A new experiment advances the idea that brain scans can teach us something about how the human mind works.
By Nathan Collins
(Illustration: Public Domain)
Mind reading stands as one of science fiction’s most enduring improbabilities, alongside light-speed space travel and laser guns. But unlike those latter two, mind reading actually has a whiff of reality: In a newdemonstration, psychologists have shown theycan figure out how far along someone’s brain is in the process of solving a sophisticated math problem—a result that, more than anything else, indicates the promise of new brain-scanning techniques for understanding the human mind.
The issue, Carnegie Mellon University psychologists John Anderson, Aryn Pyke, and John Fincham write in Psychological Science, isn’t really mind reading per se; it’s figuring out whether brain-scanning technology like functional magnetic resonance imaging (fMRI), which tracks blood flow in the brain, actually tells us something about the way people think. Sure, some have argued, one part of the brain lights up in response to baby photographs or political messaging. But so what? Can that actually tell us something about humans emotions and cognition?
Yes, Anderson, Pyke, and Fincham argue—but achieving that goal takes a sophisticated approach. Rather than look for correlations between activity in the brain and behavior in the laboratory, their idea was to look directly at patterns of changing activity—in particular, patterns of activity that go through a sequence of configurations corresponding to the stages we go through in order to problem-solve or wrestle with mathematics. Identifying a sequence of those patterns or configurations could help researchers view thinking in action.
Psychologists have shown theycan figure out how far along someone’s brain is in the process of solving a sophisticated math problem.
To see if they could actually identify such patterns, the team had 80 people solve a series of math problems while lying in an fMRI scanner. Using a mix of otherwise standard methods from computer science and neuroscience, they identified a sequence of brain-activation patterns corresponding to encoding a problem, planning a solution, making the necessary computations, and providing a response.
To validate those stages, they varied different aspects of the problem to see how that affected the duration of each brain-activation stage. For example, half the participants learned a step-by-step method to solve problems, and, for that half, the computation stage—identified only by a specific pattern of brain activation—took longer for certain problems than others. The other half learned a simple formula that applied to all problems—and, for them, the computation stage lasted the same amount of time for all math problems. That’s evidence, the researchers argue, that they had indeed identified a pattern of brain activation that corresponded to performing mathematical computations.
The findings are so far pretty limited—they really only apply to a certain set of mathematical problems—but “the results are encouraging for the general use of the … methods to parse complex cognition into distinct stages,” the researchers write. “The distinctive cognitive demands of each stage will produce a brain pattern that can be used to estimate temporal boundaries of that stage on each trial,” which may give psychologists a new, deeper window into human thinking.