# Your Brain Learned Physics and Calculus Before You Did

Tilt your head to the right while moving to the left. The neurons in your brain just solved Newton’s equations of motion, and performed complex vector calculus equations almost instantaneously. That’s what four neurologists Washington University of Medicine (St. Louis, MO) essentially claimed in *Nature* July 29,^{1} describing how your brain interprets the information coming from multiple sensory inputs.

The title of their article says it: “Neurons compute internal models of the physical laws of motion.” The article is filled with equations that the neurons have to solve correctly to help you determine whether the motion you feel means you are moving left or right, tilting, or a combination of the two. The signals come from the otoliths in your inner ear (see 10/10/2003 headline) and from the fluid in the semicircular canals. What if these inputs give contradictory information? The net vectors of the inputs could cancel each other out, or sum up to give a wrong impression. The scientists mapped out the equations that would have to be solved to distinguish between the components of translational and gravitational motion, regardless of phase, and then experimented on monkeys while watching the activity of the brain. They found that the way neurons fire in response to the stimuli match predictions of how the information would have to be parsed to fit the terms of the equation. In conclusion, they state:

These results illustratea direct correlationbetweencell firing ratesandthe equations of motion, as applied tomovement in a gravitational environmentandthe physics of the external world. A neural basis foran internal model representationof therelationship between the physical environmentand eitherthe sensory detectors or the motor apparatushas only recently begun to be explored. Here we haveshown evidencethat,in support oftheoreticalpredictions, subcorticalneural populationsmightprovide a distributed solution to the inertial motion detection problem.

^{1}Angelaki, Shaikh, Green and Dickman, “Neurons compute internal models of the physical laws of motion,” Nature 430, 560 – 564 (29 July 2004); doi:10.1038/nature02754.

As expected, this paper makes no attempt to explain how such a system could have evolved. The more detail provided in a research paper about the workings of a biological system, the less apt are the authors to attribute it to time and chance.

One of the defining marks of life is awareness of the surroundings and ability to respond to the environment. Think about all the components required to make this work: you need sensors, they need to be able to communicate to the central processor, and the central processor has to be able to interpret all the multiple inputs that provide sometimes contradictory information. So not only are the cells themselves irreducibly complex, the organs and processors are also irreducibly complex, or else no equations of motion can be solved. In fact, look at each irreducibly complex component of this system, and you will find additional irreducibly complex parts within them, every one vital to the success of the whole project. Who taught your neurons the equations of physical motion and the techniques of vector calculus? Playing a game of tennis requires rapidly solving a continuous stream of computational problems (see 01/05/2001 headline). Don’t get cocky about this skill; owls excel at math, too (see 04/13/2001 headline), and even your dog knows calculus (see 05/20/2003 headline).