Roberto Colom

An integrative architecture for general intelligence and executive function revealed by lesion mapping

Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control, the broader functional networks that support high-level cognition and give rise to general intelligence remain to be well characterized. Here, we investigated the neural substrates of the general factor of intelligence (g) and executive function in 182 patients with focal brain damage using voxel-based lesion-symptom mapping. The Wechsler Adult Intelligence Scale and Delis-Kaplan Executive Function System were used to derive measures of g and executive function, respectively. Impaired performance on these measures was associated with damage to a distributed network of left lateralized brain areas, including regions of frontal and parietal cortex and white matter association tracts, which bind these areas into a coordinated system. The observed findings support an integrative framework for understanding the architecture of general intelligence and executive function, supporting their reliance upon a shared fronto-parietal network for the integration and control of cognitive representations and making specific recommendations for the application of the Wechsler Adult Intelligence Scale and Delis-Kaplan Executive Function System to the study of high-level cognition in health and disease.

Distributed brain sites for the g-factor of intelligence

The general factor of intelligence (g) results from the empirical fact that almost all cognitive tests are positively correlated with one another. Individual tests can be classified according to the degree to which they involve g. Here, regional brain volumes associated with g are investigated by means of structural magnetic resonance imaging and voxel-based morphometry. First, individual differences in the amount of regional gray matter volumes across the entire brain were correlated with eight cognitive tests showing distinguishable g-involvement. Results show that increasing g-involvement of individual tests was associated with increased gray matter volume throughout the brain. Second, it is shown that two prototypical measures of verbal and non-verbal g (i.e., vocabulary and block design) correlate with the amount of regional gray matter across frontal, parietal, temporal, and occipital lobes, suggesting that the general factor of intelligence relates to areas distributed across the brain as opposed to the view that g derives exclusively from the frontal lobes.

Complex span tasks, simple span tasks, and cognitive abilities: A reanalysis of key studies

There is great interest in the relationships between memory span tasks and cognitive abilities. However, the causes underlying their correlation remain unknown. In the present article, five key data sets were reanalyzed according to two criteria: They must consider complex span tasks (so-called working memory [WM] tasks) and simple span tasks (so-called short-term memory [STM] tasks), and they must comprise cognitive ability measures. The obtained results offer several points of interest. First, memory span tasks should be conceived from a hierarchical perspective: They comprise both general and specific components. Second, the general component explains about four times the variance explained by the specific components. Third, STM and WM measures are closely related. Fourth, STM and WM measures share the same common variance with cognitive abilities. Finally, the strong relationship usually found between memory span tasks and cognitive abilities could be tentatively interpreted by the component shared by STM and WM—namely, the capacity for temporarily preserving a reliable memory representation of any given information.

Working memory and intelligence

Abstract The correlation perspective shows that working memory (WM) is strongly related to psychometric intelligence. Although there are numerous psychometric abilities, there is a powerful single source of variance, namely, g . g Is evidenced by the positive correlation between all psychometric cognitive abilities. The construct of WM distinguishes contents (verbal, numerical, spatial) and operations (storage and processing). However, some studies found a high correlation between several diverse WM tasks, which supports the construct validity of the concept of WM as one general cognitive resource. This study explores the structure of WM drawing on the methodology of intelligence structure research. Then, WM is related to intelligence. One hundred and eighty-seven participants took part in the study. WM was assessed through eight computerized tasks, while intelligence was assessed through the Raven Matrices or the PMA-R. The results show that WM can be considered as one general cognitive resource and that this resource is strongly related with intelligence ( r =+0.7). The statement that there is something underlying WM and intelligence is discussed.

General intelligence and memory span: Evidence for a common neuroanatomic framework

General intelligence (g) is highly correlated with working-memory capacity (WMC). It has been argued that these central psychological constructs should share common neural systems. The present study examines this hypothesis using structural magnetic resonance imaging to determine any overlap in brain areas where regional grey matter volumes are correlated to measures of general intelligence and to memory span. In normal volunteers (N = 48) the results (p < .05, corrected for multiple comparisons) indicate that a common anatomic framework for these constructs implicates mainly frontal grey matter regions belonging to Brodmann area (BA) 10 (right superior frontal gyrus and left middle frontal gyrus) and, to a lesser degree, the right inferior parietal lobule (BA 40). These findings support the nuclear role of a discrete parieto-frontal network.

Negligible sex differences in general intelligence

Abstract The general factor, g , can be extracted from a correlation matrix of a battery of mental ability tests. g is common to all mental abilities. A key question in the research on cognitive sex differences is whether, on average, females and males differ in g . This question is technically the most difficult to answer and has been the least investigated. Cognitive batteries were applied in the present study to independent samples totaling 10,475 adult subjects (4,256 females and 6,219 males). The scores were factor-analyzed by sex to obtain separate g factors. The congruence coefficients ( r c ) suggested a near identity of these factors. Then, three methods were used to know if the standardized sex differences ( ds ) are explained by g : (1) the method of correlated vectors; (2) the sex loading in g was computed including the point-biserial correlation between sex and each of the subtests in the full matrix of subtest intercorrelations for factor analysis; and (3) the correlation between sex and g factor scores. The results suggest a negligible sex difference in g . The present study includes the largest sample on which a sex difference in g has ever been tested. The findings are consistent with those using quite different test batteries and subject samples.

Cortical thickness correlates of specific cognitive performance accounted for by the general factor of intelligence in healthy children aged 6 to 18

Prevailing psychometric theories of intelligence posit that individual differences in cognitive performance are attributable to three main sources of variance: the general factor of intelligence (g), cognitive ability domains, and specific test requirements and idiosyncrasies. Cortical thickness has been previously associated with g. In the present study, we systematically analyzed associations between cortical thickness and cognitive performance with and without adjusting for the effects of g in a representative sample of children and adolescents (N=207, Mean age=11.8; SD=3.5; Range=6 to 18.3 years). Seven cognitive tests were included in a measurement model that identified three first-order factors (representing cognitive ability domains) and one second-order factor representing g. Residuals of the cognitive ability domain scores were computed to represent g-independent variance for the three domains and seven tests. Cognitive domain and individual test scores as well as residualized scores were regressed against cortical thickness, adjusting for age, gender and a proxy measure of brain volume. g and cognitive domain scores were positively correlated with cortical thickness in very similar areas across the brain. Adjusting for the effects of g eliminated associations of domain and test scores with cortical thickness. Within a psychometric framework, cortical thickness correlates of cognitive performance on complex tasks are well captured by g in this demographically representative sample.

Distributed Neural System for Emotional Intelligence Revealed by Lesion Mapping

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.

Testing the developmental theory of sex differences in intelligence on 12–18 year olds

Abstract The consensus view states that there are no sex differences in intelligence. However, Lynn (1994, 1999) has formulated a developmental theory of sex differences in intelligence that challenges that view. The theory states that boys and girls mature at different rates such that the growth of girls accelerates at the age of about 9 years and remains in advance of boys until 14–15 years. At 15–16 years the growth of girls decelerates relative to boys. As boys continue to grow from this age their height and their mean IQs increase relative to those of girls. This paper presents new evidence for the theory from the Spanish standardization sample of the fifth edition of the DAT. 1027 boys and 924 girls between 12 and 18 years were tested. The general trend shows that girls do better at the younger ages and their performance declines relative to boys among older age groups, which supports the developmental theory. The sex difference for the DAT as a whole for 18 year olds is a 4.3 IQ advantage for boys, very close to the advantage that can be predicted from their larger brain size (4.4 IQ points). The profile of sex differences in abilities among the Spanish sample is closely similar to that in the United States and Britain, which is testimony to the robustness of the difference in these different cultures.

Sex differences in fluid intelligence among high school graduates

There is contradictory empirical evidence concerning the problem of whether there is a sex difference in general intelligence. Some researchers claim that there is a sex difference, relying on the summation of the standardized sex differences in cognitive tests measuring verbal, spatial, and reasoning abilities. Other researchers state that there is not a sex difference in general intelligence; they propose that general intelligence should be conceptualized as g. g is not the result of the simple summation of tests scores, but a source of variance evidenced by the correlation among several diverse tests. We think it is possible to resolve this conflict. Fluid intelligence (Gf) is usually conceived as the core of intelligent behavior [Carroll, J. B. (1993). Human cognitive abilities. Cambridge: Cambridge University Press]. Therefore, if there is a sex difference in general intelligence, it could be systematically detected in measures of Gf. Three measures of Gf were used in the present study: the PMA Inductive Reasoning Test, the Advanced Progressive Matrices (APM), and the Culture-Fair Intelligence Test (Scale 3). A total of 4072 high school graduates was tested (1772 females and 2300 males). The results reveal that females outperform males in the PMA Reasoning test, that males outperform females in the Raven, and that there is no sex difference in the Culture-Fair Test. Therefore, given that there is no systematic difference favoring any sex in the measures of Gf, and that there is no sex difference in the best available measure of Gf (the Culture-Fair Test), it is concluded that the sex difference in fluid intelligence is non-existent.