A study led by researchers from the Human Nutrition Unit at the Universitat Rovira i Virgili (URV), the Pere Virgili Health Research Institute (IISPV) and CIBERobn points to a meaningful link between extra virgin olive oil, gut bacteria, and brain health.

Study explores olive oil, gut microbiome, and brain health

“This is the first prospective study in humans to specifically analyze the role of olive oil in the interaction between gut microbiota and cognitive function,” explains Jiaqi Ni, first author of the article and researcher at the URV’s Department of Biochemistry and Biotechnology.

The research followed 656 adults between the ages of 55 and 75 who were overweight or obese and had metabolic syndrome — a set of risk factors that increase the likelihood of developing cardiovascular disease. Over a two-year period, as part of the PREDIMED-Plus project, scientists tracked participants’ diets, including their intake of virgin and refined olive oil, along with detailed analyses of their gut microbiota. They also monitored changes in cognitive performance over time.

Virgin olive oil linked to better cognition and gut diversity

The findings showed clear differences depending on the type of olive oil consumed. Participants who regularly used virgin olive oil experienced improvements in cognitive function and had a more diverse gut microbiota, which is widely considered a sign of better intestinal and metabolic health. In contrast, those who consumed refined olive oil tended to show a decline in microbiota diversity over time.

Researchers also identified a specific group of gut bacteria, known as Adlercreutzia, that may be tied to these benefits. Its presence could serve as an indicator of the positive relationship between virgin olive oil consumption and preserved cognitive function. These results suggest that part of the oil’s brain-supporting effect may come from how it reshapes the gut microbiome.

Why extra virgin olive oil stands out

The difference between extra virgin and refined olive oil largely comes down to how they are produced. Extra virgin olive oil is obtained using mechanical methods, which help preserve its natural compounds. Refined olive oil, on the other hand, undergoes industrial processing to remove impurities.

While this refining process improves shelf life and taste consistency, it also reduces beneficial components such as antioxidants, polyphenols, vitamins and other bioactive substances. According to Jiaqi Ni, “not all olive oils have benefits for cognitive function,” highlighting the importance of choosing extra virgin varieties.

Quality of dietary fats matters for brain health

These findings add to growing evidence that diet plays a key role in both cardiovascular and cognitive health through its influence on the gut microbiota. Jordi Salas-Salvadó, principal investigator of the study, emphasizes the importance of choosing high-quality fats: “This research reinforces the idea that the quality of the fat we consume is as important as the quantity; extra virgin olive oil not only protects the heart, but can also help preserve the brain during aging.”

He also notes that identifying a specific microbial profile linked to these benefits “paves the way for new nutrition-based prevention strategies to preserve cognitive functions.”

A simple dietary change for an aging population

Co-directors Nancy Babio and Stephanie Nishi highlight the broader implications of the findings as populations continue to age. “At a time when cases of cognitive decline and dementia are on the rise, our findings drive home the importance of improving diet quality, and in particular prioritizing extra virgin olive oil over other refined versions as an effective, simple and accessible strategy for protecting brain health.”

The study was led by the Human Nutrition Unit at the URV’s Department of Biochemistry and Biotechnology, with contributions from the Pere Virgili Health Research Institute (IISPV-CERCA) and the CIBER area on the Physiopathology of Obesity and Nutrition (CIBEROBN) of the Carlos III Health Institute. Researchers from the PREDIMED-Plus consortium also participated, along with collaborators from international institutions including Wageningen (Netherlands) and Harvard (United States).

“The idea with this project was to find some cognitive way of getting the ants to consume more of the poisonous baits we put in the field,” says the first author and doctoral researcher Henrique Galante, a computational biologist at the University of Regensburg. “We found that intermediate doses of caffeine actually boost learning — when you give them a bit of caffeine, it pushes them into having straighter paths and being able to reach the reward faster.”

Argentine ants are among the most damaging and expensive invasive species worldwide. Efforts to control them typically rely on poisoned bait, but these strategies often fall short. Colonies may ignore the bait or abandon it before it spreads widely. The research team explored whether caffeine, which is already known to enhance learning in bees, could help ants better remember bait locations and lead more nestmates to them.

“We’re trying to make them better at finding these baits, because the faster they go and come back to them, the more pheromone trails they lay, the more ants will come, and, therefore, the faster they will spread the poison in the colony before they realize it’s poison,” says Galante.

Testing Caffeine’s Effects in the Lab

To investigate this idea, the scientists designed a controlled experiment using different caffeine levels. Ants crossed a small Lego drawbridge onto a test surface, which consisted of an A4 sheet placed over acrylic. There, they encountered a drop of sugar solution containing 0, 25 ppm, 250 ppm, or 2,000 ppm of caffeine.

“The lowest dose we used is what you find in natural plants, the intermediate dose is similar to what you would find in some energy drinks, and the highest amount is set to be the LD50 of bees — where half the bees fed this dose die — so it’s likely to be quite toxic for them,” says Galante.

The team tracked each ant’s movement with an automated system, measuring both travel time and how direct their paths were. In total, 142 ants took part, and each one completed four trials. Between trials, the ants could unload their collected food, and the testing surface was replaced to prevent them from following their own pheromone trails.

Straighter Paths, Faster Learning

Ants that received only sugar showed little improvement over time, indicating they were not learning the reward’s location effectively. In contrast, ants given low or moderate amounts of caffeine quickly became more efficient.

For ants exposed to 25 ppm of caffeine, foraging time decreased by 28 percent with each visit. At 250 ppm, the improvement reached 38 percent. For example, an ant that initially took 300 seconds to reach the reward could cut that time to 113 seconds at the lower dose and just 54 seconds at the intermediate dose by the final trial. The highest caffeine level did not produce the same benefit.

Focus Over Speed

The improvement was not due to increased speed. Instead, caffeinated ants followed more direct routes, suggesting stronger focus and better spatial memory. Their pace remained unchanged across all doses, but their paths became less winding at the lower and intermediate levels of caffeine.

“What we see is that they’re not moving faster, they’re just being more focused on where they’re going,” says Galante. “This suggests that they know where they want to go, therefore, they have learned the locations of the reward.”

Caffeine did not affect how efficiently ants returned to their nest (how efficiently they traveled back to the nest), although all ants improved slightly over time regardless of caffeine.

A Potential New Tool for Pest Control

The findings suggest that caffeine could play a role in improving pest control strategies for Argentine ants. By helping ants learn bait locations more quickly and recruit more nestmates, caffeine could increase how effectively poison spreads through a colony before the ants detect it.

The researchers caution that more work is needed before applying this approach in real-world settings. Ongoing studies are testing caffeine-enhanced bait in outdoor environments in Spain and examining how caffeine interacts with the poison itself.

This research was supported by the European Research Council, the Deutsche Forschungsgemeinschaft, and the University of Regensburg.

In experiments using slices of mouse brain, the artificial neurons successfully triggered responses in real neurons. This result shows a new level of compatibility between electronic devices and living neural systems.

Toward Brain Interfaces and Energy-Efficient AI

This advance moves researchers closer to electronics that can directly interface with the nervous system. Potential uses include brain-machine interfaces and neuroprosthetics, such as implants that could help restore hearing, vision, or movement.

The technology also points toward a new generation of computing systems inspired by the brain. By replicating how neurons communicate, future hardware could perform complex tasks using far less energy. The brain remains the most energy-efficient computing system known, and scientists hope to apply its principles to modern technology.

The study will be published on April 15 in the journal Nature Nanotechnology.

“The world we live in today is dominated by artificial intelligence (AI),” said Northwestern’s Mark C. Hersam, who led the study. “The way you make AI smarter is by training it on more and more data. This data-intensive training leads to a massive power-consumption problem. Therefore, we have to come up with more efficient hardware to handle big data and AI. Because the brain is five orders of magnitude more energy efficient than a digital computer, it makes sense to look to the brain for inspiration for next-generation computing.”

Hersam is an expert in brain-inspired computing and holds multiple roles at Northwestern University, including the Walter P. Murphy Professor of Materials Science and Engineering at the McCormick School of Engineering. He also is a professor of medicine at Northwestern University Feinberg School of Medicine and a professor of chemistry at the Weinberg College of Arts and Sciences. In addition, he serves as chair of the department of materials science and engineering, director of the Materials Research Science and Engineering Center, and a member of the International Institute for Nanotechnology. He co-led the study with Vinod K. Sangwan, a research associate professor at McCormick.

Why the Brain Outperforms Traditional Silicon

Modern computers handle increasing workloads by packing billions of identical transistors onto rigid, two-dimensional silicon chips. Each component behaves the same way, and once manufactured, the system remains fixed.

The brain works very differently. It consists of many types of neurons, each with specialized roles, arranged in soft, three-dimensional networks. These networks are constantly changing, forming and adjusting connections as learning occurs.

“Silicon achieves complexity by having billions of identical devices,” Hersam said. “Everything is the same, rigid and fixed once it’s fabricated. The brain is the opposite. It’s heterogeneous, dynamic and three-dimensional. To move in that direction, we need new materials and new ways to build electronics.”

Although artificial neurons have been developed before, most produce overly simple signals. To achieve more complex behavior, engineers typically need large networks of devices, which increases energy use.

Printable Materials Enable Brain-Like Behavior

To better replicate real neural activity, Hersam’s team built artificial neurons using soft, printable materials that more closely match the brain’s structure. Their approach relies on electronic inks made from nanoscale flakes of molybdenum disulfide (MoS₂), which acts as a semiconductor, and graphene, which serves as an electrical conductor. These materials were deposited onto flexible polymer surfaces using aerosol jet printing.

Previously, researchers treated the polymer in these inks as a flaw because it interfered with electrical performance. As a result, they removed it after printing. In this work, the team used that same feature to enhance the device.

“Instead of fully removing the polymer, we partially decompose it,” he said. “Then, when we pass current through the device, we drive further decomposition of the polymer. This decomposition occurs in a spatially inhomogeneous manner, leading to formation of a conductive filament, such that all the current is constricted into a narrow region in space.”

That narrow conductive path produces a sudden electrical response similar to a neuron firing. The resulting device can generate a wide variety of signals, including single spikes, continuous firing, and bursting patterns, closely resembling real neural communication.

Because each artificial neuron can produce more complex signals, fewer components are needed to perform advanced tasks. This could significantly improve computing efficiency.

Testing Artificial Neurons on Real Brain Tissue

To evaluate whether the artificial neurons could truly interact with living systems, the researchers partnered with Indira M. Raman, the Bill and Gayle Cook Professor of Neurobiology at Weinberg. Her team applied the artificial signals to slices of mouse cerebellum.

The results showed that the electrical spikes matched key biological properties, including their timing and duration. These signals reliably activated real neurons and triggered neural circuits in a way similar to natural brain activity.

“Other labs have tried to make artificial neurons with organic materials, and they spiked too slowly,” Hersam said. “Or they used metal oxides, which are too fast. We are within a temporal range that was not previously demonstrated for artificial neurons. You can see the living neurons respond to our artificial neuron. So, we’ve demonstrated signals that are not only the right timescale but also the right spike shape to interact directly with living neurons.”

Low-Cost, Sustainable Manufacturing and AI Implications

Beyond performance, the new approach offers environmental and practical advantages. The manufacturing process is simple and inexpensive, and the additive printing method places material only where it is needed, reducing waste.

Improving energy efficiency is especially important as artificial intelligence systems grow more demanding. Large data centers already consume vast amounts of power and require significant water for cooling.

“To meet the energy demands of AI, tech companies are building gigawatt data centers powered by dedicated nuclear power plants,” Hersam said. “It is evident that this massive power consumption will limit further scaling of computing since it’s hard to imagine a next-generation data center requiring 100 nuclear power plants. The other issue is that when you’re dissipating gigawatts of power, there’s a lot of heat. Because data centers are cooled with water, AI is putting severe stress on the water supply. However you look at it, we need to come up with more energy-efficient hardware for AI.”

The study, “Multi-order complexity spiking neurons enabled by printed MoS₂ memristive nanosheet networks,” was supported by the National Science Foundation.