scholarly journals A Compact Model for Stochastic Spike-Timing-Dependent Plasticity (STDP) Based on Resistive Switching Memory (RRAM) Synapses

2020 ◽  
Vol 67 (7) ◽  
pp. 2800-2806
Author(s):  
Stefano Bianchi ◽  
Giacomo Pedretti ◽  
Irene Munoz-Martin ◽  
Alessandro Calderoni ◽  
Nirmal Ramaswamy ◽  
...  
2016 ◽  
Vol 1 (4) ◽  
Author(s):  
Yao-Feng Chang ◽  
Burt Fowler ◽  
Ying-Chen Chen ◽  
Fei Zhou ◽  
Chih-Hung Pan ◽  
...  

Abstract We realize a device with biological synaptic behaviors by integrating silicon oxide (SiOx) resistive switching memory with Si diodes to further minimize total synaptic power consumption due to sneak-path currents and demonstrate the capability for spike-induced synaptic behaviors, representing critical milestones for the use of SiO2-based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation, long-term depression, and spike-timing dependent plasticity are demonstrated systemically with comprehensive investigation of spike waveform analyses and represent a potential application for SiOx-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from the (SiH)2 defect to generate the hydrogenbridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with largescale complementary metal-oxide semiconductor manufacturing technology.


2006 ◽  
Vol 18 (10) ◽  
pp. 2414-2464 ◽  
Author(s):  
Peter A. Appleby ◽  
Terry Elliott

In earlier work we presented a stochastic model of spike-timing-dependent plasticity (STDP) in which STDP emerges only at the level of temporal or spatial synaptic ensembles. We derived the two-spike interaction function from this model and showed that it exhibits an STDP-like form. Here, we extend this work by examining the general n-spike interaction functions that may be derived from the model. A comparison between the two-spike interaction function and the higher-order interaction functions reveals profound differences. In particular, we show that the two-spike interaction function cannot support stable, competitive synaptic plasticity, such as that seen during neuronal development, without including modifications designed specifically to stabilize its behavior. In contrast, we show that all the higher-order interaction functions exhibit a fixed-point structure consistent with the presence of competitive synaptic dynamics. This difference originates in the unification of our proposed “switch” mechanism for synaptic plasticity, coupling synaptic depression and synaptic potentiation processes together. While three or more spikes are required to probe this coupling, two spikes can never do so. We conclude that this coupling is critical to the presence of competitive dynamics and that multispike interactions are therefore vital to understanding synaptic competition.


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