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Neuroscience and intelligence concerns the various neurological factors that may be responsible for the variation of intelligence within a species or between different species. Much of the work in this field is concerned with the variation in human intelligence, but other intelligent species such as the non-human primates and cetaceans are also of interest. The basic mechanisms by which the brain produces complex phenomena such as consciousness and intelligence are still poorly understood.

The research into the neuroscience of intelligence has involved indirect approaches, such as searching for correlations between psychometric test scores and variables associated with the anatomy and physiology of the brain. Historically, research was conducted on non-human animals or on postmortem brains as well as on skulls (Craniometry). More recent studies have involved non-invasive techniques such as MRI scans as they can be conducted on living subjects. MRI scans can be used to measure the size of various structures within the brain, or they can be used to detect areas of the brain that are active when subjects perform certain mental tasks.

Anatomy

Some of the anatomical variables that have been studied in association with psychometric test scores include total brain volume, the size and shape of the frontal lobes, the amount of grey and white matter, and the overall thickness of the cortex.

Brain size

Another theory of brain size in vertebrates is that it may relate to social rather than mechanical skill. Cortical size relates directly to a pairbonding life style and among primates cerebral cortex size varies directly with the demands of living in a large complex social network.

Within human population, studies have been conducted to determine whether there is a relationship between brain size and a number of cognitive measures. Studies have reported correlations of intelligence and brain size that range from 0 to 0.6, with most correlations 0.3 or 0.4 Some scientists prefer to look at more qualitative variables to relate to the size of measurable regions of known function, for example relating the size of the primary visual cortex to its corresponding functions, that of visual performance.

In a study of the head growth of 633 term-born children from the Avon Longitudinal Study of Parents and Children cohort, it was shown that prenatal growth and growth during infancy were associated with subsequent IQ. The study’s conclusion was that the brain volume a child achieves by the age of 1 year helps determine later intelligence. Growth in brain volume after infancy may not compensate for poorer earlier growth.

There is an association between IQ and myopia. One suggested explanation or several is that pleiotropic gene(s) affect the size of both brain and eyes simultaneously.

Specific regions

Luders and colleagues in a literature review (2009) write that the majority of data shows that both gray matter and white matter volume correlate with IQ but the correlation is stronger for gray matter. Increased number of neurons in the gray matter may explain the higher correlation but not necessarily so since glucose consumption and intelligence measures correlate negatively which may mean intelligent individuals use their neurons more efficiently, such as being more efficient in their formation of synapses between neurons which help to create more efficient neural circuitry. The white matter correlation may be due to more myelination or better control of pH and thus enhanced neural transmission. For more specific regions, the most frequently replicated positive correlations appear localized in the lateral and medial frontal lobe cortex. Positive correlations are also found with volume in many other areas. Cortical thickness may be a better measure than gray matter volume although this may vary with age with an initially negative correlation in early childhood becoming positive later. The explanation may again be that more intelligent individuals manage their synapses better. During evolution not only brain size but also brain folding has increased which has increased the surface area. Convolution data may support the "The Parieto-Frontal Integration Theory" which see medial cortex structures as particularly important. Volume of the corpus callosum or subareas were found to be important in several studies which may be due to more efficient inter-hemispheric information transfer.

In 2007, Behavioral and Brain Sciences published a target article that put forth a biological model of intelligence based on 37 peer-reviewed neuroimaging studies (Jung & Haier, 2007). Their review of a wealth of data from functional imaging (functional magnetic resonance imaging and positron emission tomography) and structural imaging (diffusion MRI, voxel-based morphometry, in vivo magnetic resonance spectroscopy) argues that that human intelligence arises from a distributed and integrated neural network comprising brain regions in the frontal and parietal lobes.

Brain injuries at an early age isolated to one side of the brain typically results in relatively spared intellectual function and with IQ in the normal range.

Glucose metabolic rate

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Other neurological parameters have been associated with IQ. Haier et al. (1995) found a correlation of -0.58 between glucose metabolic rate "GMR" (an indicator of energy use) and IQ. This suggested that intelligence is associated with more efficient brains. Others found a positive correlation between IQ and GMR (DeLeon et al. 1983; Chase et al. 1984). It seems like difference in results comes from different cognitive tasks (complicated vs. simple) that were performed by examinees (Fidelman, 1993).

Health

Several environmental factors related to health can lead to significant cognitive impairment, particularly if they occur during pregnancy and childhood when the brain is growing and the blood-brain barrier is less effective. Developed nations have implemented several health policies regarding nutrients and toxins known to influence cognitive function. These include laws requiring fortification of certain food products and laws establishing safe levels of pollutants (e.g. lead, mercury, and organochlorides). Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed.

References

1. Deary (2000). "Testing Versus Understanding Human Intelligence" (PDF). {{cite journal}}: Cite journal requires |journal= (help)
2. Dunbar RI, Shultz S (2007-09-07). "Evolution in the social brain". "Science". 317 (5843): 1344–1347. doi:10.1126/science.1145463. PMID 17823343. {{cite journal}}: Unknown parameter |unused_data= ignored (help)
3. Witelson, SF; Beresh, H; Kigar, DL (2006). "Intelligence and Brain Size in 100 Postmoterm Brains". Brain : a journal of neurology. 129 (Pt 2): 386–98. doi:10.1093/brain/awh696. PMID 16339797.
4. Brain size does not predict cognitive abilities within families
5. Brain size and intelligence
6. Catharine R. Gale, PhD, Finbar J. O'Callaghan, PhD, Maria Bredow, MBChB, Christopher N. Martyn, DPhil and the Avon Longitudinal Study of Parents and Children Study Team (October 4, 2006). "The Influence of Head Growth in Fetal Life, Infancy, and Childhood on Intelligence at the Ages of 4 and 8 Years". PEDIATRICS Vol. 118 No. 4 October 2006, pp. 1486-1492. Retrieved August 6, 2006.{{cite web}}: CS1 maint: multiple names: authors list (link)
7. Attention: This template ({{cite pmid}}) is deprecated. To cite the publication identified by PMID 19127804, please use {{cite journal}} with |pmid=19127804 instead.
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9. Richard Haier & Rex Jung (July 26, 2007). "The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence". Cambridge University Press. Retrieved September 28, 2009.
10. Bava, Sunita; Ballantyne, Angela O; Trauner, Doris A (2005). "Disparity of Verbal and Performance IQ Following Early Bilateral Brain Damage". Cognitive and Behavioral Neurology. 18 (3): 163–70. doi:10.1097/01.wnn.0000178228.61938.3e. PMID 16175020.
11. Olness, K. "Effects on brain development leading to cognitive impairment: a worldwide epidemic," Journal of Developmental and Behavioral Pediatrics 24, no. 2 (2003): 120–30.

External links

• Neuroscience for Kids
• Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience, 11, 201-211. PDF
• Michael A. McDaniel, Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence, Intelligence, Volume 33, Issue 4, July–August 2005, Pages 337-346. PDF
• Jeremy R. Gray, Psychology Department, Yale University, and Paul M. Thompson, Laboratory of Nero Imaging, Department of Neurology, University of California, Los Angeles School of Medicine (2004). "Neurobiology of Intelligence: Science and Ethics" (PDF). Nature Publishing Group, Volume 5. Retrieved August 6, 2006. {{cite web}}: Unknown parameter |month= ignored (help)CS1 maint: multiple names: authors list (link)

• Neuropsychology
• Factors related to intelligence