A new study reveals how the brain’s "place cells" create internal maps to help us navigate. These specialized neurons, found in the hippocampus, were once thought to rely on precisely ordered patterns for spatial coding. However, researchers have found that their activity, which appears disordered in large spaces, actually follows universal mathematical principles. This surprising discovery suggests that randomness, not strict organization, is key to how our brains encode information about our experiences. The findings could reshape our understanding of brain function and pave the way for new insights into how we represent and process complex information.

Heat-resistant sensing and computing chips made of silicon carbide could advance aircraft, electric and gas-powered vehicles, renewable energy, defense and space exploration—and University of Michigan researchers are leading a multimillion dollar collaborative effort to bring more of them to market.

Inspired by the cooperation of cells in tissues, researchers have developed a robotic collective system capable of transitioning between rigid and solid structures that can also support hundreds of times its own weight. The advancement overcomes a core challenge in the development of so-called “robotic materials” – cohesive networks of individual robotic units that function as a single dynamic, adaptive structure. Realizing these systems presents a fundamental challenge: this “material” must at once be strong and stiff enough to support loads, yet at the flip of a switch, be able to flow freely to take new forms. Unlike inert materials and conventional robotic systems, living embryonic tissues possess the remarkable ability to internally regulate their mechanical properties across space and time. Drawing inspiration from living embryonic tissues, which regulate mechanical properties through coordinated cellular behavior, Matthew Devlin and colleagues engineered robotic collectives that mimic key cell-cell interaction mechanisms using motorized gears, photoreceptors, and rolling magnets. These features enable precise control over force fluctuations and polarity, allowing the system to dynamically adjust rigidity and fluidity. Devlin et al. demonstrated structure formation, with robotic units forming pillars that merged into a stable, load-bearing arch. The collective also exhibited self-healing, fluidizing to close structural defects. And it exhibited object manipulation, applying directed forces to move items. Additionally, the system adapted into functional tools, flowing around objects before rigidifying into a wrench capable of exerting torque. The researchers further showcased supporting structures, where the collective bore loads exceeded individual unit weight – supporting a human (~700 Newtons) before effortlessly transitioning back into a fluid state.