A study published in PNAS reveals a common principle underlying joint movement, and shows that ageing weakens the propulsive strength in all species studied. New open-source software enables movement patterns to be compared across species.

A research team led by the University of Bern has developed a novel learning mechanism for neural networks modeled after the human brain. “Spike-based Alignment Learning” uses random fluctuations in the activity of artificial neurons to reveal asymmetric connections, allowing synapses that are far apart to autonomously align with one another without communicating directly. This approach could help us better understand learning processes in the brain and develop robust, energy-efficient, brain-inspired computer systems.

From September 28 to October 1, 2026, more than 600 researchers from around the world will gather at Goethe University Frankfurt to discuss current questions in Computational Neuroscience. Highlights include the presentation of the Valentin Braitenberg Award to Xiao-Jing Wang and a special evening event celebrating the 100th birthday of the award’s namesake.