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Striking parallels between biological brains and AI during social interaction suggest fundamental principles

UCLA researchers have made a significant discovery showing that biological brains and artificial intelligence systems develop remarkably similar neural patterns during social interaction. This first-of-its-kind study reveals that when mice interact socially, specific brain cell types synchronize in “shared neural spaces,” and AI agents develop analogous patterns when engaging in social behaviors.

The study, “Inter-brain neural dynamics in biological and artificial intelligence systems,” appears in the journal Nature.

This new research represents a striking convergence of neuroscience and artificial intelligence, two of today’s most rapidly advancing fields. By directly comparing how biological brains and AI systems process social information, scientists reveal fundamental principles that govern across different types of intelligent systems.

ReSURF: Stretchable, self-healing water quality sensor enables ultrafast surveillance

Clean, safe water is vital for human health and well-being. It also plays a critical role in our food security, supports high-tech industries, and enables sustainable urbanization. However, detecting contamination quickly and accurately remains a major challenge in many parts of the world.

A new device developed by researchers at the National University of Singapore (NUS) has the potential to significantly advance water quality monitoring and management.

Taking inspiration from the biological function of the oily protective layer found on , a team of researchers led by Associate Professor Benjamin Tee from the Department of Materials Science and Engineering in the College of Design and Engineering at NUS translated this concept into a versatile material, named ReSURF, capable of spontaneously forming a water-repellent interface.

AI and biophysics unite to forecast high-risk viral variants before outbreaks

When the first reports of a new COVID-19 variant emerge, scientists worldwide scramble to answer a critical question: Will this new strain be more contagious or more severe than its predecessors? By the time answers arrive, it’s frequently too late to inform immediate public policy decisions or adjust vaccine strategies, costing public health officials valuable time, effort, and resources.

In a pair of recent publications in Proceedings of the National Academy of Sciences, a research team in the Department of Chemistry and Chemical Biology combined biophysics with artificial intelligence to identify high-risk viral variants in record time—offering a transformative approach for handling pandemics. Their goal: to get ahead of a virus by forecasting its evolutionary leaps before it threatens public health.

“As a society, we are often very unprepared for the emergence of new viruses and pandemics, so our lab has been working on ways to be more proactive,” said senior author Eugene Shakhnovich, Roy G. Gordon Professor of Chemistry. “We used fundamental principles of physics and chemistry to develop a multiscale model to predict the course of evolution of a particular variant and to predict which variants will become dominant in populations.”

Extraterrestrial Habitats: Bioplastics for Life Beyond Earth

If humans are ever going to live beyond Earth, they’ll need to construct habitats. But transporting enough industrial material to create livable spaces would be incredibly challenging and expensive. Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) think there’s a better way, through biology.

An international team of researchers led by Robin Wordsworth, the Gordon McKay Professor of Environmental Science and Engineering and Professor of Earth and Planetary Sciences, have demonstrated that they can grow green algae inside shelters made out of bioplastics in Mars-like conditions. The experiments are a first step toward designing sustainable habitats in space that won’t require bringing materials from Earth.


In lab experiments that recreated the thin atmosphere of Mars, Wordsworth’s team grew a common type of green algae called Dunaliella tertiolecta. The algae thrived inside a 3D-printed growth chamber made from a bioplastic called polylactic acid, which was able to block UV radiation while transmitting enough light to allow the algae to photosynthesize.

The algae was kept under a Mars-like 600 Pascals of atmospheric pressure – over 100 times lower than Earth’s — and in a carbon dioxide-rich environment, as opposed to mostly nitrogen and oxygen like on Earth. Liquid water cannot exist at such low pressures, but the bioplastic chamber created a pressure gradient that stabilized water within it. The experiments point to bioplastics as potentially key to creating renewable systems for maintaining life in a lifeless environment.

The concept the researchers demonstrated is closer to how organisms grow naturally on Earth, and it contrasts with an industrial approach using materials that are costly to manufacture and recycle.

AI helps discover optimal new material for removing radioactive iodine contamination

Managing radioactive waste is one of the core challenges in the use of nuclear energy. In particular, radioactive iodine poses serious environmental and health risks due to its long half-life (15.7 million years in the case of I-129), high mobility, and toxicity to living organisms.

A Korean research team has successfully used artificial intelligence to discover a new material that can remove iodine for nuclear environmental remediation. The team plans to push forward with commercialization through various industry–academia collaborations, from iodine-adsorbing powders to contaminated water treatment filters.

Professor Ho Jin Ryu’s research team from the Department of Nuclear and Quantum Engineering, in collaboration with Dr. Juhwan Noh of the Digital Chemistry Research Center at the Korea Research Institute of Chemical Technology, developed a technique using AI to discover new materials that effectively remove contaminants. Their research is published in the Journal of Hazardous Materials.

Light pollution has more dramatic effect on circadian rhythms of social birds than isolated birds, study finds

Light pollution, or artificial light at night (ALAN), is a widespread phenomenon in areas with dense human populations. Normally, animals use natural external cues, like sunlight and temperature, to synchronize their biological rhythms with the day-night cycle. However, ALAN is known to affect the biological rhythms of animals living within its range by altering physiological, molecular and behavioral mechanisms related to sleep-wake cycles (circadian rhythms).

Diver-operated microscope brings hidden coral biology into microscale level focus

The intricate, hidden processes that sustain coral life are being revealed through a new microscope developed by scientists at UC San Diego’s Scripps Institution of Oceanography.

The diver-operated —called the Benthic Underwater Microscope imaging PAM, or BUMP—incorporates pulse amplitude modulated (PAM) light techniques to offer an unprecedented look at coral photosynthesis on micro-scales.

In a new study, researchers describe how the BUMP imaging system makes it possible to study the health and physiology of in their natural habitat, advancing longstanding efforts to uncover precisely why corals bleach.