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You are at:Home » AI is able to detect the position of a mouse by analyzing its brain activity
Ai Is Able To Detect The Position Of A Mouse
Science February 23, 2024

AI is able to detect the position of a mouse by analyzing its brain activity

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Micrograph of a cross-section of a mouse brain highlighting neural pathways (green)

Mark and Mary Stevens Neuroimaging and Informatics Institute/Scientific Photo Library

By analyzing a mouse’s brain activity, scientists can tell where the animal is and the exact direction the mouse is looking. With further research, the findings could one day help robots navigate autonomously.

The mammalian brain uses two main types of neurons for navigation. “Head direction cells” indicate where the animal is facing, and “grid cells” help provide her two-dimensional brain map of where the animal is located.

To learn more about the firing of these neurons, Vasilios Marlas and colleagues at the University of Tennessee, Knoxville, worked with the U.S. Army Research Laboratory to analyze data from previous studies.

In this experiment, probes were inserted into the brains of several mice. They then combined data about their neural firing patterns with video footage showing their position and head position as they moved around their open environment.

Because of this, Marlas and his colleagues developed an artificial intelligence algorithm that can figure out where the mouse is looking and where it is.

In practice, it’s similar to the drop pins and directional arrows on your smartphone’s map app, except instead of connecting to GPS satellites, scientists analyze the subjects’ brain activity.

“This method eliminates the reliance on updating GPS coordinates based on preloaded maps, satellite data, etc.,” Marulas says. “In a sense, the algorithm ‘thinks’ and perceives space in the same way as a mammalian brain.”

AI could eventually allow intelligent systems to move autonomously, he says. “In other words, we are taking advantage of the way the mammalian brain processes data and incorporating it into the architecture of our algorithms.”

Adam Hines Researchers from Australia’s Queensland University of Technology say the smartphone app analogy is helpful. “The location information (drop pin) and the direction (blue arrow) match, and during navigation, as he moves, the two pieces of information are constantly updated. Grid cells are like GPS, heading cells are It’s like a compass.”

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Source: www.newscientist.com

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