Researchers at University of Limerick’s Bernal Institute worked with an international team of scientists to create a new type of organic material that learns from its past behaviour.

The discovery of the ‘dynamic molecular switch’ that emulate synaptic behaviour is revealed in a new study in the international journal Nature Materials.

The study was led by Damien Thompson, Professor of Molecular Modelling in UL’s Department of Physics and Director of SSPC, the UL-hosted Science Foundation Ireland Research Centre for Pharmaceuticals, together with Christian Nijhuis at the Centre for Molecules and Brain-Inspired Nano Systems in University of Twente and Enrique del Barco from University of Central Florida.

Working during lockdowns, the team developed a two-nanometre thick layer of molecules, which is 50,000 times thinner than a strand of hair and remembers its history as electrons pass through it.

Professor Thompson explained that the “switching probability and the values of the on/off states continually change in the molecular material, which provides a disruptive new alternative to conventional silicon-based digital switches that can only ever be either on or off.”

The newly discovered dynamic organic switch displays all the mathematical logic functions necessary for deep learning, successfully emulating Pavlovian ‘call and response’ synaptic brain-like behaviour.

The researchers demonstrated the new materials properties using extensive experimental characterisation and electrical measurements supported by multi-scale modelling spanning from predictive modelling of the molecular structures at the quantum level to analytical mathematical modelling of the electrical data.

To emulate the dynamical behaviour of synapses at the molecular level, the researchers combined fast electron transfer (akin to action potentials and fast depolarization processes in biology) with slow proton coupling limited by diffusion (akin to the role of biological calcium ions or neurotransmitters).

Since the electron transfer and proton coupling steps inside the material occur at very different time scales, the transformation can emulate the plastic behaviour of synapse neuronal junctions, Pavlovian learning, and all logic gates for digital circuits, simply by changing the applied voltage and the duration of voltage pulses during the synthesis, they explained.

“This was a great lockdown project, with Chris, Enrique and I pushing each other through zoom meetings and gargantuan email threads to bring our teams combined skills in materials modelling, synthesis and characterisation to the point where we could demonstrate these new brain-like computing properties,” explained Professor Thompson.

“The community has long known that silicon technology works completely differently to how our brains work and so we used new types of electronic materials based on soft molecules to emulate brain-like computing networks.”

The researchers explained that the method can in the future be applied to dynamic molecular systems driven by other stimuli such as light and coupled to different types of dynamic covalent bond formation.

This breakthrough opens up a whole new range of adaptive and reconfigurable systems, creating new opportunities in sustainable and green chemistry, from more efficient flow chemistry production of drug products and other value-added chemicals to development of new organic materials for high density computing and memory storage in big data centres.

“This is just the start. We are already busy expanding this next generation of intelligent molecular materials, which is enabling development of sustainable alternative technologies to tackle grand challenges in energy, environment, and health,” explained Professor Thompson.

Professor Norelee Kennedy, Vice President Research at UL, said: “Our researchers are continuously finding new ways of making more effective, more sustainable materials. This latest finding is very exciting, demonstrating the reach and ambition of our international collaborations and showcasing our world-leading ability at UL to encode useful properties into organic materials.”

Magnets generate invisible fields that attract certain materials. A common example is fridge magnets. Far more important to our everyday lives, magnets also can store data in computers. Exploiting the direction of the magnetic field (say, up or down), microscopic bar magnets each can store one bit of memory as a zero or a one — the language of computers.

Scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory want to replace the bar magnets with tiny magnetic vortices. As tiny as billionths of a meter, these vortices are called skyrmions, which form in certain magnetic materials. They could one day usher in a new generation of microelectronics for memory storage in high performance computers.

“The bar magnets in computer memory are like shoelaces tied with a single knot; it takes almost no energy to undo them,” said Arthur McCray, a Northwestern University graduate student working in Argonne’s Materials Science Division (MSD). And any bar magnets malfunctioning due to some disruption will affect the others.

“By contrast, skyrmions are like shoelaces tied with a double knot. No matter how hard you pull on a strand, the shoelaces remain tied.” The skyrmions are thus extremely stable to any disruption. Another important feature is that scientists can control their behavior by changing the temperature or applying an electric current.

Scientists have much to learn about skyrmion behavior under different conditions. To study them, the Argonne-led team developed an artificial intelligence (AI) program that works with a high-power electron microscope at the Center for Nanoscale Materials (CNM), a DOE Office of Science user facility at Argonne. The microscope can visualize skyrmions in samples at very low temperatures.

The team’s magnetic material is a mixture of iron, germanium and tellurium. In structure, this material is like a stack of paper with many sheets. A stack of such sheets contains many skyrmions, and a single sheet can be peeled from the top and analyzed at facilities like CNM.

“The CNM electron microscope coupled with a form of AI called machine learning enabled us to visualize skyrmion sheets and their behavior at different temperatures,” said Yue Li, a postdoctoral appointee in MSD.

“Our most intriguing finding was that the skyrmions are arranged in a highly ordered pattern at minus 60 degrees Fahrenheit and above,” said Charudatta Phatak, a materials scientist and group leader in MSD. ?”But as we cool the sample the skyrmion arrangement changes.” Like bubbles in beer foam, some skyrmions became larger, some smaller, some merge and some vanish.

At minus 270, the layer reached a state of nearly complete disorder, but order came back when the temperature returned to minus 60. This order-disorder transition with temperature change could be exploited in future microelectronics for memory storage.

“We estimate the skyrmion energy efficiency could be 100 to 1000 times better than current memory in the high performance computers used in research,” McCray said.

Energy efficiency is essential to the next generation of microelectronics. Today’s microelectronics already account for roughly 10% of the world’s electricity. And that number could double by 2030. More energy-efficient electronics must be found.

“We have a way to go before skyrmions find their way into any future computer memory with low power,” Phatak said. ?”Nonetheless, this kind of radical new way of thinking about microelectronics is key to next generation devices.”

This research was supported by the DOE Office of Basic Energy Sciences. The team’s machine learning program was run on supercomputing resources at the Argonne Leadership Computing Facility, a DOE Office of Science user facility.

This research appeared in Nano Letters. In addition to Phatak, Li, and McCray, Argonne authors include Amanda K. Petford-Long, Daniel P. Phelan and Xuedan Ma. Other authors include Rabindra Basnet, Krishna Pandey and Jin Hu from the University of Arkansas.

The affected proteins are known as actins, which are highly abundant and have multiple roles that include helping every cell unite its contents, maintain its shape, divide and migrate. Actins assemble into thread-like filaments to do certain work inside cells.

Researchers found that two toxins produced by the Vibrio genus of bacteria cause actins to start joining together into these filaments — which could be thought of as cellular highways on which cargo is delivered — at the wrong location inside cells, and headed in the wrong direction.

“Growing in the wrong direction is a totally new function that was not previously known and was not thought to be possible for actin filaments inside the cell,” said senior author Dmitri Kudryashov, associate professor of chemistry and biochemistry at The Ohio State University. “A large fraction of actin in the cell is consumed in formation of the ‘highways’ where they are not needed, so the cell resources are wasted and cannot be used to satisfy the cell’s basic needs.”

The research is published today (Nov. 18, 2022) in the journal Science Advances.

These disruptive toxins are called VopF and VopL, and are produced by two strains of Vibrio bacteria living in seawater: V. cholerae and V. parahaemolyticus, both of which can contaminate oysters and other shellfish that, when eaten raw, make people sick.

In this study, the research team zeroed in on describing the unexpected cellular activities rather than any further implications, such as how the hijacking relates to bacterial infection.

“We are looking at the interference at the molecular level — we have not focused here on how this cell function might affect humans,” said first and co-corresponding author Elena Kudryashova, a research scientist in chemistry and biochemistry at Ohio State.

“From a practical standpoint, this tells us more about these pathogens, and knowing your enemy helps you fight your enemy,” she said. “But finding something that we didn’t know was possible — for actin to behave in such a way inside the cell — raises new questions about whether this function might actually be needed, or could come about in some other way.”

Until now, actins have been known to assemble each filament in one way, originating from what is known as its pointed end and directed toward what is called the barbed end of the structure. Because they are limited in number, the actins disassemble as needed from the pointed end and are recycled to maintain directional activity toward the barbed end — and then these actin filaments perform functions, such as cell migration, contraction or division, as dictated by what the cell commands.

When the VopF and VopL toxins enter a cell, however, they attract actin molecules to start a new filament and cause the filaments to start assembling in this spot, which leads them to elongate in the direction of the pointed end — a reversal of their usual elongation direction.

“The toxins start making these actin filament highways in the wrong place, building something that is useless for the cell, and the cell doesn’t know how to deal with it,” Kudryashov said.

This actin interference was observed using imaging of live cells containing individual toxin molecules. Though they don’t yet know all the consequences of this hijacking activity, the researchers said the results could include seepage of nutrients through damaged intestinal walls — which would provide food for the infectious bacteria waiting outside.

“Killing cells is not always necessary — disrupting cells’ barrier function can also be beneficial to pathogens,” Kudryashova said.

And that’s why the scientists want to learn more — whether other molecules can force actins to assemble “roads to nowhere,” and whether that strange filament formation might even be a beneficial mechanism under a different set of circumstances.

“It’s quite possible that our own cells are doing this on some occasion, but we don’t know because actin has so many functions and not all of them are yet well understood,” Kudryashov said.

The Ohio State team collaborated with co-authors Ankita, Heidi Ulrichs and Shashank Shekhar of Emory University.

This work was supported by grants from the National Institutes of Health.

“The brain is very busy when we sleep, repeating what we have learned during the day,” said Maxim Bazhenov, PhD, professor of medicine and a sleep researcher at University of California San Diego School of Medicine. “Sleep helps reorganize memories and presents them in the most efficient way.”

In previous published work, Bazhenov and colleagues have reported how sleep builds rational memory, the ability to remember arbitrary or indirect associations between objects, people or events, and protects against forgetting old memories.

Artificial neural networks leverage the architecture of the human brain to improve numerous technologies and systems, from basic science and medicine to finance and social media. In some ways, they have achieved superhuman performance, such as computational speed, but they fail in one key aspect: When artificial neural networks learn sequentially, new information overwrites previous information, a phenomenon called catastrophic forgetting.

“In contrast, the human brain learns continuously and incorporates new data into existing knowledge,” said Bazhenov, “and it typically learns best when new training is interleaved with periods of sleep for memory consolidation.”

Writing in the November 18, 2022 issue of PLOS Computational Biology, senior author Bazhenov and colleagues discuss how biological models may help mitigate the threat of catastrophic forgetting in artificial neural networks, boosting their utility across a spectrum of research interests.

The scientists used spiking neural networks that artificially mimic natural neural systems: Instead of information being communicated continuously, it is transmitted as discrete events (spikes) at certain time points.

They found that when the spiking networks were trained on a new task, but with occasional off-line periods that mimicked sleep, catastrophic forgetting was mitigated. Like the human brain, said the study authors, “sleep” for the networks allowed them to replay old memories without explicitly using old training data.

Memories are represented in the human brain by patterns of synaptic weight — the strength or amplitude of a connection between two neurons.

“When we learn new information,” said Bazhenov, “neurons fire in specific order and this increases synapses between them. During sleep, the spiking patterns learned during our awake state are repeated spontaneously. It’s called reactivation or replay.

“Synaptic plasticity, the capacity to be altered or molded, is still in place during sleep and it can further enhance synaptic weight patterns that represent the memory, helping to prevent forgetting or to enable transfer of knowledge from old to new tasks.”

When Bazhenov and colleagues applied this approach to artificial neural networks, they found that it helped the networks avoid catastrophic forgetting.

“It meant that these networks could learn continuously, like humans or animals. Understanding how human brain processes information during sleep can help to augment memory in human subjects. Augmenting sleep rhythms can lead to better memory.

“In other projects, we use computer models to develop optimal strategies to apply stimulation during sleep, such as auditory tones, that enhance sleep rhythms and improve learning. This may be particularly important when memory is non-optimal, such as when memory declines in aging or in some conditions like Alzheimer’s disease.”

Co-authors include: Ryan Golden and Jean Erik Delanois, both at UC San Diego; and Pavel Sanda, Institute of Computer Science of the Czech Academy of Sciences.

About 443 million years ago, life on Earth was undergoing the Late Ordovician mass extinction, or LOME, which eliminated about 85% of marine species. Scientists have long studied this mass extinction and continue to investigate its possible causes, such as reduced habitat loss in a rapidly cooling world or persistent low-oxygen conditions in the oceans.

By measuring isotopes of the element thallium — which shows special sensitivity to changes in oxygen in the ancient marine environment — the research team found that previously documented patterns of this mass extinction coincided with an initial rapid decrease in marine oxygen levels followed by a rapid increase in oxygen. Their work is published online in the journal Science Advances.

“Paleontologists have noted that there were several groups of organisms, such as graptolites and brachiopods, that started to decline very early in this mass extinction interval, but we didn’t really have any good evidence of an environmental or climate signature to tie that early decline of these groups to a particular mechanism,” said co-author Seth Young, an associate professor in the Department of Earth, Ocean and Atmospheric Science. “This paper can directly link that early phase of extinction to changes in oxygen. We see a marked change in thallium isotopes at the same time these organisms start their steady decline into the main phase of the mass extinction event.”

That decrease in oxygen was immediately followed by an increase. This rapid shift in oxygen coincided with the traditional first die-off of mass extinction and major ice sheet growth over the ancient South Pole.

“Turbulence in oxygen levels in oceanic waters is really what seems to have been pretty problematic for organisms that were living in the Late Ordovician at that time, which might have been adapted to cope with low oxygen conditions initially or vice versa,” Young said. “The fact that oxygen levels in the oceans next to the continents switching back and forth over short geologic time scales (a few hundred thousand years) really did seem to play havoc with these marine ecosystems.”

The Late Ordovician extinction was one of five major mass extinctions in Earth’s history and the only one scientists are confident took place in what are called “icehouse” conditions, in which widespread ice sheets are present on Earth’s surface. Earth is currently experiencing icehouse conditions and loss of biodiversity, which makes this ancient mass extinction an important analog for present-day conditions, along with trying to understand Earth’s future as our climate continues to warm and ice sheets recede.

Previous research into environmental conditions surrounding the LOME used evidence found in limestones from more oxygenated settings, but this study used shales that were deposited in deeper, oxygen-poor water, which record different geochemical signatures, allowing the researchers to make conclusions about global marine conditions, rather than for local conditions.

“The discovery of the initial expansion of low-oxygen conditions on a global level and the coincidence with the early phases of decline in marine animals helps paint a clearer picture of what was happening with this extinction event,” said lead author Nevin Kozik, a visiting assistant professor at Occidental College and former FSU doctoral student.

Co-authors on this paper were doctoral student Sean Newby and associate professor Jeremy Owens of FSU; former FSU postdoctoral scholar and current assistant professor at the College of Charleston Theodore Them; Mu Liu and Daizhao Chen of the Chinese Academy of Sciences; Emma Hammarlund of Lund University; and David Bond of the University of Hull.

This research was supported by the National Science Foundation, the American Chemical Society, the Sloan Research Foundation and the Geological Society of America.

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Materials provided by Florida State University. Original written by Bill Wellock. Note: Content may be edited for style and length.