of energy consumption of artificial synapses remains a difficult challenge. We report organic nanowire (ONW) synaptic transistors (STs) that emulate the important working principles of a biological synapse. The ONWs emulate the morphology of nerve fibers. With a core-sheath–structured ONW active channel and a well-confined 300-nm channel length obtained using ONW lithography, ~1.23 fJ per synaptic event for individual ONW was attained, which rivals that of biological synapses. The ONW STs provide a significant step toward realizing low-energy–consuming artificial intelligent electronics and open new approaches to assembling soft neuromorphic systems with nanometer feature size.


RSC Advances ◽  
2015 ◽  
Vol 5 (119) ◽  
pp. 98110-98117 ◽  
Author(s):  
W. S. Dong ◽  
F. Zeng ◽  
S. H. Lu ◽  
X. J. Li ◽  
C. T. Chang ◽  
...  

Long-term bidirectional frequency selectivity has been achieved in MEH-PPV/PEO–Nd3+cells, which suggests spike-rate-dependent plasticity learning protocol. It depends on pulse shape due to variation of ionic type.


2018 ◽  
Vol 112 (12) ◽  
pp. 122103 ◽  
Author(s):  
Xianjie Wang ◽  
Qian Zhou ◽  
Hui Li ◽  
Chang Hu ◽  
Lingli Zhang ◽  
...  

2017 ◽  
Author(s):  
Eline R. Kupers ◽  
Helena X. Wang ◽  
Kaoru Amano ◽  
Kendrick N. Kay ◽  
David J. Heeger ◽  
...  

AbstractCurrently, non-invasive methods for studying the human brain do not reliably measure signals that depend on the rate of action potentials (spikes) in a neural population, independent of other responses such as hemodynamic coupling (functional magnetic resonance imaging) and subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive methods - animal microelectrode recordings and human intracortical recordings (electrocorticography, or ECoG) - have recently measured broadband power elevation spanning 50-200 Hz in electrical fields generated by neuronal activity as a proxy for the locally averaged spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using a non-invasive method - magnetoencephalography (MEG) - in individual subjects. Because extracranial measurements like MEG have multiple global noise sources and a relatively low signal-to-noise ratio, we developed an automated denoising technique, adapted from Kay et al, 2013 (1), that helps reveal the broadband signal of interest. Subjects viewed 12-Hz contrast-reversing patterns in the left, right, or bilateral visual field. Sensor time series were separated into an evoked component (12-Hz amplitude) and a broadband component (60–150 Hz, excluding stimulus harmonics). In all subjects, denoised broadband responses were reliably measured in sensors over occipital cortex. The spatial pattern of the broadband measure depended on the stimulus, with greater broadband power in sensors contralateral to the stimulus. Because we obtain reliable broadband estimates with relatively short experiments (~20 minutes), with a sufficient signal-to-noise-ratio to distinguish responses to different stimuli, we conclude that MEG broadband signals, denoised with our method, offer a practical, non-invasive means for characterizing spike-rate-dependent neural activity for a wide range of scientific questions about human brain function.Author SummaryNeuronal activity causes perturbations in nearby electrical fields. These perturbations can be measured non-invasively in the living human brain using electro- and magneto-encephalography (EEG and MEG). These two techniques have generally emphasized two kinds of measurements: oscillations and event-related responses, both of which reflect synchronous activity from large populations of neurons. A third type of signal, a stimulus-related increase in power spanning a wide range of frequencies (‘broadband’), is routinely measured in invasive recordings in animals and pre-surgical patients with implanted electrodes, but not with MEG and EEG. This broadband response is of great interest because unlike oscillations and event-related responses, it is correlated with neuronal spike rates. Here we report quantitative, spatially specific measurements of broadband fields in individual human subjects using MEG. These results demonstrate that a spike- rate-dependent measure of brain activity can be obtained non-invasively from the living human brain, and is suitable for investigating a wide range of questions about spiking activity in the human brain.


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