Brain Development

This study focuses on understanding how connections between neurons (i.e., synapses) change and adapt in a process known as synaptic plasticity, which is crucial for learning and memory. They introduce a new computational method called filter simulation-based inference (fSBI) to understand how brain connections change and adapt during learning, testing millions of possible combinations to find those that work effectively. Their method successfully identified multiple viable rules that maintain stable brain activity patterns, challenging some traditional experimental approaches while suggesting new ways to study brain plasticity.

This Goethe University study investigated how the brain's visual system develops after animals first open their eyes. Using ferrets, researchers found that mammals are born with some amount of the visual cortex ready to use. They discovered that, while the brain initially responds strongly but unreliably to visual input, it develops more stable and consistent responses within days of normal vision. This development involves reorganizing brain circuits through a process called "feedforward-recurrent alignment," where incoming visual information becomes properly matched with internal brain networks.

This study introduces “Peak Selection,” a concept that explains how modular structures emerge from local interactions. Challenging existing theories, it shows that systems like brain grid cells and ecosystems self-organize without genetic instruction. Supported by mathematical models, the findings reveal how stable, large-scale structures naturally form, offering new insights into biological organization.