MIT: The brain uses calculus to control fast movements

Kristina Armitage/Quanta Magazine
Kristina Armitage/Quanta Magazine

by Kevin Hartnett, Contributing Writer to Quanta Magazine
November 28, 2022

A mouse is running on a treadmill embedded in a virtual reality corridor. In its mind’s eye, it sees itself scurrying down a tunnel with a distinctive pattern of lights ahead. Through training, the mouse has learned that if it stops at the lights and holds that position for 1.5 seconds, it will receive a reward — a small drink of water. Then it can rush to another set of lights to receive another reward.

This setup is the basis for research published in July in Cell Reports by the neuroscientists Elie Adam, Taylor Johns and Mriganka Sur of the Massachusetts Institute of Technology. It explores a simple question: How does the brain — in mice, humans and other mammals — work quickly enough to stop us on a dime? 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 employs a more complicated signaling system based on principles of calculus. This arrangement may sound overly complicated, but it’s a surprisingly clever way to control behaviors that need to be more precise than the commands from the brain can be.

Control over the simple mechanics of walking or running is fairly easy to describe: The mesencephalic locomotor region (MLR) of the brain sends signals to neurons in the spinal cord, which send inhibitory or excitatory impulses to motor neurons governing muscles in the leg: Stop. Go. Stop. Go. Each signal is a spike of electrical activity generated by the sets of neurons firing.

The story gets more complex, however, when goals are introduced, such as when a tennis player wants to run to an exact spot on the court or a thirsty mouse eyes a refreshing prize in the distance. Biologists have understood for a long time that goals take shape in the brain’s cerebral cortex. How does the brain translate a goal (stop running there so you get a reward) into a precisely timed signal that tells the MLR to hit the brakes?

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