Associations between cortical thickness and general intelligence in children,adolescents and young adults

Neuroimaging research indicates that human intellectual ability is related to brain structure including the thickness of the cerebral cortex. Most studies indicate that general intelligence is positively associated with cortical thickness in areas of association cortex distributed throughout both brain hemispheres. In this study, we performed a cortical thickness mapping analysis on data from 182 healthy typically developing males and females ages 9 to 24 years to identify correlates of general intelligence (g) scores. To determine if these correlates also mediate associations of specific cognitive abilities with cortical thickness, we regressed specific cognitive test scores on g scores and analyzed the residuals with respect to cortical thickness. The effect of age on the association between cortical thickness and intelligence was examined. We found a widely distributed pattern of positive associations between cortical thickness and g scores, as derived from the first unrotated principal factor of a factor analysis of Wechsler Abbreviated Scale of Intelligence (WASI) subtest scores. After WASI specific cognitive subtest scores were regressed on g factor scores, the residual score variances did not correlate significantly with cortical thickness in the full sample with age covaried. When participants were grouped at the age median, significant positive associations of cortical thickness were obtained in the older group for g-residualized scores on Block Design (a measure of visual-motor integrative processing) while significant negative associations of cortical thickness were observed in the younger group for g-residualized Vocabulary scores. These results regarding correlates of general intelligence are concordant with the existing literature, while the findings from younger versus older subgroups have implications for future research on brain structural correlates of specific cognitive abilities, as well as the cognitive domain specificity of behavioral performance correlates of normative gray matter thinning during adolescence.     

Gray matter and intelligence factors: Is there a neuro-g?

Heterogeneous results among neuro-imaging studies using psychometric intelligence measures may result from the variety of tests used. The g-factor may provide a common metric across studies. Here we derived a g-factor from a battery of eight cognitive tests completed by 6929 young adults, 40 of whom also completed structural MRI scans. Regional gray matter (GM) was determined using voxel-based-morphometry (VBM) and correlated to g-scores. Results showed correlations distributed throughout the brain, but there was limited overlap with brain areas identified in a similar study that used a different battery of tests to derive g-scores. Comparable spatial scores (with g variance removed) also were derived from both batteries, and there was considerable overlap in brain areas where GM was correlated to the respective spatial scores. The results indicate that g-scores derived from different test batteries do not necessarily have equivalent neuro-anatomical substrates, suggesting that identifying a “neuro-g” will be difficult. The neuro-anatomical substrate of a spatial factor, however, appears more consistent and implicates a distributed network of brain areas that may be involved with spatial ability. Future imaging studies directed at identifying the neural basis of intelligence may benefit from using a psychometric test battery chosen with specific criteria.     

Erratum to “Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds”

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6–18, n = 216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.     

Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6–18, n = 216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.     

Sex differences in brain volume are related to specific skills, not to general intelligence

It has been proposed that males would show higher mean scores than females in general intelligence (g) because (1) men have, on average, larger brains than women, and (2) brain volume correlates with g. Here we report a failure to support the conclusion derived from these premises. High resolution MRIs were acquired in a sample of one hundred healthy young participants for estimating total, gray, and white matter volumes. Participants also completed an intelligence battery - comprising tests measuring abstract, verbal, and spatial abilities - that allowed the extraction of g scores. Results showed consistent relations between sex differences in brain volumes and non-g spatial and verbal skills but not for g.     

Finding the g-factor in brain structure using the method of correlated vectors

It is unclear whether brain mechanisms underlying human intelligence are distributed throughout the brain or mainly concentrated in the frontal lobes. Data are inconsistent possibly due, at least in part, to the different ways the construct of intelligence is measured. Here we apply the method of correlated vectors to determine how the general factor of intelligence (g) is related to regional gray matter and white matter volumes. This is a re-analysis of an earlier study showing regional gray matter and white matter volume is correlated to Full Scale IQ (FSIQ). However, it is well-known that FSIQ taps several cognitive abilities and skills in addition to g. The results now show that the g factor accounts for several but not all FSIQ/gray matter correlations distributed throughout the brain and these areas may differ for young and older adults.     

On the interpretation of the CHC factor Gc

On the one hand, the factors Gf and Gc in the Cattell-Horn-Carroll (CHC) model of intelligence are hypothesized to represent individual differences in unique psychological or biological capacities. On the other hand, they are interpreted as representing the theoretical variables fluid and crystallized intelligence in investment theory. With respect to Gc, this leads to a theoretical conflict because in investment theory crystallized intelligence is not a capacity but purely a statistical entity. We contend that if CHC factor Gc represents a capacity, it cannot represent crystallized intelligence, and if Gc represents crystallized intelligence, it does not represent a capacity. In addition, from our discussion of Gc, we conclude that in investment theory the factors Gf and g represent one and the same capacity. In support of our theoretical conclusions, we implemented the CHC model in a confirmatory factor analysis of a HCA (Human Cognitive Abilities project) data set. As expected, Gf and g were statistically indistinguishable. Gc was effectively absent, because it was statistically equivalent to verbal comprehension. Factors Gc and g could be removed from the model without any reduction in model fit. We argue that in the CHC taxonomy the factors Gc and g are redundant as explanatory variables.     

The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence

"Is there a biology of intelligence which is characteristic of the normal human nervous system?" Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.     

Memory span and general intelligence: A latent-variable approach

There are several studies showing that working memory and intelligence are strongly related. However, working memory tasks require simultaneous processing and storage, so the causes of their relationship with intelligence are currently a matter of discussion. The present study examined the simultaneous relationships among short-term memory (STM), working memory (WM), and general intelligence (g). Two hundred and eight participants performed six verbal, quantitative, and spatial STM tasks, six verbal, quantitative, and spatial WM tasks, and eight tests measuring fluid, crystallized, spatial, and quantitative intelligence. Especial care is taken to avoid misrepresenting the relations among the constructs being studied because of specific task variance. Structural equation modelling (SEM) results revealed that (a) WM and g are (almost) isomorphic constructs, (b) the isomorphism vanishes when the storage component of WM is partialed out, and (c) STM and WM (with its storage component partialed out) predict g.     

Hippocampal structure and human cognition: Key role of spatial processing and evidence supporting the efficiency hypothesis in females

Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05), significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences.     

The Neural Architecture of General Knowledge

Cognitive performance varies widely between individuals and is highly influenced by structural and functional properties of the brain. In the past, neuroscientific research was principally concerned with fluid intelligence, while neglecting its equally important counterpart crystallized intelligence. Crystallized intelligence is defined as the depth and breadth of knowledge and skills that are valued by one's culture. The accumulation of crystallized intelligence is guided by information storage capacities and is likely to be reflected in an individual's level of general knowledge. In spite of the significant role general knowledge plays for everyday life, its neural foundation largely remains unknown. In a large sample of 324 healthy individuals, we used standard magnetic resonance imaging along with functional magnetic resonance imaging and diffusion tensor imaging to examine different estimates of brain volume and brain network connectivity and assessed their predictive power with regard to both general knowledge and fluid intelligence. Our results demonstrate that an individual's level of general knowledge is associated with structural brain network connectivity beyond any confounding effects exerted by age or sex. Moreover, we found fluid intelligence to be best predicted by cortex volume in male subjects and functional network connectivity in female subjects. Combined, these findings potentially indicate different neural architectures for information storage and information processing. © 2019 European Association of Personality Psychology     

Is g an entity? A Japanese twin study using syllogisms and intelligence tests

Using a behavioral genetic approach, we examined the validity of the hypothesis concerning the singularity of human general intelligence, the g theory, by analyzing data from two tests: the first consisted of 100 syllogism problems and the second a full-scale intelligence test. The participants were 448 Japanese young adult twins (167 pairs of identical and 53 pairs of fraternal twins). Data were analyzed for their fit to two kinds of multivariate genetic models: a common pathway model, in which a higher-order latent variable, g, was postulated as an entity; and an independent pathway model, in which the higher-order latent variable was not posited. These analyses revealed that the common pathway model which included additive genetic and nonshared environmental factors best accounted for the three distinct mental abilities: syllogistic logical deductive reasoning, verbal, and spatial. Both the substantial g-loading for syllogism-solving, historically recognized as the symbol of human intelligence, and the emergence of g as an entity at an etiological level, that is, at the genetic and environmental factor level, provide further support for the g theory.     

The three-stratum theory of cognitive abilities: Test of the structure of intelligence across the life span

Recently a three-stratum theory of intelligence that combines the major aspects of Spearman's (1927) theory of general intelligence (g) and Horn and Cattell's (1966) theory of crystallized and fluid intelligence (G_f-G_c) has been proposed (Carroll, 1993a). The purpose of this study was to test the three-stratum theory using hierarchical confirmatory factor analysis with the LISREL computer program. Developmental changes in the structure of intelligence were also investigated. Results provided support for the three-stratum theory and suggested the possibility of intermediate factors between the second and third strata but did not support developmental changes in the organization of cognitive abilities over the life span.     

Event-related-potential (ERP) correlates of cognitive styles,abilities and aptitudes

Fifty, right-handed males were given 11 psychometric tests of cognitive styles, abilities and aptitudes. Visual (VERP), auditory (AERP) and bimodal (BERP) brain event-related-potential (ERP) amplitudes were recorded from each of these Ss. Canonical and product-moment correlations were computed. These analyses established that VERPs and BERPs elicited in the frontal, temporal, parietal and occipital regions were related to abilities and aptitudes: general aptitude, reading and verbal comprehension and spatial ability; and a cognitive style: field dependence-independence. The results demonstrated the construct validity of ERPs as indicators of individual differences in cognitive characteristics, especially crystallized and fluid intelligence.     

A unifying model for the structure of intellectual abilities

Models of the structure of cognitive abilities suggested by Spearman, Thurstone, Guilford, Vernon and Cattell-Horn are reviewed. It is noted that some of the models include a general intellectual factor (g) while others do not. It is also noted that some models are nonhierarchical, while in others more narrow abilities are subsumed under broader abilities in a hierarchical pattern. An empirical study in which a test battery of 16 tests was administered to some 1000 subjects in the 6th grade is reported. Using the LISREL technique to test different models, good support is obtained for oblique primary factors in the Thurstone tradition as well as for the second-order factors fluid intelligence, crystallized intelligence, and general visualization hypothesized by Cattell and Horn. It is also found, however, that the second-order factor of fluid intelligence i is identical with a third-order g-factor. On the basis of these results a three-level model (the HILI-model) is suggested, with the g-factor at the top, two broad factors reflecting the ability to deal with verbal and figural information, respectively, at the second-order level, and the primary factors in the Thurstone and Guilford tradition at the lowest level. It is argued that most previously suggested models are special cases of the HILI-model.     

The Relationship Between Diverse Components of Intelligence and Creativity

Intelligence and creativity are accounted for in terms of two different mental operations referred to as ‘convergent thinking’ and ‘divergent thinking’, respectively. Nevertheless, psychometric evidence on the relationship between intelligence and creativity has been controversial. To clarify their relationship, we characterized the relationship between diverse components of intelligence and creativity through the administration of psychometric tests on a large sample (WAIS, RPM, and TTCT‐figural: n = 215; TTCT‐verbal: n = 137). The general intelligence factor (g) score showed significant correlations with both TTCT‐figural and TTCT‐verbal scores. However, sub‐dimensional analysis demonstrated that their association was attributable to the specific components of both TTCTs (TTCT‐figural: Abstractness of Titles, Elaboration, and Resistance to Premature Closure; TTCT‐verbal: Flexibility) rather than to their common components (Fluency and Originality). Among the intelligence sub‐dimensions, crystallized intelligence (gC) played a pivotal role in the association between g and the specific components of both TTCTs. When the total sample was divided into two IQ groups, these phenomena were more evident in the average IQ group than in the high IQ group. These results suggest that the mental operation of creativity may be different from that of intelligence, but gC may be used as a resource for the mental operation of creativity.     

Comparing subtest profiles of g loadings and correlations with RT measures

It is argued that if a response time (RT) measure correlates with psychometric test (PT) scores because it shares variance in common with general intelligence, g, then the profile of g loadings for a set of PTs would be predictable from the profile of correlations between the RT measure and the PT scores. On the other hand, if an RT correlates with PTs through variance not shared with g, the g loadings of the PTs should be unrelated to the correlations between RT and PTs. The profiles of g loadings and correlations with RT were compared for a set of 6 RT measures and 8 PT scores from Smith and Stanley (1983). To demonstrate statistical significance, standard errors of the statistics were generated by Efron's bootstrap technique (Efron, 1979). It was clearly shown that the profile of the PT's g loadings could be well predicted from the RT-PT correlations for four of the RT measures. It can be concluded that RT tasks do measure general intelligence. Analysis of the errors in prediction suggested that the RTs may correlate more with fluid than crystallized intelligence.     

A smarter brain is associated with stronger neural interaction in healthy young females: A resting EEG coherence study

General intelligence, the g factor, is a major issue in psychology and neuroscience. However, the neural mechanism of the g factor is still not clear. It is suggested that the g factor should be non-modular (a property across the brain) and show good colinearity with various cognitive tests. This study examines the hypothesis that functional connectivity may be a good candidate for the g factor. We recorded resting state eyes-closed EEG signals in 184 healthy young females. Coherence values of 38 selected channel pairs across delta, theta, alpha, beta and gamma frequencies were correlated with six intelligence quotient (IQ) subtests, including symbol search, block design, object assembly, digit span, similarity and arithmetic. A three-stage analytic flow was constructed to delineate common (g factor) and unique neural components of intelligence. It is noticed that the coherence pattern demonstrates good correlation with five of the IQ subtests (except symbol search) and non-modularity in the brain. Our commonality analyses support connectivity strength in the brain as a good indicator of the g factor. For the digit span and arithmetic tests, the uniqueness analyses provide left-lateralized topography relevant to the operation of working memory. Performance on the arithmetic test is further correlated with strengths at left temporo-parietal and bilateral temporal connections. All the significant correlations are positive, indicating that the stronger the connectivity strengths, the higher the intelligence. Our analyses conclude that a smarter brain is associated with stronger interaction in the central nervous system. The implication and why the symbol search does not show parallel results are discussed.     

Relations between mental performance and reaction time: New aspects of an old problem

The relation between simple and complex reaction time and psychometrically determined mental performance was reexamined with 486 subjects of above-average intelligence. Various standardized tests measuring aspects of cognitive ability, memory and ability to concentrate were used. Simple and complex reaction times were measured using the Klebelsberg modification of the Mierke apparatus. Correlations between complex reaction time and mental performance as observed by other investigators were mostly confirmed. We found, however, the strongest and most consistent correlations with tests measuring short-term memory; ability to concentrate and spatial ability. On the other hand, tests known and shown again in this paper to load highly on Spearman's general factor g, such as verbal abilities; combinatoric thinking; abstraction; or calculation gave only trivial, and, in most cases, nonsignificant correlations with complex reaction time. We even observed a negative (though, for our data, not significant) correlation between g-loadings of subtests and their correlations with complex reaction time for the only complete standardized intelligence test used in this study, the “Intelligenz-Strukturtest (Amthauer).” Therefore, this study does not support the hypothesis that fast processing of complex information as measured by complex reaction time is the decisive component of the general factor of intelligence g.     

Adolescent intelligence and socio-economic wealth independently predict adult marital and reproductive behavior

Counter-intuitively, sociobiological and evolutionary theories predict a negative relationship between g and reproduction when applied to modern humans. Although existing research has documented this dysgenic trend, the association between g and socio-economic factors presents a confound that has not systematically been addressed in prior research. Based on a sample of 325,252 individuals drawn from the nationally representative Project Talent database, we examined the unique effects of g and socio-economic wealth, assessed in adolescence, on marital and reproductive behavior over the next 11 years. Results show that both g and socio-economic wealth have unique, independent negative effects on marital and reproductive behavior such that individuals of higher intelligence and higher wealth delay marriage and reproductive longer than those of lower intelligence and wealth. The effect of g was slightly stronger than that of wealth, though for both variables much of their influence was mediated by educational attainment. Consistent with sociobiological theory, these dysgenic effects were stronger among females than males.