
image: A pure lipid membrane formed using lipid-coated water droplets exhibits long-term potentiation, or LTP, associated with learning and memory, mimicking hippocampal LTP seen in mammalian brain and birds.
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Credit: Credit: Jill Hemman/ORNL, US Dept. of Energy
While studying how bio-inspired materials could inform the design of next-generation computers, scientists at the Department of Energy’s Oak Ridge National Laboratory have come up with a one-of-a-kind result that could have big implications for the future. times for advanced computing and human health.
Results published in Proceedings of the National Academy of Sciences show that an artificial cell membrane is capable of long-term potentiation, or LTP, a hallmark of biological learning and memory. This is the first evidence that a cell membrane alone – without proteins or other biomolecules embedded within – is capable of LTP that persists for many hours. It is also the first identified nanoscale structure in which memory can be encoded.
“When the facilities were closed due to COVID, it led us to move away from our usual membrane research,” said John Katsaras, a biophysicist in ORNL’s Neutron Science Branch who specializes in scattering membranes. neutrons and the study of biological membranes at ORNL. “With post-doctoral fellow Haden Scott, we decided to revisit a system previously studied by Pat Collier and colleagues, this time with an entirely different electrical stimulation protocol that we called ‘training’.” This ultimately led to data virtually indistinguishable from the LTP signal seen in the human brain.
Memory encoding in nanoscale systems has the potential to advance the development of next-generation computing materials and architectures that seek to match the efficiency and flexibility of human cognition – known as neuromorphic computing name. While the implications for artificial intelligence may be obvious, brain-like computing will also dramatically change the power efficiency and computing capabilities of next-generation devices.
“Memory and logic in the brain are closely linked,” said Collier, a research scientist at the Center for Nanophase Materials Sciences, a DOE Office of Science user facility at ORNL where the research was performed. “But in modern computers, these functions happen in different places – a bottleneck that the brain doesn’t have.”
Even today’s supercomputers have separate slots for processing and memory. By merging these functions, neuromorphic computers could help keep pace with exponentially growing data sets that are becoming increasingly complex as the Internet of Things, or IoT, and device interconnectivity become commonplace in homes and workspaces. It would also greatly advance edge computing, the ability for a device to do its own logic at the data collection site, without having to send information to a central server or cloud.
Additionally, scientists have yet to identify a nanoscale structure in the brain where memory is stored. Large sections of the brain, such as the hippocampus, are known to store memory, but much remains unknown about where memory is stored in the hippocampus and the molecular mechanisms responsible for it. Importantly, cell membranes have been overlooked as structures in which information could be encoded, even though lipids, a major component of membranes, make up most of the brain’s mass.
The unexpected result of making LTP in a pure lipid membrane will initiate a re-examination of where and how memory is stored in a living brain. If neural cell membranes prove to be a key feature of human memory, it could lead to new treatments for the more than one billion people worldwide who live with neurological disorders.
“If neurobiologists can find evidence of this in the brain, it could have dramatic impacts on how we understand dementia and learning,” Katsaras said. “Importantly, the membrane may offer a new therapeutic target for brain diseases that do not respond to protein-targeting drugs.
The nanoscale systems used in this study create an artificial membrane by bringing together two micron-sized lipid-coated water droplets in an oil suspension. At the interface between the two droplets, a lipid bilayer forms that mimics the cell membranes of neuronal synapses in the human brain.
Previous ORNL research has shown that this biomembrane system is able to store electrical charge, but only for short periods of time. In the new study, the presence of LTP means there are new avenues for how this system of flexible materials could be used in neuromorphic devices or how it could serve as a model for building semiconductor devices with similar characteristics.
“Now that we have begun to define the electrical protocols to induce LTP in lipid bilayer membranes, we are preparing to create two-terminal crossbar architectures in which multiple nanoscale membranes interact, allowing active logic to be performed , not just passive storage,” Collier said. “Right now we’re using unique systems; in the future, we need to learn how to connect them together.
In addition to partnering with neurobiologists to explore the biomedical implications of this discovery, future neuromorphic computational work on the biomembrane system will involve simulations and the use of ORNL’s neutron leadership facilities and computing.
“What we’re seeing are serendipitous findings that came from somewhat curiosity-driven research conducted during the pandemic,” Collier said. “But this is an important discovery for neuromorphic computing. We don’t know exactly how this will work, but that’s the fun part.
The journal article is published under the title “Evidence for long-term potentiation in phospholipid membranes”.
The research was supported by the DOE Office of Science. Data collection and analysis was performed at CNMS, while all samples were prepared at the University of Tennessee Shull Wollan Center, located at ORNL.
UT-Battelle manages the ORNL for the DOE Office of Science. The largest supporter of basic physical science research in the United States, the Office of Science works to address some of the most pressing challenges of our time. For more information, please visit https://www.energy.gov/science.
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Proceedings of the National Academy of Sciences
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