Synapse-inspired variable conductance in biomembranes: A preliminary study

Joseph S. Najem, Graham J. Taylor, Charles P. Collier, Stephen A. Sarles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Memristors are solid-state devices that exhibit voltagecontrolled conductance. This tunable functionality enables the implementation of biologically-inspired synaptic functions in solid-state neuromorphic computing systems. However, while memristors are meant to emulate an intricate signal transduction process performed by soft biomolecular structures, they are commonly constructed from silicon- or polymer-based materials. As a result, the volatility, intricate design, and high-energy resistance switching in memristive devices, usually, leads to energy consumption in memristors that is several orders of magnitude higher than in natural synapses. Additionally, solidstate memristors fail to achieve the coupled dynamics and selectivity of synaptic ion exchange that are believed to be necessary for initiating both short- and long-term potentiation (STP and LTP) in neural synapses, as well as paired-pulse facilitation (PPF) in the presynaptic terminal. LTP is a phenomenon mostly responsible for driving synaptic learning and memory, features that enable signal transduction between neurons to be history-dependent and adaptable. In contrast, current memristive devices rely on engineered external programming parameters to imitate LTP. Because of these.

Original languageEnglish (US)
Title of host publicationDevelopment and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791858257
DOIs
StatePublished - Jan 1 2017
EventASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017 - Snowbird, United States
Duration: Sep 18 2017Sep 20 2017

Publication series

NameASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017
Volume1

Other

OtherASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017
CountryUnited States
CitySnowbird
Period9/18/179/20/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

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