Thanks to research by scientists at INSERM in France, we now have a much better idea of why humans and our primate cousins are so capable of learning new behaviors that evolution couldn’t have prepared us for. Things like driving cars, writing code, or sitting in a classroom never could have been anticipated by evolution, as these simply aren’t things that we would have been exposed to in nature.

But evolution did one better, and primates developed a “pre-adaptation” neural network that allows us to quickly adapt and learn new behaviors. Essentially, the network functions by allowing neurons to form recurrent loops, so that inputs can mix around within the network, similar to “reservoir computing.” This mix of inputs constantly reacting allows us to pull on various combinations of inputs to deal with new things.

The scientists gave both a primate and a reservoir computer the same task and studied how they reacted. The systems by which both solved the problem showed a very similar activation of neurons.

This is a pretty huge step forward in understanding how the human brain works, and it should have implications for evolutionary biology, computing, and education, among other areas. Since our brains are building an ever larger and essentially limitless collection of inputs and responses, it stands to reason that teaching new behaviors and skills to students can benefit from drawing upon similar experiences and skills. By starting with a simple, or at least familiar, concept, teachers can build upon that foundation with other information, behaviors, or skills, and rely on the neural networks of their students to help fill in the gaps by finding neuron loops related to the shared experiences.

Of course, this in and of itself isn’t a particularly new concept in pedagogy, but no that we know more about the way our brains learn novel behaviors, perhaps we can use that to strengthen that pedagogy.