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Title: Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Abstract

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the cognitive powers of the brain with comparable efficiency and density. To date, silicon-based three-terminal transistors and two-terminal memristors have been widely used in neuromorphic circuits, in large part due to their ability to co-locate information processing and memory. Yet these devices cannot achieve the interconnectivity and complexity of the brain because they are power-hungry, fail to mimic key synaptic functionalities, and suffer from high noise and high switching voltages. To overcome these limitations, we have developed and characterized a biomolecular memristor that mimics the composition, structure, and switching characteristics of biological synapses. Here, we describe the process of assembling and characterizing biomolecular memristors consisting of a 5 nm-thick lipid bilayer formed between lipid-functionalized water droplets in oil and doped with voltage-activated alamethicin peptides. While similar assembly protocols have been used to investigate biophysical properties of droplet-supported lipid membranes and membrane-bound ion channels, this article focuses on key modifications of the droplet interface bilayer method essential for achieving consistent memristor performance. Specifically, we describe the liposome preparation process and the incorporation of alamethicin peptides in lipid bilayer membranes, and themore » appropriate concentrations of each constituent as well as their impact on the overall response of the memristors. As a result, we also detail the characterization process of biomolecular memristors, including measurement and analysis of memristive current-voltage relationships obtained via cyclic voltammetry, as well as short-term plasticity and learning in response to step-wise voltage pulse trains.« less

Authors:
 [1];  [2];  [3];  [2];  [2];  [2]; ORCiD logo [4]; ORCiD logo [4];  [2]; ORCiD logo [5]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
  2. Univ. of Tennessee, Knoxville, TN (United States)
  3. Univ. of Kentucky, Lexington, KY (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  5. Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1557533
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Visualized Experiments
Additional Journal Information:
Journal Volume: 145; Journal Issue: 145; Journal ID: ISSN 1940-087X
Publisher:
MyJoVE Corp.
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; biomolecular memristor; alamethicin; memristor; ion channel; biomembrane; neuromorphic computing; lipid bilayer; synapse; synaptic mimic

Citation Formats

Najem, Joseph S., Taylor, Graham J., Armendarez, Nick, Weiss, Ryan J., Hasan, Md Sakib, Rose, Garrett S., Schuman, Catherine D., Belianinov, Alex, Sarles, Stephen A., and Collier, C. Patrick. Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes. United States: N. p., 2019. Web. doi:10.3791/58998.
Najem, Joseph S., Taylor, Graham J., Armendarez, Nick, Weiss, Ryan J., Hasan, Md Sakib, Rose, Garrett S., Schuman, Catherine D., Belianinov, Alex, Sarles, Stephen A., & Collier, C. Patrick. Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes. United States. doi:10.3791/58998.
Najem, Joseph S., Taylor, Graham J., Armendarez, Nick, Weiss, Ryan J., Hasan, Md Sakib, Rose, Garrett S., Schuman, Catherine D., Belianinov, Alex, Sarles, Stephen A., and Collier, C. Patrick. Tue . "Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes". United States. doi:10.3791/58998.
@article{osti_1557533,
title = {Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes},
author = {Najem, Joseph S. and Taylor, Graham J. and Armendarez, Nick and Weiss, Ryan J. and Hasan, Md Sakib and Rose, Garrett S. and Schuman, Catherine D. and Belianinov, Alex and Sarles, Stephen A. and Collier, C. Patrick},
abstractNote = {The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the cognitive powers of the brain with comparable efficiency and density. To date, silicon-based three-terminal transistors and two-terminal memristors have been widely used in neuromorphic circuits, in large part due to their ability to co-locate information processing and memory. Yet these devices cannot achieve the interconnectivity and complexity of the brain because they are power-hungry, fail to mimic key synaptic functionalities, and suffer from high noise and high switching voltages. To overcome these limitations, we have developed and characterized a biomolecular memristor that mimics the composition, structure, and switching characteristics of biological synapses. Here, we describe the process of assembling and characterizing biomolecular memristors consisting of a 5 nm-thick lipid bilayer formed between lipid-functionalized water droplets in oil and doped with voltage-activated alamethicin peptides. While similar assembly protocols have been used to investigate biophysical properties of droplet-supported lipid membranes and membrane-bound ion channels, this article focuses on key modifications of the droplet interface bilayer method essential for achieving consistent memristor performance. Specifically, we describe the liposome preparation process and the incorporation of alamethicin peptides in lipid bilayer membranes, and the appropriate concentrations of each constituent as well as their impact on the overall response of the memristors. As a result, we also detail the characterization process of biomolecular memristors, including measurement and analysis of memristive current-voltage relationships obtained via cyclic voltammetry, as well as short-term plasticity and learning in response to step-wise voltage pulse trains.},
doi = {10.3791/58998},
journal = {Journal of Visualized Experiments},
number = 145,
volume = 145,
place = {United States},
year = {2019},
month = {1}
}

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This content will become publicly available on January 1, 2020
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