The Neuroscience of Intelligence (Book Review)

I am very impressed by this book. Given that it’s series by Cambridge and one of the leading scientists on intelligence, I had high hopes, but it managed to surpass it.

From the get-go what I loved the most was the fact that the author clearly admitted his bias towards biological explanations of intelligence. Everyone is biased, admitting and putting forth your bias is infinitely better than trying to hide it or being unaware of it. Nevertheless, it gives his reasoning on why that’s the case supported his 40 years of research.

The book is insanely well written, in almost every single point I can think of. It gives a succinct and necessary introduction, how intelligence research got started, its controversies and myths. Then moves on the impact of genetics, neuroimaging, intelligence manipulation, and ends with a nice reflection of the field in general. All of this is written in an accessible manner, which anyone could read without a neuroscience background, which is very impressive.

I was pleasantly surprised by how intellectually and scientifically honest Haier was. He was always careful to remind the limitations of the evidence and how no single study is conclusive. Typical problems of neuroscience, such as low sample sizes or lack of replication were often emphasized. He frequently pointed to null results and contradictory evidence, which is so crucial yet not very common.

The Neuroscience of Intelligence
By Richard J. Haier (2016)

He’s also quite humble on how he may be wrong and invites you to prove it. In the final chapter: “Speaking of you, reading also forces thinking. Even if you are convinced by my arguments, I challenge you to think critically about the studies I have presented throughout this book as representative of neuroscience progress and about what I think they mean. My challenge to you is to find weak links and loopholes in my presentation, and when you do, design a new research study to fix or falsify them”.

I wish it explored more on the role of the environment, brain plasticity and epigenetics. On the other hand, I felt sometimes he went in too much detail into neuroimaging techniques, adding little to his argument as a whole. But of course, it’s just my opinion and a hard thing to balance.

A quick summary of the points in the book:

• Intelligence can be defined for scientific research, against popular belief. Although it’s always relative among other people, and never a ratio scale.
• G-factor is a key and valid concept to estimate one’s intelligence, and IQ is a good correlate of G.
• Evidence validates the predictive validity of IQ tests and its importance for academic and life success.
• The genetic role of intelligence has been known for decades, but early proponents of it like Cyril Burt and Jensen were attacked and rejected.
• Modern quantitative genetic studies overwhelmingly support a major role of genes for intelligence.
• While environment plays a role in intelligence during early childhood, this diminishes almost entirely by teenagehood.
• Compensatory education has failed to improve IQ in the long-term
• Intelligence is a by-product of many genes, each with a small effect.
• Advanced DNA technologies with molecular genetics are beginning to identify genes that play a role in intelligence and their neurobiological mechanisms.
• Intelligence isn’t centred in any particular brain region, but rather seems to be expressed through networks.
• Higher intelligence seems to be the ability to progress information efficiently, as there is an inverse correlation between IQ scores and brain activity.
• Not all brains work the same way, and individual differences can’t be ignored. Group averages taint the data.
• The Parieto-frontal Integration Theory of intelligence (PFIT) has emphasized the structural and functional characteristics of specific brain areas and their connections
• New neuroimaging methods are discovering structural and functional brain networks related to intelligence test scores. Many consistent with the PFIT.
• While there has been some progress, it’s not yet possible to predict IQ scores based on brain measures.
• Individual differences between brain measures and intelligence have genes in common.
• There is no way of increasing intelligence that has survived independent replication with a reasonable weight of evidence. Most of the claims are full of methodological flaws.
• Psychoactive drugs and various non-drug methods like electrical stimulation show promise of enhancing cognition but no solid evidence so far.
• Chronometrics may be the measurement of intelligence of the future, by being able to assess intelligence on a ratio scale by tracking information processing in units of time.
• Memory is a key part of intelligence
• Brain fingerprints are stable and unique to individuals and can predict IQ.
• Given the role of neurobiology and genetics in cognitive ability, it’s incorrect to blame lack of economic or educational success exclusively to poor motivation, education or other social factors.

Richard J. Haier is an American psychologist best known for his work on the neural basis of human intelligence psychometrics, general intelligence, and sex and intelligence.

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Tiago V.F.