Literature DB >> 24960611

Neuronal synapse as a memristor: modeling pair- and triplet-based STDP rule.

Weiran Cai, Frank Ellinger, Ronald Tetzlaff.   

Abstract

We propose a new memristive model for the neuronal synapse based on the spike-timing-dependent plasticity (STDP) protocol, considering both long-term and short-term plasticity in the synapse. Higher-order behavior is modeled by a memristor with adaptive thresholds, which realizes the well-established suppression principle of Froemke. We assume a mechanism of variable thresholds adapting to synaptic potentiation (LTP) and depression (LTD), which reproduces the refractory time in the weight modification. The corresponding dynamical process is governed by a set of ordinary differential equations. Interestingly, the Froemke's model and our memristive model, based on two completely different mechanisms, are found to be quantitatively equivalent for the 'pre-post-pre' case and 'post-pre-post' case. A relation of the adaptive thresholds to short-term plasticity is addressed.

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Year:  2014        PMID: 24960611     DOI: 10.1109/TBCAS.2014.2318012

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  2 in total

1.  Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices.

Authors:  Zhongqiang Wang; Tao Zeng; Yanyun Ren; Ya Lin; Haiyang Xu; Xiaoning Zhao; Yichun Liu; Daniele Ielmini
Journal:  Nat Commun       Date:  2020-03-20       Impact factor: 14.919

2.  Time and rate dependent synaptic learning in neuro-mimicking resistive memories.

Authors:  Taimur Ahmed; Sumeet Walia; Edwin L H Mayes; Rajesh Ramanathan; Vipul Bansal; Madhu Bhaskaran; Sharath Sriram; Omid Kavehei
Journal:  Sci Rep       Date:  2019-10-28       Impact factor: 4.379

  2 in total

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