“The layout of streets directs traffic. Similarly, connections between neighboring neurons determine how signals flow through the brain,” explains Yangfan Peng. Crucially, it is not only which cells are involved, but how they communicate with one another. “We aim to understand how local neuronal networks are organized and how the collective activity of many neurons emerges to control motor behavior,” says the neuroscientist, who is now conducting research with his team at the Institute of Cell and Neurobiology at Charité.

Advanced methods to decode neural networks

To address these questions, Yangfan Peng combines different state-of-the-art methodologies. Synaptic connectivity between neurons will be examined directly in brain tissue using the so-called multipatch technique. In this approach, multiple glass pipettes simultaneously record activity and synaptic connectivity from up to ten neurons. The team will analyze brain tissue from mice, as well as valuable human brain tissue obtained during neurosurgical procedures that would otherwise be discarded.

In addition, the researchers will use high-resolution electrodes in animal models to record the activity of hundreds of neurons simultaneously. This makes it possible to link specific patterns of brain activity to distinct motor behaviors. Using artificial intelligence, the team aims to predict behavior based on neuronal activity patterns.