Curiosity’s importance to brain development suggests that children should be given a choice of activities How did our brains evolve to be so complex? The answer may boil down to curiosity. Researchers who trained thousands of artificial neural networks with different learning styles found that the most curious ones not only had more sophisticated and flexible cognitive abilities, they also spontaneously organised into structures that resemble human brains.
The networks formed interconnected modules and followed a human-like developmental trajectory, for example, with dense neural connections forming early on before being pruned away. Curiosity is usually seen as a consequence of having a complex brain, says Francesco Poli at the University of Cambridge. The infants were shown sequences of colourful shapes on a screen, which provided varying amounts of information about where the next shape was likely to be displayed.
The babies proved to be highly sensitive to how much information the different stimuli provided. Whenever their rate of learning dropped below average, they disengaged and looked for something new, says Poli. The team used this principle to design artificial neural networks with different levels of intrinsic curiosity, then trained them on 20 tasks.
The high-curiosity models were designed to immediately switch task if their rate of learning dropped below a certain threshold, whereas the low-curiosity models switched randomly. All the networks, curious or not, became experts at the tasks they were trained on. But after the training, the curious models performed significantly better at tests they hadn’t seen before.
This ability to put together different things in flexible ways is seen as a hallmark of complex human cognition, says Poli. The curious models also developed physical characteristics resembling those of complex brains. The researchers embedded the artificial networks into a virtual three-dimensional space, modelled on the anatomy of the human brain.
They then forced the networks to wire themselves efficiently by penalising long-distance connections, in order to mimic the cost of long-range wiring in real brains. On its own, this wasn’t enough to produce complexity, but when the researchers added curiosity on top, a range of brain-like features emerged. For example, the curious networks developed a hierarchical “modular” structure with highly-interconnected areas that were in turn connected to each other.
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