Book Summary: “The Neuroscience of Intelligence”, Richard J. Haier

The Neuroscience of Intelligence, Richard J. Haier
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The Neuroscience of Intelligence, Richard J. Haier

“The Neuroscience of Intelligence”, Richard J. Haier
251 pages – Paperback | eBook

This summary is part of an ongoing project to read, note and summarise ~70 books on Learning How to Learn - for more, see the full reading list.

TYPE: Non-fiction (science), theoretical.

SYNTHESIS: A neuroscience-heavy, research-rich review of the evidence, myths and future of our understanding of intelligence – including what it is, why some people have it and what can be done to enhance it – by psychologist and professor, Richard J. Haier.

WHY ARE SOME PEOPLE SMARTER?

  • What is intelligence? Intelligence can be split into:
    • Specific Intelligence: The ability to quickly solve specific types of problem (e.g., reasoning, spatial ability, memory, processing speed, vocabulary).
    • General Intelligence (g): A core, general ability to quickly solve many types of novel problems.
  • How can we measure g? Psychometric tests are still the best (/only) way to approximate g (though imperfect and only ever peer-relative). Neuroimaging is not yet practical for predicting intelligence but that could change in the future.
  • Why does g matter?
    • g (as estimated above) correlates with many real-world outcomes like general learning ability, job performance and adult mortality, regardless of socio-economic status.
    • Establishing the primary cause(s) of g and the potential ability to enhance it, therefore, have important implications for educational and social policy.
  • What causes g (nature/nurture)? A controversial topic. Recent evidence suggests roles for genetic and early environmental factors. All we know for sure for now is that the story is complex – made more so by numerous emerging research methods and conflicting findings, not all of which are rigorous or replicable.
    • Anatomical: Neuroimaging studies support theories such as P-FIT (Parieto-frontal Integration Theory) which propose that g depends on the functioning of and coordination between several distributed structures in the brain.
    • Biological: Evidence point to a probabilistic combination of genetic (nature) and epigenetic (nature + nurture) factors (i.e., predispositions + environment => intelligence) though much more research is needed to explore and identify specific factors.

How can we enhance intelligence?

There are currently no proven ways to enhance g with a compelling weight of evidence behind them.

  • Myths that lack evidence but are widely believed include listening to classical music (The Mozart Effect), general memory training and playing computer games.
  • Opportunities: Will depend on further research but psychoactive drugs and genetics are promising.

What does the future look like?

  • Chronometric (neural, speed based testing) assessments may give us an absolute way to measure g.
  • Neural studies of memory and super-memory may shed more light on and give ways to enhance g.
  • Increasingly granular measurement and manipulation (e.g., via opto– and chemogenetics) of neural circuits in animal models may unlock insights that can be extrapolated to humans.
  • Developments in biotech may allow us to bridge human and machine intelligence circuit by circuit, leading to profound advances in our understanding of both.
  • Imaging studies of consciousness and creativity may prove a fruitful avenue for investigating g.
  • The more we learn about intelligence, the more pressingly we must engage morally and practically with issues of Neuro-Poverty (aspects of poverty that result mostly from the genetic aspects of intelligence) and Neuro-Social-Economic-Status in Public Policy.

PERSONAL THOUGHTS

On the role of time and changing support factors in g: How do we consider g on a day-by-day or even hour-by-hour basis? A “bright” person with poor mood, energy and attention management may perform exceptionally some days but poorly on others. Are they more or less intelligent than someone who scores lower than the first’s top scores but higher than them on average due to more consistent management of these factors?

On the book’s style: A superbly structured and written book that skilfully weaves quantitative data with qualitative reasoning. Thoroughly rooted in and makes good use of current research. In particular, I love the chapter structure:

  • Quotes – Introduces the different sides of the debate
  • Learning objectives – Primes reader with key points
  • Introduction – Sets the scene and outlines the chapter
  • Sections – Clearly presents the debate mixing hard science and clear English.
  • Summary – Recaps the main arguments.
  • Review questions – Tests active recall.
  • Further reading – Points to more of the same.

The layout and contents of the glossary, index and reference sections of the book are also good.

CONTENTS:

1 – WHAT WE KNOW ABOUT INTELLIGENCE FROM THE WEIGHT OF STUDIES

  1. What is Intelligence? Do You Know It When You See It?
  2. Defining Intelligence for Empirical Research
  3. The Structure of Mental Abilities and the g-Factor
  4. Alternative Models
  5. Focus on the g-Factor
  6. Measuring Intelligence and IQ
  7. Some Other Intelligence Tests
  8. Myth: Intelligence Tests are Biased or Meaningless
  9. The Key Problem for “Measuring” Intelligence
  10. Four Kinds of Predictive Validity for Intelligence Tests
  11. Why Do Myths About Intelligence Definitions and Measurement Persist?

2 – NATURE MORE THAN NURTURE: THE IMPACT OF GENETICS ON INTELLIGENCE

  1. The Evolving View of Genetics
  2. Early Failures to Boost IQ
  3. “Fraud” Fails to Stop Genetic Progress
  4. Quantitative Genetic Findings also Support a Role for Environmental Factors
  5. Molecular Genetics and the Hunt for Intelligence Genes
  6. Seven Recent Noteworthy Studies of Molecular Genetic Progress

3 – PEEKING INSIDE THE LIVING BRAIN: NEUROIMAGING IS A GAME-CHANGER FOR INTELLIGENCE RESEARCH

  1. The First PET Studies
  2. Brain Efficiency
  3. Not All Brains Work in the Same Way
  4. What the Early PET Studies Revealed and What They Did Not
  5. The First MRI Studies
  6. Basic Structural MRI Findings
  7. Improved MRI Analyses Yield Consistent and Inconsistent Results
  8. Imaging White Matter Tracts with Two Methods
  9. Functional MRI (fMRI)
  10. The Parieto-frontal Integration Theory (PFIT)
  11. Einstein’s Brain Chapter

4 – 50 SHADES OF GRAY MATTER: A BRAIN IMAGE OF INTELLIGENCE IS WORTH A THOUSAND WORDS

  1. Brain Networks and Intelligence
  2. Functional Brain Efficiency – is Seeing Believing?
  3. Predicting IQ From Brain Images
  4. Are “Intelligence” and “Reasoning” Synonyms?
  5. Common Genes for Brain Structure and Intelligence
  6. Brain Imaging and Molecular Genetics

5 – THE HOLY GRAIL: CAN NEUROSCIENCE BOOST INTELLIGENCE?

  1. Case 1: Mozart and the Brain
  2. Case 2: You Must Remember This, and This, and This …
  3. Case 3: Can Computer Games for Children Raise IQ?
  4. Where are the IQ Pills?
  5. Magnetic Fields, Electric Shocks, and Cold Lasers Target Brain Processes
  6. The Missing Weight of Evidence for Enhancement

6 – NEUROSCIENCE ADVANCES, WHAT’S NEXT FOR INTELLIGENCE RESEARCH?

  1. From Psychometric Testing to Chronometric Testing
  2. Cognitive Neuroscience of Memory and Super-Memory
  3. Bridging Human and Animal Research with New Tools Neuron by Neuron
  4. Bridging Human and Machine Intelligence Circuit by Circuit
  5. Consciousness and Creativity
  6. Neuro-poverty and Neuro-Social– Economic Status (SES): Implications for Public Policy Based on the Neuroscience of
  7. Final Thoughts
Arthur
Arthur
Arthur is a learning-freak, slow-thinker, and writer who loves helping curious, busy people digest chewy topics fast. One of his passions is language learning. Send yourself his Free Ultimate Language Learning Guide today to save you or a friend thousands of dollars and hours on your journey to fluency.

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