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The brain is like a noisy city where each district has its own business. Neurons communicate via electrical signals, and sometimes you need to reach a specific block without disturbing the neighbors. Temporal interference stimulation (where two high-frequency fields, superimposed, create a low-frequency effect only at their intersection) promises such targeted stimulation of deep structures. But until now, tuning it felt like trying to find a particular alley without a map or a flashlight.

The researchers built a digital model of a mouse head and equipped it with an optimization algorithm. This is not just a virtual cast of the skull — the program accounts for how tissues conduct current and iterates over electrode placements, frequencies, and signal strengths. The goal is to achieve maximum brightness at the target point and minimal spillover around it. This approach turns crude tuning into precise calculation.

In another scenario, for the dentate gyrus (involved in distinguishing similar memories), the radius of the stimulation spot shrank from 3.99 to 3.54 millimeters. Almost half a millimeter — a noticeable difference for a mouse hippocampus. The algorithm doesn't just amplify the signal; it seeks a balance: sometimes power matters more, sometimes sharp boundaries. Validation on a standard Sim4Life phantom confirmed that the found settings work reliably, not just tuned to one specific model.

Now the researchers have a navigator that plots a route to any district of the neural city. This promises cleaner experiments: when you know you've only touched the target block and the neighbors are silent, conclusions about brain function become more reliable.