There is a mouse running on a treadmill. It sees itself going down a tunnel with a pattern of lights behind it. A small drink of water will be given to the mouse if it stops at the lights for 1.5 seconds. It can get another reward by rushing to another set of lights.
The basis for the research published in July is this setup. How does the brain in mammals work to stop us on dimes? According to the new work, the brain isn't wired to send a stop command in a direct way. It uses a more complicated signaling system based on the principles of math. It's a 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 of the brain sends signals to neurons in the spinal cord, which send excitatory impulses to motor neurons governing muscles in the leg Don't go. Don't, stop. Don't go. The signals are generated by the sets of neurons firing.
When goals are introduced, the story gets more complicated, 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. Goals in the cerebral cortex are understood by biologists. The brain can translate a goal into a signal that tells the MLR to hit the brakes.
When it comes to sensory motor control, humans and mammals are the best. People have been studying our brains for decades.
The researchers monitored the neural activity in a mouse's brain to understand the answer. They expected to see a surge in the MLR that would cause the legs to stop.
There was a discrepancy in the data. They observed a stop signal flowing into the MLR, but it wasn't fast enough to explain how quickly the animal halted.
If you feed the animal with stop signals, it will stop, but the math tells you it won't be fast enough.
The cortex doesn't give a switch We thought the cortex could go from 0 to 1 in less than a second. The puzzle is that it doesn't do that.
There had to be an additional signaling system in place.
They looked at the brain of a mouse. The subthalamic nucleus is located between the cortex where goals start and the MLR that controls locomotion. The MLR is connected by two pathways, one sending excitatory signals and the other suppressing them. The researchers realized that the MLR responds to the interplay between the two signals.
The MLR gets a signal from the STN when the mouse stops. Immediately afterwards it also gets an excitatory signal. The MLR pays attention to the difference between the two signals when they come on.
The height of the spikes is not known. The interval between the spikes is where everything is located. The interval can carry information because of the spikes.
The researchers cast the stopping mechanism in terms of two functions of calculus: integration and derivation.
The quantity of the signal would be more important than the amount of the stop signal. Integration alone isn't enough for rapid control The way a derivative is calculated is by using the difference between two infinitesimally close values to calculate the slope of a curve. The fast dynamics of the derivatives allow for a fast stop.
The two signals are being compared quickly. The animal stops when there is a switch thrown.
It makes strategic sense to use a derivatives-based control system. It's useful to know how fast a tennis player is going when they're racing across a court. It is more useful for them to know how fast they are moving so that they can plan their next move.
It allows you to make predictions. I can predict what my velocity will be at the next step if I know the derivative. I can plan for it if I have to stop.
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