The Neuroscience Of Intelligence by Richard J. Haier

Author:Richard J. Haier
Language: eng
Format: epub, pdf
Tags: Neuroscience, Intelligence, Psychometrics, Psychology, IQ, heritability, complex traits, genetics, cognitive neuroscience
Published: 2016-12-28T05:00:00+00:00

amount of gray matter in eight PFIT areas identified by numbered Brodmann area (L, left; R, right). The y-axis is based on standardized gray matter scores so positive numbers show values greater than the group mean; negative numbers show values less than the group mean. Although the profile shapes are similar for these two individuals, one has substantially more gray matter in the eight areas than the other (courtesy Richard Haier).

There is another potential application for predicting IQ. As we discussed in Chapter 1, the g -factor definition of intelligence is sufficient for many empirical research questions, but what if we could define intelligence based on quantifiable brain measures instead of psychometric scores? If brain parameters can predict IQ, then why not define IQ in terms of brain parameters? We do not know if twice the amount of gray matter in a particular part of the cortex, for example, makes one twice as smart. We are now able to explore redefining intelligence in ways that incorporate neurometric assessments. In the next chapter , we will explore this idea further when we discuss future research possibilities.

So can intelligence be predicted from neuroimaging? The short answer is, no. The longer answer is, not yet. So far, the weight of evidence is promising but not compelling. Look at the MEG movies of brain activation patterns for different individuals correctly solving the same single problem ( Textbox 4.2 links). How can these patterns be understood? Is there one particular pattern of brain variables, a unitary neuro-g, which correlates with the psychometric g-factor, or are there multiple brain patterns that imply many neuro-g factors (Haier et al., 2009)? So far, we do not know. It is my speculation, however, that should a cross-validated method become available to predict IQ or SAT scores accurately from brain images, many parents of high school students will be eager to use it and lobby institutions of higher education to do so as well. Imagine that.

Stop imagining! Just as I was finishing the final draft of this book, a remarkable new study reports that the pattern of connectivity among brain areas based on fMRI is stable within a person and unique enough to identify that person like a fingerprint (Finn et al., 2015 ). And, these brain fingerprints predict intelligence. This study comes from a large collaborative project that aims to map all the connections in the human brain. I have added a more detailed description of this study at the end of Section 6.4 . but at this point I am

ready to change the answer about predicting intelligence from neuroimaging from “not yet” to “looking good.” Very good - see more at the end of Section 6.4 .

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