[6] Analyses of the parameters of intellectual systems, patterns of their emergence and evolution, distinctive features, and the constants and limits of their structures and functions made it possible to measure and compare the capacity of communications (~100 m/s), to quantify the number of components in intellectual systems (~1011 neurons), and to calculate the number of successful links responsible for cooperation (~1014 synapses).
[1] The specific regions that show the most robust correlation between volume and intelligence are the frontal, temporal and parietal lobes of the brain.
[10][11][12] A large number of studies have been conducted with uniformly positive correlations, leading to the generally safe conclusion that larger brains predict greater intelligence.
A meta-analytic review by McDaniel found that the correlation between intelligence and in vivo brain size was larger for females (0.40) than for males (0.25).
For instance evidence suggests that in adolescents learning new words, vocabulary growth is associated with gray matter density in bilateral posterior supramarginal gyri.
[22] Taking into account measurement quality, and sample type and IQ-range, the meta-analytic association of brain volume in appears to be ~ .4 in normal adults.
[15] Researcher Jakob Pietschnig argued that the strength of the positive association of brain volume and IQ remains robust, but has been overestimated in the literature.
[1] More specifically, higher intelligence has been associated with larger cortical grey matter in the prefrontal and posterior temporal cortex in adults.
[24] One specific methodology used to study grey matter correlates of intelligence in areas of the brain is known as voxel-based morphometry (VBM).
VBM has been used to correlate grey matter positively with intelligence in the frontal, temporal, parietal, and occipital lobes in healthy adults.
[26] VBM has also been successfully used to establish a positive correlation between grey matter volumes in the anterior cingulate and intelligence in children aged 5 to 18 years old.
[27] An underlying caveat to research into the relationship of grey matter volume and intelligence is demonstrated by the hypothesis of neural efficiency.
[32] Anatomical mesh-based geometrical modelling[33][34][35] has also shown positive correlations between the thickness of the corpus callosum and Intelligence in healthy adults.
[5] These findings indicate that the brain is structurally interconnected and that axonal fibres are integrally important for fast information process, and thus general intelligence.
It has been hypothesized that the high degree of cortical convolution may be a neurological substrate that supports some of the human brain's most distinctive cognitive abilities.
[39][40] The neural efficiency hypothesis postulates that more intelligent individuals display less activation in the brain during cognitive tasks, as measured by Glucose metabolism.
[6] A small sample of participants (N=8) displayed negative correlations between intelligence and absolute regional metabolic rates ranging from -0.48 to -0.84, as measured by PET scans, indicating that brighter individuals were more effective processors of information, as they use less energy.
[6] According to an extensive review by Neubauer & Fink[41] a large number of studies (N=27) have confirmed this finding using methods such as PET scans,[42] EEG[43] and fMRI.
[52] 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).
[53] A recent lesion mapping study conducted by Barbey and colleagues provides evidence to support the P-FIT theory of intelligence.
[58] Intelligence in chimpanzees has been found to be related to brain size, grey matter volume, and cortical thickness, as in humans.
[59] 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.