Synaptic plasticity, metaplasticity and memory effects in hybrid organic–inorganic bismuth-based materials

Abstract

Since the discovery of memristors, their application in computing systems utilizing multivalued logic and a neuromimetic approach is of great interest. A thin film device made of methylammonium bismuth iodide exhibits a wide variety of neuromorphic effects simultaneously, and is thus able to mimic synaptic behaviour and learning phenomena. Standard learning protocols, such as spike-timing dependent plasticity and spike-rate dependent plasticity might be further modulated via metaplasticity in order to amplify or alter changes in the synaptic weight. Moreover, transfer of information from short-term to long-term memory is observed. These effects show that the diversity of functions of memristive devices can be strongly affected by the pre-treatment of the sample. Modulation of the resistive switching amplitude is of great importance for the application of memristive elements in computational applications, as additional sub-states might be utilized in multi-valued logic systems and metaplasticity and memory consolidation will contribute to the development of more efficient bioinspired computational schemes.