General cognitive ability and fluctuating asymmetry of brain surface area

Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study

Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or 'g')? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate. There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9-59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1-88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.

Hemispheric asymmetries in cortical grey matter of gyri and sulci in modern human populations from South America

Structural asymmetries of brain regions associated with lateralised functions have been extensively studied. However, there are fewer morphometric analyses of asymmetries of the gyri and sulci of the entire cortex. The current study assessed cortical asymmetries in a sample of healthy adults (N = 175) from an admixed population from South America. Grey matter volume and surface area of 66 gyri and sulci were quantified on T1 magnetic resonance images. The departure from zero of the differences between left and right hemispheres (L-R), a measure of directional asymmetry (DA), the variance of L-R, and an index of fluctuating asymmetry (FA) were evaluated for each region. Significant departures from perfect symmetry were found for most cortical gyri and sulci. Regions showed leftward asymmetry at the population level in the frontal lobe and superior lateral parts of the parietal lobe. Rightward asymmetry was found in the inferior parietal, occipital, frontopolar, and orbital regions, and the cingulate (anterior, middle, and posterior-ventral). Despite this general pattern, several sulci showed the opposite DA compared to the neighbouring gyri, which remarks the need to consider the neurobiological differences in gyral and sulcal development in the study of structural asymmetries. The results also confirm the absence of DA in most parts of the inferior frontal gyrus and the precentral region. This study contributes with data on populations underrepresented in the databases used in neurosciences. Among its findings, there is agreement with previous results obtained in populations of different ancestry and some discrepancies in the middle frontal and medial parietal regions. A significant DA not reported previously was found for the volume of long and short insular gyri and the central sulcus of the insula, frontomarginal, transverse frontopolar, paracentral, and middle and posterior parts of the cingulate gyrus and sulcus, gyrus rectus, occipital pole, and olfactory sulcus, as well as for the volume and area of the transverse collateral sulcus and suborbital sulcus. Also, several parcels displayed significant variability in the left-right differences, which can be partially attributable to developmental instability, a source of FA. Moreover, a few gyri and sulci displayed ideal FA with non-significant departures from perfect symmetry, such as subcentral and posterior cingulate gyri and sulci, inferior frontal and fusiform gyri, and the calcarine, transverse collateral, precentral, and orbital sulci. Overall, these results show that asymmetries are ubiquitous in the cerebral cortex.

Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex

Cortical asymmetry is a ubiquitous feature of brain organization that is subtly altered in some neurodevelopmental disorders, yet we lack knowledge of how its development proceeds across life in health. Achieving consensus on the precise cortical asymmetries in humans is necessary to uncover the developmental timing of asymmetry and the extent to which it arises through genetic and later influences in childhood. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in seven datasets and chart asymmetry trajectories longitudinally across life (4-89 years; observations = 3937; 70% longitudinal). We find replicable asymmetry interrelationships, heritability maps, and test asymmetry associations in large-scale data. Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in childhood and peaks in early adulthood. Areal asymmetry is low-moderately heritable (max h2SNP ~19%) and correlates phenotypically and genetically in specific regions, indicating coordinated development of asymmetries partly through genes. In contrast, thickness asymmetry is globally interrelated across the cortex in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in population-level right-asymmetric regions (and vice versa), and exhibits low or absent heritability. We find less areal asymmetry in the most consistently lateralized region in humans associates with subtly lower cognitive ability, and confirm small handedness and sex effects. Results suggest areal asymmetry is developmentally stable and arises early in life through genetic but mainly subject-specific stochastic effects, whereas childhood developmental growth shapes thickness asymmetry and may lead to directional variability of global thickness lateralization in the population.

Structural architecture and brain network efficiency link polygenic scores to intelligence

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

Developmental instability, fluctuating asymmetry, and human psychological science

Developmental instability (DI) is an individual's inability to produce a specific developmental outcome under a given set of conditions, generally thought to result from random perturbations experienced during development. Fluctuating asymmetry (FA) - asymmetry on bilateral features that, on average, are symmetrical (or asymmetry deviating from that arising from design) - has been used to measure DI. Dating to half a century ago, and accelerating in the past three decades, psychological researchers have examined associations between FA (typically measured on bodily or facial features) and a host of outcomes of interest, including psychological disorders, cognitive ability, attractiveness, and sexual behavior. A decade ago, a meta-analysis on findings from nearly 100 studies extracted several conclusions. On average, small but statistically reliable associations between FA and traits of interest exist. Though modest, these associations are expected to greatly underestimate the strength of associations with underlying DI. Despite the massive sample size across studies, we still lack a good handle on which traits are most strongly affected by DI. A major methodological implication of the meta-analysis is that most studies have been, individually, woefully underpowered to detect associations. Though offering some intriguing findings, much research is the past decade too has been underpowered; hence, the newer literature is also likely noisy. Several large-scale studies are exceptions. Future progress depends on additional large-scale studies and researchers' sensitivity to power issues. As well, theoretical assumptions and conceptualizations of DI and FA driving psychological research may need revision to explain empirical patterns.

The individuality of shape asymmetries of the human cerebral cortex

Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales (~37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales (~65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.

Associations between Cortical Asymmetry and Domain Specific Cognitive Functions in Healthy Children

Cortical asymmetry and functional lateralization form intriguing and fundamental features of human brain organization, and is complicated by individual differences and evolvement with age. While many studies have investigated neuroanatomical differences between hemispheres as well as functional lateralization of the brain for different age groups, few have looked into the associations between cortical asymmetry and development of cognitive functions in children. In this study, we aimed to identify relationships between hemispheric asymmetry in brain cortex measured by MRI and cognitive development in healthy young children evaluated by a comprehensive battery of neuropsychological tests. Structural MRI data were obtained from 71 children in the age range of 7.5 to 8.5 years. Structural lateralization index (SLI), a reflection of the brain asymmetry, was computed for each of the 3 cortical morphometry measurements: cortical thickness, surface area and gray matter volume. A total of 34 bilateral regions were studied for the whole brain cortex as defined by the Desikan atlas. Region-wise SLI was correlated with domain specific cognitive scores using partial correlation analysis controlled for the potential confounding effects of age and sex. Significant correlations were identified between test scores of multiple cognitive domains and SLI of several cortical regions. Specifically, SLI of total surface area of precuneus and insula significantly correlated with measures of executive function behavior; significant relationships were also found between SLI of mean cortical thickness of superior parietal cortex and memory and language tests scores; in addition, SLI of parahippocampal gyrus also showed significant correlations with language test scores for all 3 morphometry features. These findings revealed regional hemispheric asymmetries that may be linked to specific cognitive abilities in children.Clinical relevance- This study shows associations between structural lateralization in different brain cortical regions and variations in specific cognitive functions in healthy children.

Computer Programming E-Learners' Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating Factors

Educational systems around the world encourage students to engage in programming activities, but programming learning is one of the most challenging learning tasks. Thus, it was significant to explore the factors related to programming learning. This study aimed to identify computer programming e-learners’ personality traits, self-reported cognitive abilities and learning motivating factors in comparison with other e-learners. We applied a learning motivating factors questionnaire, the Big Five Inventory—2, and the SRMCA instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners, the mean age was 25.19 years. It was found that computer programming e-learners demonstrated significantly lower scores of extraversion, and significantly lower scores of motivating factors of individual attitude and expectation, reward and recognition, and punishment. No significant differences were found in the scores of self-reported cognitive abilities between the groups. In the group of computer programming e-learners, extraversion was a significant predictor of individual attitude and expectation; conscientiousness and extraversion were significant predictors of challenging goals; extraversion and agreeableness were significant predictors of clear direction; open-mindedness was a significant predictor of a diminished motivating factor of punishment; negative emotionality was a significant predictor of social pressure and competition; comprehension-knowledge was a significant predictor of individual attitude and expectation; fluid reasoning and comprehension-knowledge were significant predictors of challenging goals; comprehension-knowledge was a significant predictor of clear direction; and visual processing was a significant predictor of social pressure and competition. The SEM analysis demonstrated that personality traits (namely, extraversion, conscientiousness, and reverted negative emotionality) statistically significantly predict learning motivating factors (namely, individual attitude and expectation, and clear direction), but the impact of self-reported cognitive abilities in the model was negligible in both groups of participants and non-participants of e-learning based computer programming courses; χ² (34) = 51.992, p = 0.025; CFI = 0.982; TLI = 0.970; NFI = 0.950; RMSEA = 0.051 [0.019–0.078]; SRMR = 0.038. However, as this study applied self-reported measures, we strongly suggest applying neurocognitive methods in future research.

Fluctuating asymmetry in brain structure and general intelligence in 73-year-olds

Fluctuating body asymmetry is theorized to indicate developmental instability, and to have small positive associations with low socioeconomic status (SES). Previous studies have reported small negative associations between fluctuating body asymmetry and cognitive functioning, but relationships between fluctuating brain asymmetry and cognitive functioning remain unclear. The present study investigated the association between general intelligence (a latent factor derived from a factor analysis on 13 cognitive tests) and the fluctuating asymmetry of four structural measures of brain hemispheric asymmetry: cortical surface area, cortical volume, cortical thickness, and white matter fractional anisotropy. The sample comprised members of the Lothian Birth Cohort 1936 (LBC1936, N = 636, mean age = 72.9 years). Two methods were used to calculate structural hemispheric asymmetry: in the first method, regions contributed equally to the overall asymmetry score; in the second method, regions contributed proportionally to their size. When regions contributed equally, cortical thickness asymmetry was negatively associated with general intelligence (β = −0.18,p < .001). There was no association between cortical thickness asymmetry and childhood SES, suggesting that other mechanisms are involved in the thickness asymmetry-intelligence association. Across all cortical metrics, asymmetry of regions identified by the parieto-frontal integration theory (P-FIT) was not more strongly associated with general intelligence than non-P-FIT asymmetry. When regions contributed proportionally, there were no associations between general intelligence and any of the asymmetry measures. The implications of these findings, and of different methods of calculating structural hemispheric asymmetry, are discussed.

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Previous work has shown links between cortical asymmetry and intelligence.

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In the current study, two methods of calculating global cortical hemispheric asymmetry were compared.

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Equal region contribution: the association between cortical thickness asymmetry and general intelligence was β = −0.18.

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Proportional region contribution: no associations between three measures of cortical asymmetry and general intelligence.