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Analysing a mouse’s brain activity tells scientists where the animal is located and the exact direction it is looking. With further research, the findings could one day help robots navigate autonomously.

Mammalian brains use two main types of neurons for navigation: “head direction cells” show where an animal is facing and “grid cells” help provide a two-dimensional brain map of where it is located.

To learn more about the firing of these neurons, at the University of Tennessee, Knoxville, and his colleagues – together with the US Army Research Laboratory – analysed data from a previous study.

In this experiment, probes were inserted into several mice’s brains. Data on their neural firing patterns were then paired with video footage showing their locations and head positions as they moved around an open environment.

From this, Maroulas and his colleagues developed an artificial intelligence algorithm that can use neural activity to work out where a mouse is looking and where it is located.

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In effect, it is like the drop pin and directional arrow on a smartphone’s map app, except instead of connecting to a GPS satellite, scientists analyse a subject’s brain signals.

“This method allows us to not be dependent on a preloaded map or updating the GPS coordinates based on, say, satellite data,” says Maroulas. “In some sense, the algorithm ‘thinks’ and recognises space as a mammalian brain would.”

The AI could eventually enable intelligent systems to navigate autonomously, he says. “In other words, we take advantage of how the mammalian brain processes data and incorporate it in the architecture of the algorithm.”

at the Queensland University of Technology in Australia says the smartphone app analogy is a helpful one. “You have positional information (the drop pin) aligned with direction (blue arrow), and during navigation the two are constantly updating as you move. Grid cells are like the GPS and heading cells are like a compass.”