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Big Brains
Neuroscientist Paul Thompson is one of those researchers studying brain structure and IQ, but that wasn’t what he planned on when he started his lab at UCLA: he focused on the wave of changes in the brain that characterize Alzheimer’s and schizophrenia. Because serious cognitive deficits accompany both of those diseases, however, Thompson and his collaborators tested cognitive function in their subjects. When they began to look more closely for variables that correlated with brain structure, they found that intelligence seemed to be among the most significant. “IQ came in as a key factor that determines how the brain looks,” Thompson says.

Scientists who study intelligence typically define it in comparative terms, as a general cognitive ability measured against a mean. A quantifiable “general intelligence factor,” known as g, can be statistically extracted from scores on a battery of intelligence tests. While some people clearly have particular areas of talent, those who score well on one test are likely to score well on others as well, reflecting a higher g.

Researchers have yet to find a simple neural explanation for g. In 2001, Thompson showed that it is correlated with volume in the frontal cortex, a result consistent with a number of studies that have linked intelligence to overall brain size. But size is a crude measure: while larger brains may be smarter on average, it’s not clear if that’s because they have more nerve cells, more connections between cells, or more of the fibers that carry neural signals. Any of these factors can result in a larger brain or thicker cortex, but neither of these things is necessary for great intelligence. Studies of Albert Einstein’s brain, for example, have found that it was typical in size, or even a bit on the small side. (It was missing a wrinkle in the inferior parietal lobe, which is behind the frontal cortex; some have speculated that this quirk allowed the neurons in that region to communicate more effectively.)

As structural brain imaging has become more sophisticated, scientists have focused on sections of the brain involved in specific tasks, including sensory processing, memory, attention, and decision making. Different studies have connected different areas with intelligence, however, making it difficult to come to an overarching conclusion about its anatomical basis.

But what if the key to intelligence is neither an individual area of the brain nor its total volume but the network over which information is transmitted and integrated? In 2007, Jung and Richard Haier, now professor emeritus of psychology at the University of California, Irvine, developed the first comprehensive theory drawn from neuroimaging of how the brain gives rise to intelligence. Gathering information from 37 published papers that had used imaging to study intelligence, they mapped out the brain areas that had been pinpointed in at least a third of the studies to sketch a network of regions spanning the frontal and parietal lobes.

The network consists of about 10 nodes, or clusters of cells, that had been linked to attention, working memory, and facial recognition, among other cognitive functions. Applying existing theories of how information flows in the brain, Jung and Haier hypothesized that neural signals travel from nodes near the back of the brain, where sensory data is collected and synthesized, to those in the frontal lobes, which are responsible for decision making and planning. The connections between these nodes, they argued, are just as critical as the nodes themselves. “If the nodes of a network aren’t communicating effectively and efficiently, then the network won’t function efficiently,” says Jung.

The theory was provocative, but the data used to develop it had a major limitation: the published studies had focused primarily on gray matter. As for the connecting white matter, Jung and Haier inferred its paths from the locations of the key nodes and existing maps of neural anatomy. They didn’t look directly at the white matter itself, largely because they lacked the technology to do so.

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Credits: Andrew Frew/Brainlab, Paul Thompson
Video by Erica Kraus

Tagged: Biomedicine, imaging, brain, MRI, neural network, cognitive enhancement, intelligence, cognitive ability

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