The study: Ben Vermaercke and his colleagues at KU Leuven gave two cognitive-learning tasks to lab rats and students. With both tasks, the subjects were trained to distinguish between “good” and “bad” patterns and then tested on their ability to apply that know-how to new types of patterns. In the first task, the patterns varied on only one dimension—either orientation or spacing—and rats and humans performed it equally well. In the second, the patterns varied on both dimensions, and the rats did better than the humans.

The challenge: Are rodents more intelligent than we give them credit for? Are they, in some cases, our cognitive superiors? Mr. Vermaercke, defend your research.



A more complex brain isn’t always a better one. In information integration tasks, rats applied what they learned more quickly.

Vermaercke: The “in some cases” caveat is key here. The rats did outperform the humans in the second task. They needed more practice with the initial set of patterns to figure out how to discriminate between “good” and “bad,” but when given the next set, they were able to apply what they’d learned more quickly. They had to swim to show us their choices, while the student subjects used computers. But otherwise we tried to make the conditions as equal as possible.

HBR: How do you explain the rats’ better performance?

The first task involved rules. The second focused on information integration. Humans learn in both ways. Our rule-based system was an evolutionary development: How do you tell if a berry is good for eating? You learn that this small red one is good, and then you save energy by bypassing the ones of a different shape or color. So our brains have been conditioned to look for rules. We’re taught them in school, at work, and by our parents, and we can make many good decisions by applying the ones we’ve learned. But in other situations there’s too much going on for simple rules to work, and that’s when information integration learning has to kick in. Think of a radiologist evaluating an X-ray. If you ask him what rules he uses to determine whether a spot is cancer, he’d probably have a hard time verbalizing them. He’s learned from labeled examples in medical school and his own experience, and then developed an instinct for identifying cancerous spots based on what he’s seen before. Another example that comes to mind is a manager interviewing a job candidate. There aren’t any hard-and-fast rules about who will be a good hire. You have to consider many factors and rely on your judgment or on a gut feeling based on your experience with people in the workplace. Unfortunately, there’s a great deal of evidence showing that humans have a harder time learning how to integrate information in this way, because they seek rules even when there are none.

But rats don’t have the same problem?

Right. A more complex brain isn’t always a better one. Our theory is that instead of considering the specific data points and trying to find and apply a rule, our rat subjects employed what we call a similarity-based categorization strategy: Does this pattern look like the “good” targets we saw in training?

Are rats really that discerning?

Since my PhD thesis I’ve been studying how far we can push these animals in terms of task complexity, and the answer is, quite far. People used to think rats were practically blind; now we know that their visual abilities are pretty advanced. We’ve done research showing they can tell the difference between a movie that features a rat and one that doesn’t. David Cox and his colleagues at Harvard have reported that rats can recognize a 3-D object even if its size changes or it’s been rotated. These and other findings show that the rat is a valuable animal model for the study of complex visual processes.

Why should we care what rats can do?

Even though the rat brain is smaller and less complex than the human brain, research has shown that the two are remarkably similar in structure and function. Both consist of a vast amount of highly connected neurons that are constantly talking to each other. But we still have a very limited understanding of the main principles underlying this communication. So we start by investigating less complicated mammalian systems. You wouldn’t begin to learn the English language by reading Shakespeare, right? Also, with rats we can obviously study things that we just couldn’t in people. Take my current work as a research fellow at Harvard. It involves removing a small part of the skull of a living rat and replacing it with a coverslip, so we literally have a window into its brain and can see how its neural circuits change as it learns tasks. We can do this with dozens of animals.

What does PETA think about that?

We always follow institutional guidelines for humane housing and testing. And one benefit to proving that rats are intelligent creatures and using them for these sorts of experiments is that we take the weight off the shoulders of monkeys. I’m not saying you can replace primates with rats for all research. But it is feasible to use them in some cases. You can train many more of them, and there are fewer ethical and financial restraints.

What other types of animals are proving useful to brain research?

Quite a lot of animal models are used in neuroscience, and each has specific advantages. For example, the larvae of the zebra fish are completely transparent. This allows researchers to capture images of developing brain cells to answer questions about which molecules are important at which stage—knowledge that’s relevant to human embryo development. Another nice example is the male songbird, which develops a stereotypical song during adolescence. Researchers have studied the neural processing at work there to better understand how motor patterns develop through variable behavior and gradual refinement—something you also see in young children when they’re learning through trial and error to walk, eat, and speak.

Let’s get back to your experiment. Did you expect the humans to lose to the rats?

No. At first the study was on rats only. We simply wanted to know how they would handle the two types of learning tasks. However, when we saw that the pattern of results did not match those found in similar human studies, we decided to add people to our study and create as direct a comparison as possible. We were really surprised by the results.

What can humans do to overcome our bias toward rule seeking and get better at integrating information? How do we beat the rats?

One specific strategy might be to occupy your brain’s rule-based learning system with another task so that it doesn’t dominate your information integration learning system. In an experiment led by J. Vincent Filoteo of the University of California, San Diego, people did much better on an exercise very similar to the one we gave our subjects if they performed a number memory task—that is, one that occupied their rule-based system—between the training and the testing. There’s still room and need for more research, though. We’ve known about these two systems for about 15 years, but when it comes to the implications they hold for improving learning in our schools or organizations, I don’t think we’ve reached the answers.