Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

• Published in: Scientific reports Vol. 6; no. 1; p. 39216
• Main Authors: La Barbera, Selina, Vincent, Adrien F., Vuillaume, Dominique, Querlioz, Damien, Alibart, Fabien
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 16.12.2016; Nature Publishing Group
• Subjects: 639/766/1130/2798; 639/925/927/1007; Brain research; Circuits; Computer science; Computer Simulation; Data processing; Electrodes; Firing pattern; Humanities and Social Sciences; Learning; Memory; Models, Neurological; Motion detection; multidisciplinary; Neuronal Plasticity - physiology; Neurons - physiology; Oxidation; Science; Short term; Synaptic plasticity
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep39216

Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.