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No matter how you did in high school science, you’re a master of the laws of physics, able to predict intuitively how objects in the world will behave.
Cognitive scientists have now found the source of that intuitive understanding, what they call the brain’s “physics engine,” which allows humans to judge where to catch a fly ball or when to cross the street safely.
This engine, which comes alive when people watch physical events unfold, lies not in the brain’s vision center, but in a set of regions devoted to planning actions, the scientists say.
That suggests that the brain performs constant, real-time physics calculations so people are ready to catch, dodge, hoist, or take any other action as needed, on the fly.
“We run physics simulations all the time to prepare us for when we need to act in the world,” says lead researcher Jason Fischer, assistant professor of psychological and brain sciences at Johns Hopkins University. “It is among the most important aspects of cognition for survival.”
Fischer says that before this study, published online in the Proceedings of the National Academy of Sciences
, there had been almost no research done to identify and study the brain regions involved in this intuitive physics.
How’s your physics engine? Take the ‘Jenga’ test
In this video, you can try out the experiment that scientists used to locate the human brain’s “physics engine.”
Fischer, along with researchers at Massachusetts Institute of Technology, conducted a series of experiments to find the parts of the brain involved.
First they had 12 subjects look at videos of Jenga-style block towers. While monitoring their brain activity, the team asked the subjects either to predict where the blocks would land should the tower topple, or guess if the tower had more blue or yellow blocks. Predicting the direction of falling blocks involved physics intuition, while the color question was merely visual.
Next, the team had other subjects watch a video of two dots bouncing around a screen. They asked subjects to predict the next direction the dots would head, based either on physics or social reasoning.
With both the blocks and dots, the team found, when subjects attempted to predict physical outcomes, the most responsive brain regions included the premotor cortex and the supplementary motor area—the brain’s action planning areas.
“Our findings suggest that physical intuition and action planning are intimately linked in the brain,” Fischer says. “We believe this might be because infants learn physics models of the world as they hone their motor skills, handling objects to learn how they behave. Also, to reach out and grab something in the right place with the right amount of force, we need real-time physical understanding.”
Even when we’re not thinking about it
In the last part of the experiment, the team asked subjects to look at short movie clips—just to look; they received no other instructions—while having their brain activity monitored. Some of the clips had a lot of physics content, others very little. The team found that the more physical content in a clip, the more the key brain regions activated.
“The brain activity reflected the amount of physical content in a movie, even if people weren’t consciously paying attention to it,” Fischer says. “This suggests that we are making physical inferences all the time, even when we’re not even thinking about it.”
The findings could offer insight into movement disorders such as apraxia, as it’s very possible that people with damage to the motor areas of the brain also have what Fischer calls “a hidden impairment”—trouble making physical judgments. A better understanding of how the brain runs physics calculations might also enrich robot design. A robot built with a physics model, constantly running in its programming almost like a video game, could navigate the world more fluidly.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Eye Institute, and the National Science Foundation funded the study.
Source: Johns Hopkins University
This article was originally published on futurity.org