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Did Standing Up Drive Human Evolution?

Credit: travenian /iStockphoto

Credit: travenian /iStockphoto

By Mac Shine & Rick Shine

Watching a toddler learn to walk has led to a new hypothesis that bipedalism drove the evolution of the human brain.

Although lots of animals are smart, humans are even smarter. No other species can build spaceships that fly to the moon, or write operas, or understand the intricacies of mathematical theory. How and why do we think so differently from other species?

Watching a child learning to walk has suggested a new explanation to that age-old question. The generation of the hypothesis, recently published in Frontiers in Neuroscience, has been a family affair: the child in question (Tyler Shine) is the son and grandson of the two authors of that paper (and of this article).

We’re an unusual son-and-father team: Mac is a neurobiologist interested in neuroimaging, and Rick is an evolutionary ecologist who specialises in reptiles and amphibians. But watching young Tyler as he stumbled around the living room suggested a novel hypothesis to us: that the big difference between humans and other species may lie in how we use our brains for routine tasks. The key to exploiting the awesome processing power of our brain’s most distinctive feature – the cortex – may have been to liberate it from the drudgery of controlling routine activities.

Humans are smart not just because we have bigger brains – although that helps. More importantly, we have evolved a cognitive system that delegates control of routine tasks to other parts of the brain. That capacity to delegate allows us to save our superfast processing unit for new and unpredictable challenges.

And that’s where young Tyler Shine, now 2 years old, comes into the story. When Tyler was first learning to walk, his doting father and grandfather noticed that every step took Tyler’s full attention. But before too long, walking became routine and Tyler was able to start noticing other things around him. For example, he was better at maintaining his balance, which freed up his attention to focus on more interesting tasks, like trying to find out where his father had hidden chocolate in the kitchen.

How did Tyler improve his walking skills? Modern neuroimaging studies suggest that one of the keys to Tyler’s increasing mobility was that he began to transfer the control of his balance to “lower” parts of the brain. That delegation of routine movements freed up his cortex to focus on unpredictable challenges, such as a bumpy floor covered in stray toys.

The same transition is familiar to all of us. Any complicated activity – like driving a car or playing a musical instrument – consumes all of our attention at first but eventually becomes routine.

So the basic idea is simple. Humans are “smart” because we can automate lots of routine tasks, and thus can devote our most potent mental faculties to deal with new, unpredictable challenges. Although other species automate tasks in much the same way, we think that humans are distinctly better at it.

What event in the early history of humans made us change the way we use our brains? Watching Tyler learn to walk suggested that it was the evolutionary shift from walking on all fours to walking on two legs.

The fossil evidence shows that our ancestors switched from quadrupedal to bidepal life not long before our brains started expanding. These two shifts might well be related. As soon as we began to move around on two legs we were faced with the complicated challenge of keeping our balance – and the best kind of brain to have was one that didn’t waste its most powerful functions on controlling routine tasks.

We suggest that natural selection favoured pre-humans with brains that were good at shifting control of the routine balancing task to “lower” neural centres. An ancestor with a brain like this was more likely to notice a lurking predator or outwit an edible antelope. His cousin, who needed to concentrate entirely on what he was doing if he wanted to avoid falling over, fared less well in the evolutionary battle.

So what parts of the brain might be involved in this ability to delegate control from “higher” to “lower” centres? Young Tyler Shine couldn’t really provide much assistance to his father or grandfather here, so we had to resort to recent research on neural architecture in humans and closely related species.

Interestingly, the human brain doesn’t seem to contain any distinctly new regions. Rather, natural selection has expanded and inter-connected pre-existing regions, opening up new channels for the effective processing of information.

Human brains have tightly interconnected networks of brain activity that are not present in our nearest relatives. These networks have emerged via a reorganisation of existing brain regions, akin to installing a new software program onto an existing computer. Although the hardware remains the same, the computer is now capable of running more sophisticated tasks at a greater speed.

If the improvements in brain function exhibited by humans are due to changes in brain function rather than structure, how do we automate routine tasks? The system depends upon feedback – that is, input from reinforcement signals.

Behaviour in the early stages of learning is very flexible. This enables a comparison of a large array of potential behaviours to determine the most effective strategy. But over the course of learning this system trades off flexibility for consistency.

Importantly, the system needs to have global access to all of the brain. We think we know which parts of the brain have taken over this delegation function: pathways that interconnect the cortex, the basal ganglia and the cerebellum. Each of these structures has undergone rapid expansion in recent evolutionary history.

This three-part system connects large regions of the cerebral cortex (capable of flexible and rapid processing) with the cerebellum (responsible for habitual and inflexible processing) and the basal ganglia (subcortical brain structures that constantly monitor the environment for subtle changes). In our proposed model, the basal ganglia nuclei flexibly “switch” activity between these two systems in the face of changing environmental circumstances (Fig. 1).

Although metaphors of brain function that invoke computers are often criticised, an analogy with computer-based memory helps to explain concepts at the core of this “delegation” hypothesis. The difference between the “higher” and “lower” systems in the brain is similar to the difference between Rapid Access Memory (RAM) and Read-Only Memory (ROM) in a computer. Like the “higher” cortex, computer RAM is a flexible and high capacity storage system. It is adaptable to multiple functions and can be rapidly modified by user-defined processing decisions. In contrast, ROM is a rigid, inaccessible system that performs automatic tasks but is outside the control of the system operator.

Viewed through this analogy, our hypothesis suggests that the computational problems associated with bipedal locomotion led to the development of a system that delegates behaviours from RAM to ROM, effectively “hard-wiring” rewarded behaviours into memory. By doing this, the brain frees up its awesome computational processing power (the RAM) for other, unpredictable tasks.

Importantly, this analogy is about function and not mechanism: we do not suggest that the computational algorithms used by the human brain are similar to those required for RAM and ROM. Indeed, it is far more likely, based on the precise connectivity of the human brain, that the process of “delegation” from goal-directed to habitual behaviour emerges as a function of complex dynamics within neuronal networks.

We believe that those first pre-humans who began to stand upright faced a new evolutionary pressure, not just on their bodies but on their brains as well. Just as young Tyler Shine switched control over bipedal balance from conscious to unconscious brain centres as he grew older, we suggest that the challenges of standing up on two legs imposed a powerful evolutionary advantage to early humans capable of using their brains in a different and more effective way.

Mac Shine is a medical doctor who was recently awarded his PhD in cognitive neuroscience, and is currently using neuroimaging techniques to clarify brain function. Rick Shine is Professor in Evolutionary Biology at The University of Sydney. Tyler Shine is a rambunctious toddler who loves playing with Lego, running around and eating chocolate. Lots of chocolate. The Frontiers in Neuroscience research paper is available online at http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00090/full