
When it comes to brains, size doesn’t matter much
Image credit: Ionut Stefan
It all started from a reasonable assumption: bigger brains pack more neurons, and more neurons make one smarter, ergo bigger brain = smarter cookie. But if there’s one thing brains love, it’s nonlinearities (to be read as “freaking messes!”). To understand what that means, we’ll talk about how brains of different sizes are structured, and if it’s not size, what features actually make them smart.
We can approach this discussion at two levels: between species and within species. At the first level, brain size varies dramatically (imagine mouse vs. elephant), giving us a coarse-grained understanding of why size alone doesn’t explain intelligence. At the second one, we’ll look at comparisons between people, where the differences in brain size are much smaller, but the data is richer, giving us a more fine-grained picture of what might be going on.
What is intelligence
In both cases, we need to define what “smart” means. Intelligence, like a lot of other higher-order cognitive concepts, suffers from definition fuzziness: there are a bunch of ways to define it, and if we don’t clarify this upfront, we risk talking past each other. For this article, we’ll focus on general intelligence, or mental ability.
Another point to consider is that we’ll be talking about both humans and other species.
For all of them, general intelligence includes the ability to solve problems and come up with novel solutions, the capacity to learn and change one’s behavior based on experience, and the ability to think abstractly.
In humans, however, intelligence tests obviously rely heavily on verbal ability, and many studies use something called the g factor. This variable summarizes positive correlations between different cognitive tasks, and is used to reflect something we’ve observed empirically: that people who do well on one cognitive test usually do well on others too.
There have been attempts to use the g factor for quantifying intelligence in other animals, but as you can imagine, the lack of verbal ability makes standardized inter-species comparisons extremely challenging. Instead, researchers rely on a set of indirect tests. These let them measure things such as learning and problem-solving, memory capacity, or even the ability for self-recognition (using the mirror test).
The lack of standardization makes it difficult to say with certainty that, for example, a crow is more intelligent than a baboon. Yes, crows can do geometry and baboons apparently can’t, but is that all it takes to be smart? Still, imperfect as they are, these measures allow us to challenge the assumption that bigger brains are smarter: if a crow, with a much smaller brain than a baboon’s, can do geometry, clearly there’s more at play than sheer brain size.
The comparison between species
But let’s back up a bit. In the section above, it seemed reasonable to define “smart”, but what if I told you we also need a definition for “brain size”? It might seem a bit ridiculous, but there really is more than one interpretation for this term. We saw the first one in the crow-baboon example, where we introduced absolute brain size. The problem with this is that absolute brain size correlates strongly with body size: larger animals have larger brains. And we don’t even need to compare crows and baboons, we can compare ourselves to whales and elephants. Even though they’re quite intelligent animals, they’re still not exactly on our level. So absolute brain size is not a good indicator of intelligence.
Another way to define brain size would be relative to the body weight. Take humans and whales again: the brain of a human weighs about 1.5 kg, and that of a whale about 9 kg. In terms of absolute brain size, whales win hands down. But if we look at brain weight as a percentage of the body weight, we get about 2.5% in humans and a measly 0.02% in whales. We now have a data point indicating that a species with a higher relative brain size is also more intelligent. We can now expand this to as many species as possible and see if it still holds. It’s not a big surprise that it doesn’t, but I bet you won’t guess which animal breaks the pattern. It’s the Etruscan shrew (this little guy), with a brain weight of about 0.1 g and a body weight of only 2 g, giving us a 5% value, double that of humans!
Alright, that’s another simple explanation gone down the drain. Back to the drawing board it is. We said that larger bodies go hand in hand with larger brains. Now, if intelligence didn’t play any role at all, we could assume that the brain is simply increasing in size because it needs to manage a larger body. In that case, if we knew an animal’s body size, we could mathematically predict what its absolute brain size should be. If we saw any increase in size on top of that, we could only assume that’s due to the extra brain being used for intelligence. That’s the simplest explanation for what scientists termed the third way of defining brain size, the encephalization quotient (EQ). As you might already guess, that didn’t work out very well either. Humans came up pretty well on this metric, but chimpanzees, gorillas, and whales, animals which we know are fairly smart, scored quite low EQs. More attempts were made to improve the EQ calculation formula. These only succeeded in making it more complicated, so I won’t bore you with the details. Bottom line is, the idea that brain size is related to intelligence across species was examined from multiple angles and it always came up short.
But why? Why? Why?
Well, for a bunch of reasons. Let’s start with our first assumption: “bigger brains pack more neurons”. Remember that? Across species, that’s not always true. What’s more, which brain regions have more neurons is also very important. As an example, elephants have 3 times (!) more neurons than humans. But in elephants, a lot of these neurons are found in the cerebellum, not in the cortex (presumably to control the fine-grained movements of the trunk), the neurons themselves are larger, and their number per cubic millimeter is much lower (only 6.000-7.000 neurons/mm3, compared to 25.000-30.000 neurons/mm3 in humans).
In contrast, although crows have tiny brains compared both to humans and elephants, their neuronal density is nothing short of impressive: in the nidopallidum, a region used for executive tasks, it can reach about 130.000-160.000 neurons/mm3. With such numbers, it’s no wonder crows can rival and even outperform some primates on cognitive tasks.
However, as we’ll see more clearly in the next section, the number, density, or location of neurons aren’t the only factors that matter. How they are connected and how fast information can travel between them also play important roles.
The comparison within species
The comparisons above showed us that, across species, brain size isn’t a good predictor of intelligence. Brains don’t just scale up, but some of their properties, such as neuron density or size, also change between species. But within species, and more specifically between people, we don’t expect such significant differences. That’s why, before diving into more complex structural features, it’s worth asking again how the relation between brain size and intelligence holds up in humans.
It turns out that it works slightly better. There is a small, positive correlation between brain size and the g factor. The correlation coefficient r (which goes from -1 to 1, with 1 indicating perfectly correlated, 0 meaning no correlation, and -1 perfectly anticorrelated) sits in the range of 0.2-0.3. It’s not much, but it’s honest work. What’s more, separating the brain into gray and white matter and correlating their volumes with intelligence shows that gray matter is the driver of this effect. But even so, this only explains a small part of the picture. So… where is the rest coming from?
We’ve already hinted above that it has to do with connections and information speed. In more concrete terms, we know the brain is basically a network of neurons. And the information-processing capacity of this network is what translates into intelligence. Unfortunately, studying large networks like the brain and how their properties relate to constructs such as intelligence tends to be a bit…complicated. That’s why, even though gathering relevant data in humans is much easier compared to other species, the full picture is still quite murky.
What we know so far is that networks connected more efficiently appear to correlate with higher intelligence and that good myelination is important for cognitive processing speed. In terms of theories, perhaps the most well-established one is the parieto-frontal integration theory, which tells us that a network formed by lateral frontal and parietal areas is highly relevant for intelligence. However, newer studies suggest it’s not just these regions, but how the entire brain is structured, that determines intelligence.
To sum up
Brains are complicated. And although it seems easy to assume that larger brains with more neurons can do more, nature doesn’t agree. There still a lot of work needed to determine what makes a brain smart. But so far we’ve learned that where those neurons are situated and how efficiently information can flow between them trumps simple upscaling. Maybe something to keep in mind for other so-called “brain-like” systems.
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References
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