Name: assembly and characterization of biomolecular memristors consisting of ion channel-doped lipid membranes
Uploaded: 2019-03-09T15:00:00
Description: Watch this Scientific Journal Video about Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes at JoVE.com

Financial support was provided by the National Science Foundation Grant NSF ECCS-1631472. Research for G.J.T., C.D.S., A.B., and C.P.C. was partially sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy. A portion of this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.&#160;

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This paper presents a protocol for assembling and characterizing biomolecular memristors based on ion channel-doped synthetic biomembranes formed between two droplets of water in oil. The soft-matter, two-terminal device is designed and studied to: 1) overcome constraints that are associated with solid-state technology, such as high noise, high energy consumption, and high switching voltages, 2) more closely mimic the composition, structure, switching mechanisms of biological synapses, and 3) explore the mechanisms and f...

It is widely recognized that biological synapses are responsible for the high efficiency and enormous parallelism of the brain due to their ability to learn and process information in highly adaptive ways. This coordinated functionality emerges from multiple, highly complex molecular mechanisms that drive both short-term and long-term synaptic plasticity1,2,3,4,5. Neuromorphic computing systems aim to emulate synaptic functionalities at levels approaching the density, complexity, and energy efficiency of the brain, which are needed for the next generation of brain-like computers6,7,8. However, reproducing synaptic features using traditional electronic circuit elements is virtually impossible9, instead requiring the design and fabrication of new hardware elements that can adapt to incoming signals and remember information histories9. These types of synapse-inspired hardware are known as mem-elements9,10,11 (short for memory elements), which, according to Di Ventra et al.9,11, are passive, two-terminal devices whose resistance, capacitance, or inductance can be reconfigured in response to external stimuli, and which can remember prior states11. To achieve energy consumption levels approaching those in the brain, these elements should employ similar materials and mechanisms for synaptic plasticity12.
To date, two-terminal memristors13,14,15 have predominantly been built using complementary metal-oxide-semiconductor (CMOS) technology, characterized by high-switching voltages and high noise. This technology does not scale well due to high power consumption and low density. To address these limitations, multiple organic and polymeric memristors have been recently built. However, these devices exhibit significantly slower switching dynamics due to time-consuming ion diffusion through a conductive polymer matrix16,17. As a result, the mechanisms by which both CMOS-based and organic memristive devices emulate synapse-inspired functionalities are highly phenomenological, encompassing only a few synaptic functionalities such as Spike Timing Dependent Plasticity (STDP)18, while overlooking other key features that also play essential roles in making the brain a powerful and efficient computer, such as pre-synaptic, short-term plasticity19.&#160;
Recently, we introduced a new class of memristive devices12 featuring voltage-activated peptides incorporated in biomimetic lipid membranes that mimics the biomolecular composition, membrane structure, and ion channel triggered switching mechanisms of biological synapses20.&#160; Here, we describe how to assemble and electrically interrogate these two-terminal devices, with specific focus on how to evaluate short-term plasticity for implementation in online learning applications12. Device assembly is based on the droplet interface bilayer (DIB)21 method, which has been used extensively in recent years to study the biophysics of model membranes21 and membrane-bound ion channels22,23,24, and as building blocks for the development of stimuli-responsive materials25,26. We describe the membrane assembly and interrogation process in detail for those interested in neuromorphic applications but have limited experience in biomaterials or membrane biology. The protocol also includes a full description of the characterization procedure, which is as important as the assembly process, given the dynamic and reconfigurable electrical properties of the device27. The procedure and representative results described here are foundations for a new class of low-cost, low-power, soft mem-elements based on lipid interfaces and other biomolecules for applications in neuromorphic computing, autonomous structures and systems, and even adaptive brain-computer interfaces.

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			<td style="width:183px;">850356P/850356C</td>
			<td style="width:663px;">Purchased as lyophilized powder (P) or in chloroform (C)&#160;</td>
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			<td style="width:183px;">610000</td>
			<td>This includes a mini-extruder, 2 syringes, 100 PC membranes, 100 filter supports, and 1 holder/heating block</td>
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assembly and characterization of biomolecular memristors consisting of ion channel-doped lipid membranes

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. 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.

Figure 1 displays the experimental setup used to assemble and characterize the biomolecular memristor. Lowering the free ends of the electrodes to the bottom of the oil reservoir, as shown in Figure 1b, was found helpful to minimize vibrations of the electrodes and droplets that can result in variations in measured current and bilayer area, especially in cases where heating the oil can generate convective flow in the oil. Figure 2 s...

Watch this Scientific Journal Video about Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes at JoVE.com

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

Soft, low-power, biomolecular memristors leverage similar composition, structure, and switching mechanisms of bio-synapses. Presented here is a protocol to assemble and characterize biomolecular memristors obtained from insulating lipid bilayers formed between water droplets in oil. The incorporation of voltage-activated alamethicin peptides results in memristive ionic conductance across the membrane.

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the ...

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