Neuroscience and intelligence: Difference between revisions
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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. There is clear agreement within the scientific community about the measurement of intelligence, but not, yet, its bio-social basis.<ref name="deary"/> The basic mechanisms by which the brain produces complex phenomena such as consciousness and intelligence are still poorly understood.<ref name="deary">{{cite journal|last=Deary|year=2000|url= http://www.psycnet.org/journals/law/6/1/180.pdf|title=Testing Versus Understanding Human Intelligence}}</ref> |
'''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. There is clear agreement within the scientific community about the measurement of intelligence, but not, yet, its bio-social basis.<ref name="deary"/> The basic mechanisms by which the brain produces complex phenomena such as consciousness and intelligence are still poorly understood.<ref name="deary">{{cite journal|last=Deary|year=2000|url= http://www.psycnet.org/journals/law/6/1/180.pdf|title=Testing Versus Understanding Human Intelligence}}</ref> |
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Much of 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. 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. |
Much of 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. |
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==Anatomy== |
==Anatomy== |
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===Brain size=== |
===Brain size=== |
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Rushton and Jensen (2010) argue that the brain is metabolically demanding. In rats, cats, and dogs it uses about 5% of the body's energy. In primates, 10%. In humans, 20%. Larger brain are also expensive evolutionary since they take time to grow and requires larger bodies to produce and sustain them. So an increased brain size would not have evolved unless it gives great evolutionary advantages. They argue that brain size and [[brain-to-body mass ratio]] has been increasing for the last 575 million years. Mammals living 65 million years ago had substantially lower brain size than today. The [[hominid]] brain has tripled in size over the last 3 million years from [[Australopithecus]] to [[Homo erectus]] to modern humans. The claim that [[Neanderthal]]s had average larger crania than anatomically modern humans has been falsified. Looking at brain to body size it was slightly smaller. They further argue that any decrease in average brain size over the past 35,000 years has been paralleled by a corresponding decrease in average body size suggesting no change in the ratio of brain to body size.<ref name=RJ2010ResponseToNisbett>{{cite journal |author=J. Philippe Rushton and Arthur R. Jensen |title=Race and IQ: A theory-based review of the research in Richard Nisbett's Intelligence and How to Get It |journal=The Open Psychology Journal |volume=3 |pages=9–35 |year=2010 |url=http://psychology.uwo.ca/faculty/rushtonpdfs/2010%20Review%20of%20Nisbett.pdf |doi= 10.2174/1874350101003010009 |ref=harv}}</ref> |
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When comparing different species, the ratio of brain weight to body weight does [[Correlation does not imply causation|correlate]] with [[Intelligence]],{{Citation needed|date=December 2010}} although the actual brain weight has little or no effect. For example, the ratio of brain weight to body weight for fish is 1:5000; for reptiles it is about 1:1500; for birds, 1:220; for most [[mammals]], 1:180, and for [[humans]], 1:50.{{Citation needed|date=December 2010}} |
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Brain size is an import variable in Rushton's r-K theory which he described in his book ''[[Race, Evolution, and Behavior]]'' (1995). Rushton (2004) argued that the theory was supported by relationships between brain weight and several other variables among 234 [[mammalian]] species: longevity (r = .70), gestation time (.72), birth weight (.44), litter size (-.43), age at first mating (.63), duration of lactation (.62), body weight (.44), and body length (.54). The relationship remained after controlling for body weight and body length. Looking 21 [[primate]] species, brain size still correlated .80 to .90 with life span, length of gestation, age of weaning, age of eruption of first molar, age at complete dentition, age at sexual maturity, inter-birth interval, and body weight.<ref>{{cite doi|10.1016/j.intell.2004.06.003}}</ref> |
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| ⚫ | 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 that range from 0 to 0.6, with most correlations 0.3 or 0.4<ref>{{cite journal|last=Witelson|url=http://brain.oxfordjournals.org/cgi/content/abstract/129/2/386|title=Intelligence and Brain Size in 100 Postmoterm Brains|year=2006|pmid=16339797|doi=10.1093/brain/awh696|first1=SF|last2=Beresh|first2=H|last3=Kigar|first3=DL|volume=129|issue=Pt 2|pages=386–98|journal=Brain : a journal of neurology}}</ref> |
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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.<ref>[http://www.pnas.org/cgi/content/full/97/9/4932 Brain size does not predict [[cognitive abilities]] within families]</ref><ref>[http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=neurosci.box.1833 Brain size and intelligence]</ref> |
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| ⚫ | 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 (sociology)|life style]] and among primates cerebral cortex size varies directly with the demands of living in a large complex social network.<ref>{{cite journal|unused_data=issue5843|author=Dunbar RI, Shultz S|date=2007-09-07|title=Evolution in the social brain|journal=“Science”|volume=317|pages=1344–1347|doi=10.1126/science.1145463|pmid=17823343|issue=5843}}</ref> |
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The brain is a metabolically expensive organ, and consumes about 25 percent of the body's metabolic energy in some species. Therefore, although larger brains are associated with higher intelligence, smaller brains might be advantageous from an [[evolutionary]] point of view if they are equal in intelligence to larger brains. [[Skull]] size correlates with brain size, but is not necessarily indicative. |
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| ⚫ | 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 that range from 0 to 0.6, with most correlations 0.3 or 0.4<ref>{{cite journal|last=Witelson|url=http://brain.oxfordjournals.org/cgi/content/abstract/129/2/386|title=Intelligence and Brain Size in 100 Postmoterm Brains|year=2006|pmid=16339797|doi=10.1093/brain/awh696|first1=SF|last2=Beresh|first2=H|last3=Kigar|first3=DL|volume=129|issue=Pt 2|pages=386–98|journal=Brain : a journal of neurology}}</ref> 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.<ref>[http://www.pnas.org/cgi/content/full/97/9/4932 Brain size does not predict [[cognitive abilities]] within families]</ref><ref>[http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=neurosci.box.1833 Brain size and intelligence]</ref> |
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| ⚫ | |||
Rushton and Ankney (2009) in a literature review write that in 28 samples using brain imaging techniques the mean brain size/''g'' correlation was 0.40 (N = 1,389). In 59 samples using external head size measures it was 0.20 (N = 63,405). In 6 studies that corrected for that different IQ subtests measure ''g'' unequally well, the mean correlation was 0.63. Some studies have found the whole brain to be important for ''g'' while others have found the [[frontal lobe]]s to be particularly important. Two studies founds correlations of 0.48 and 0.56 between brain size and the number of [[neuron]]s in the [[cerebral cortex]] (based on counting in representative areas.<ref>{{cite doi|10.1080/00207450802325843}}</ref> |
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Here is a list of some species, along with their rough average brain sizes: |
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*''[[Homo erectus]]'': 980 cm³ |
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*''[[Homo habilis]]'': 750 cm³ |
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*''[[Homo floresiensis]]'': 380 cm³ |
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*''[[Neanderthal|Homo neanderthalensis]]'': 1200–1750 cm³ skull capacity (10 percent greater than modern human average, when including juvenile cranial capacity) |
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*''[[Human|Homo sapiens]]'': 1350–1400 cm³{{Citation needed|reason=if range false if average why 2 numbers|date=September 2008}} |
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A [[twin study|study on twins]] (Thompson ''et al.'', 2001){{verify source|date=November 2010}} showed that frontal [[gray matter]] volume was correlated with ''[[General intelligence factor|g]]'' and highly [[heritable]]. A related study has reported that the correlation between brain size (reported to have a [[heritability]] of 0.85) and ''g'' is 0.4, and that correlation is mediated entirely by genetic factors (Posthuma et al. 2002).{{verify source|date=November 2010}} |
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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.<ref>{{Cite web |
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.<ref>{{Cite web |
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}}</ref> |
}}</ref> |
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=== Specific regions === |
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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 [[synapse]]s 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 [[Anatomical terms of location|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.<ref>{{cite doi|10.1016/j.intell.2008.07.002}}</ref> |
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Many different sources of information have converged on the view that the frontal lobes are critical for [[fluid intelligence]]. Patients with damage to the [[frontal lobe]] are impaired on fluid intelligence tests (Duncan et al. 1995). The volume of frontal grey (Thompson et al. 2001) and white matter (Schoenemann et al. 2005) have also been associated with general intelligence. In addition, recent neuroimaging studies have limited this association to the lateral prefrontal cortex. Duncan and colleagues (2000) showed using [[Positron Emission Tomography]] that problem-solving tasks that correlated more highly with IQ also activate the lateral [[prefrontal cortex]]. More recently, Gray and colleagues (2003) used functional magnetic resonance imaging (fMRI) to show that those individuals that were more adept at resisting distraction on a demanding working memory task had both a higher IQ and increased prefrontal activity.<ref>{{Cite web |
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|url=http://www.loni.ucla.edu/~thompson/PDF/nrn0604-GrayThompson.pdf |
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|format=PDF|title= Neurobiology of Intelligence: Science and Ethics |
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|accessdate=August 6, 2006 |month=June | year=2004 |
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|author= 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 |
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|publisher=Nature Publishing Group, Volume 5 |
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}}</ref> |
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In 2004, Richard Haier, professor of psychology in the Department of Pediatrics and colleagues at [[University of California, Irvine]] and the [[University of New Mexico]] used [[MRI]] to obtain structural images of the brain in 47 normal adults who also took standard IQ tests. The study demonstrated that general human intelligence appears to be correlated with the volume and location of [[gray matter]] tissue in the brain. Although the regional distribution of gray matter in humans may have a genetic basis, structural changes can also occur in response to environmental stimulation. The study also demonstrated that, of the brain's gray matter, only about 6 percent appeared to be related to IQ.<ref>{{Cite web |
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|url=http://today.uci.edu/news/release_detail.asp?key=1187 |
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|title=Human Intelligence Determined by Volume and Location of Gray Matter Tissue in Brain |
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|accessdate=August 6, 2006 |date=July 19, 2004 |
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|author=Richard Haier |
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|publisher=Brain Research Institute, UC Irvine College of Medicine |
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}}</ref> |
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A study involving 307 children (age between six to nineteen) measuring the size of brain structures using magnetic resonance imaging (MRI) and measuring verbal and non-verbal abilities has been conducted (Shaw et al. 2006). The study has indicated that there is a relationship between IQ and the structure of the cortex—the characteristic change being the group with the superior IQ scores starts with thinner cortex in the early age then becomes thicker than average by the late teens.<ref>{{Cite web |
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|url=http://www.bri.ucla.edu/bri_weekly/news_060330.asp |
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|title=Scans Show Different Growth for Intelligent Brains |
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|accessdate=August 6, 2006 |date=March 30, 2006 |
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|author=Nicholas Wade |
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|publisher=Brain Research Institute, UCLA.. |
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}}</ref> |
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== Neurobiology == |
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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). |
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==Genetics== |
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Variation in psychometric test scores is affected by both environmental and genetic factors. Much study into the heritability of intelligence uses twin studies. In neuroscience, twin studies are used to determine the heritability of neurological variables such as total brain volume or the amount of white matter.{{Citation needed|date=November 2010}} While there are around two thousand genes linked to severe mental disability, at present, there is no widely replicated instance of a gene that is associated with normal IQ differences. Researchers who carry out twin studies caution that even high estimates of heritability have nothing to say about how much environmental factors can influence a behavioral trait such as [[Intelligence quotient|IQ]].<ref>{{Cite journal |last1=Johnson |first1=Wendy |last2=Turkheimer |first2=E. |last3=Gottesman |first3=Irving |last4=Bouchard |first4=Thomas |year=2009 |title=Beyond Heritability: Twin Studies in Behavioral Research |journal=Current Directions in Psychological Science |publisher= |volume=18 |issue=4 |pages=217–220 |url=http://people.virginia.edu/~ent3c/papers2/Articles%20for%20Online%20CV/Johnson%20%282009%29.pdf |accessdate=29 June 2010 |doi=10.1111/j.1467-8721.2009.01639.x |pmc=2899491 |pmid=20625474 |ref=harv }}</ref><ref>{{Cite journal |last=Turkheimer |first=Eric |year=2008 |month=April |title=A Better Way to Use Twins for Developmental Research |journal=LIFE Newsletter |volume=2 |issue=1 |publisher=Max Planck Institute for Human Development |pages=2–5 |url=http://people.virginia.edu/~ent3c/papers2/Articles%20for%20Online%20CV/Turkheimer%20%282008%29.pdf |accessdate=29 October 2010 |doi= |ref=harv }}</ref> |
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==Parieto-frontal integration theory (P-FIT)== |
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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.<ref>{{Cite web |
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.<ref>{{Cite web |
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|publisher=Cambridge University Press |
|publisher=Cambridge University Press |
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}}</ref> |
}}</ref> |
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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.<ref>{{cite journal |last1=Bava |first1=Sunita |last2=Ballantyne |first2=Angela O |last3=Trauner |first3=Doris A |title=Disparity of Verbal and Performance IQ Following Early Bilateral Brain Damage |journal=Cognitive and Behavioral Neurology |volume=18 |issue=3 |pages=163–70 |year=2005 |pmid=16175020 |doi= 10.1097/01.wnn.0000178228.61938.3e}}</ref> |
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== 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). |
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== Height == |
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{{main|Height and intelligence}} |
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Epidemiological studies have shown that intelligence is positively correlated with body [[human height|height]] in human populations. One possible explanation is that it may be explained by differences in brain size, which is a correlated with height. |
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It has been suggested that the large increases in average height, assumed to be due to improved nutrition, have been accompanied by an increase in brain size which may be one explanation for the [[Flynn effect]].<ref>{{cite doi|10.1037/0003-066X.51.2.77}}</ref> |
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== Health == |
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{{main|Health and intelligence}} |
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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 [[food fortification|fortification]] of certain food products and laws establishing safe levels of pollutants (e.g. [[lead]], [[mercury (element)|mercury]], and organochlorides). Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed.<ref name="Olness">Olness, K. "[http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&list_uids=12692458&dopt=Citation Effects on brain development leading to cognitive impairment: a worldwide epidemic]," ''Journal of Developmental and Behavioral Pediatrics'' 24, no. 2 (2003): 120–30.</ref> |
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== See also == |
== See also == |
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Revision as of 14:21, 19 March 2011
| Types | |
|---|---|
| Abilities, traits, and constructs | |
| Models and theories | |
| Areas of research | |
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. There is clear agreement within the scientific community about the measurement of intelligence, but not, yet, its bio-social basis.[1] The basic mechanisms by which the brain produces complex phenomena such as consciousness and intelligence are still poorly understood.[1]
Much of 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
Rushton and Jensen (2010) argue that the brain is metabolically demanding. In rats, cats, and dogs it uses about 5% of the body's energy. In primates, 10%. In humans, 20%. Larger brain are also expensive evolutionary since they take time to grow and requires larger bodies to produce and sustain them. So an increased brain size would not have evolved unless it gives great evolutionary advantages. They argue that brain size and brain-to-body mass ratio has been increasing for the last 575 million years. Mammals living 65 million years ago had substantially lower brain size than today. The hominid brain has tripled in size over the last 3 million years from Australopithecus to Homo erectus to modern humans. The claim that Neanderthals had average larger crania than anatomically modern humans has been falsified. Looking at brain to body size it was slightly smaller. They further argue that any decrease in average brain size over the past 35,000 years has been paralleled by a corresponding decrease in average body size suggesting no change in the ratio of brain to body size.[2]
Brain size is an import variable in Rushton's r-K theory which he described in his book Race, Evolution, and Behavior (1995). Rushton (2004) argued that the theory was supported by relationships between brain weight and several other variables among 234 mammalian species: longevity (r = .70), gestation time (.72), birth weight (.44), litter size (-.43), age at first mating (.63), duration of lactation (.62), body weight (.44), and body length (.54). The relationship remained after controlling for body weight and body length. Looking 21 primate species, brain size still correlated .80 to .90 with life span, length of gestation, age of weaning, age of eruption of first molar, age at complete dentition, age at sexual maturity, inter-birth interval, and body weight.[3]
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.[4]
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 that range from 0 to 0.6, with most correlations 0.3 or 0.4[5] 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.[6][7]
Rushton and Ankney (2009) in a literature review write that in 28 samples using brain imaging techniques the mean brain size/g correlation was 0.40 (N = 1,389). In 59 samples using external head size measures it was 0.20 (N = 63,405). In 6 studies that corrected for that different IQ subtests measure g unequally well, the mean correlation was 0.63. Some studies have found the whole brain to be important for g while others have found the frontal lobes to be particularly important. Two studies founds correlations of 0.48 and 0.56 between brain size and the number of neurons in the cerebral cortex (based on counting in representative areas.[8]
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.[9]
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.[10]
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.[11]
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.[12]
Glucose metabolic rate
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).
Height
Epidemiological studies have shown that intelligence is positively correlated with body height in human populations. One possible explanation is that it may be explained by differences in brain size, which is a correlated with height.
It has been suggested that the large increases in average height, assumed to be due to improved nutrition, have been accompanied by an increase in brain size which may be one explanation for the Flynn effect.[13]
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.[14]
See also
References
- ^ a b Deary (2000). "Testing Versus Understanding Human Intelligence" (PDF).
{{cite journal}}: Cite journal requires|journal=(help) - ^ J. Philippe Rushton and Arthur R. Jensen (2010). "Race and IQ: A theory-based review of the research in Richard Nisbett's Intelligence and How to Get It" (PDF). The Open Psychology Journal. 3: 9–35. doi:10.2174/1874350101003010009.
{{cite journal}}: Invalid|ref=harv(help) - ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1016/j.intell.2004.06.003, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1016/j.intell.2004.06.003instead. - ^ 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) - ^ 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.
- ^ Brain size does not predict cognitive abilities within families
- ^ Brain size and intelligence
- ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1080/00207450802325843, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1080/00207450802325843instead. - ^ 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) - ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1016/j.intell.2008.07.002, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1016/j.intell.2008.07.002instead. - ^ 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.
- ^ 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.
- ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1037/0003-066X.51.2.77, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with
|doi=10.1037/0003-066X.51.2.77instead. - ^ 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.
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