Your brain uses math to control fast movements

A mouse is run on a treadmill built into a virtual reality hallway. In his mind, he sees himself rushing through a tunnel with a distinctive pattern of lights in front of him. Through training, the mouse learned that if it stops at the lights and holds that position for 1.5 seconds, it will receive a reward: a small glass of water. Then he can dash to another set of lights to receive another reward.

This configuration is the basis of the research published in July in Cell reports by neuroscientists Elijah Adam, Taylor Johns and Mriganka Sur from Massachusetts Institute of Technology. It explores a simple question: how do the brains of mice, humans, and other mammals work fast enough to shut us down in a pinch? The new work reveals that the brain is not wired to transmit a sharp “stop” command in the most direct or intuitive way. Instead, it uses a more complicated signaling system based on computational principles. This arrangement may seem overly complicated, but it’s a surprisingly clever way to control behaviors that need to be more precise than brain commands can be.

Control of the simple mechanisms of walking or running is fairly easy to describe: the midbrain locomotor region (MLR) of the brain sends signals to neurons in the spinal cord, which send inhibitory or excitatory impulses to motor neurons that control muscles of the leg: stop . Go. Stop. Go. Each signal is a spike in electrical activity generated by sets of neurons that fire.

The story becomes more complex, however, when goals are introduced, such as when a tennis player wants to run to a specific spot on the court or a thirsty mouse stares at a refreshing prize in the distance. Biologists have long understood that targets take shape in the cerebral cortex of the brain. How does the brain translate a goal (stop running there for a reward) into a precisely timed signal that tells the MLR to brake?

“Humans and mammals have extraordinary abilities when it comes to sensory motor control,” said Sridevi Sarma, a neuroscientist at Johns Hopkins University. “For decades, people have studied what in our brains makes us so agile, fast and robust.”

The fastest and hairiest

To understand the answer, the researchers monitored neural activity in a mouse’s brain while timing the time it took the animal to decelerate from top speed to a complete stop. They expected to see an inhibitory signal popping up in the MLR, causing the legs to stop almost instantaneously, like an electrical switch turning off a light bulb.

Neuroscientist Mriganka Sur and his colleagues discovered that in the brain of a mouse, a precise physical command was encoded in the interval between the spikes of two neural signals. “There is no information on the height of the spikes,” he said.

Photography: Webb Chappell

But a discrepancy in the data quickly undermined that theory. They observed a “stop” signal flowing through the MLR as the mouse slowed down, but it did not reach an intensity fast enough to explain how quickly the animal stopped.

“If you just take stop signals and feed them into the MLR, the animal will stop, but the math tells us the stop won’t be fast enough,” Adam said.

“The cortex doesn’t provide a switch,” Sur said. “We thought that’s what the cortex would do, go from 0 to 1 with a quick signal. It doesn’t do that, it’s the puzzle.

So the researchers knew there had to be an additional signaling system at work.

To find it, they looked again at the anatomy of the mouse brain. Between the cortex where goals originate and the MLR which controls locomotion is another region, the subthalamic nucleus (STN). It was already known that the STN connects to the MLR through two pathways: one sends excitatory signals and the other sends inhibitory signals. The researchers realized that the MLR responds to the interaction between the two signals rather than relying on the strength of either.

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