A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the discovery of counterintuitive activity by a group of neurons that researchers working with animals to perform the same task had not noticed in their data before, reports a team of scientists at Dartmouth College, MIT, and the State University of New York at Stony Brook.
Separate two superconductors with a thin layer of material and something strange happens.
Their superconductivity—a property driven by paired electrons that allows electricity to flow without energy loss—can leak into the barrier and link together, synchronizing their behavior despite the separation.
This device is known as a Josephson junction. It’s the foundational building block of quantum computers and advances of it won the 2025 Nobel Prize in Physics.
Encapsulated microbubbles (EMBs), tiny gas-filled bubbles coated in lipid or protein shells, play a central role in biomedical ultrasound. When exposed to ultrasound waves, EMBs contract, resulting in oscillations that enhance image contrast or deliver drugs directly by creating pores in cell membranes via sonoporation. However, while promising for biomedical applications, their behavior is far more complex.
Most existing theories on EMBs assume spherically symmetrical oscillations and only study them in simple Newtonian fluids. However, most biological fluids, such as blood, are viscoelastic (non-Newtonian) fluids. When inside the body, these fluid forces, pressure from vessel walls, and changing ultrasound pulses can influence the behavior of EMBs, affecting both imaging accuracy and treatment safety.
To better understand these effects, a multi-institutional research team has developed a comprehensive computational model that simulates the behavior of EMBs under real biological conditions. The team included Assistant Professor Haruki Furukawa and Professor Shuichi Iwata from Nagoya Institute of Technology (NITech), Japan, in collaboration with Emeritus Professor Tim N. Phillips, Dr. Michael J. Walters, and Reader Steven J. Lind from Cardiff University, Wales.
David Deutsch didn’t just contribute to the field of quantum computing—he redefined what computation *is*, bridging the gap between physics and information in a way no one had before. By theorizing the universal quantum computer, Deutsch opened the door to possibilities previously confined to science fiction, forever altering our understanding of reality and the limits of what machines can achieve.
The familiar fight between “mind as software” and “mind as biology” may be a false choice. This work proposes biological computationalism: the idea that brains compute, but not in the abstract, symbol-shuffling way we usually imagine. Instead, computation is inseparable from the brain’s physical structure, energy constraints, and continuous dynamics. That reframes consciousness as something that emerges from a special kind of computing matter, not from running the right program.
