Literature DB >> 25373422

Multiprotocol-induced plasticity in artificial synapses.

Vladimir Kornijcuk1, Omid Kavehei, Hyungkwang Lim, Jun Yeong Seok, Seong Keun Kim, Inho Kim, Wook-Seong Lee, Byung Joon Choi, Doo Seok Jeong.   

Abstract

We suggest a 'universal' electrical circuit for the realization of an artificial synapse that exhibits long-term plasticity induced by different protocols. The long-term plasticity of the artificial synapse is basically attributed to the nonvolatile resistance change of the bipolar resistive switch in the circuit. The synaptic behaviour realized by the circuit is termed 'universal' inasmuch as (i) the shape of the action potential is not required to vary so as to implement different plasticity-induction behaviours, activity-dependent plasticity (ADP) and spike-timing-dependent plasticity (STDP), (ii) the behaviours satisfy several essential features of a biological chemical synapse including firing-rate and spike-timing encoding and unidirectional synaptic transmission, and (iii) both excitatory and inhibitory synapses can be realized using the same circuit but different diode polarity in the circuit. The feasibility of the suggested circuit as an artificial synapse is demonstrated by conducting circuit calculations and the calculation results are introduced in comparison with biological chemical synapses.

Mesh:

Year:  2014        PMID: 25373422     DOI: 10.1039/c4nr03405h

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  3 in total

Review 1.  Plasticity in memristive devices for spiking neural networks.

Authors:  Sylvain Saïghi; Christian G Mayr; Teresa Serrano-Gotarredona; Heidemarie Schmidt; Gwendal Lecerf; Jean Tomas; Julie Grollier; Sören Boyn; Adrien F Vincent; Damien Querlioz; Selina La Barbera; Fabien Alibart; Dominique Vuillaume; Olivier Bichler; Christian Gamrat; Bernabé Linares-Barranco
Journal:  Front Neurosci       Date:  2015-03-02       Impact factor: 4.677

2.  A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

Authors:  Zhongqiang Wang; Stefano Ambrogio; Simone Balatti; Daniele Ielmini
Journal:  Front Neurosci       Date:  2015-01-15       Impact factor: 4.677

3.  Scalable excitatory synaptic circuit design using floating gate based leaky integrators.

Authors:  Vladimir Kornijcuk; Hyungkwang Lim; Inho Kim; Jong-Keuk Park; Wook-Seong Lee; Jung-Hae Choi; Byung Joon Choi; Doo Seok Jeong
Journal:  Sci Rep       Date:  2017-12-14       Impact factor: 4.379

  3 in total

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