Approximate number sense (ANS), the ability to rapidly and accurately compare quantities presented non-symbolically, has been proposed as a precursor to mathematics skills. Earlier work reported low heritability of approximate number sense, which was interpreted as evidence that approximate number sense acts as a fitness trait. However, viewing ANS as a fitness trait is discordant with findings suggesting that individual differences in approximate number sense acuity correlate with mathematical performance, a trait with moderate genetic effects. Importantly, the shared etiology of approximate number sense, mathematics, and general cognitive ability has remained unexamined. Thus, the etiology of approximate number sense and its overlap with math and general cognitive ability was assessed in the current study with two independent twin samples (N = 451 pairs). Results suggested that ANS acuity had moderate but significant additive genetic influences. ANS also had overlap with generalist genetic mechanisms accounting for variance and covariance in mathematics and general cognitive ability. Furthermore, ANS may have genetic factors unique to covariance with mathematics beyond overlap with general cognitive ability. Evidence across both samples was consistent with the proposal that the etiology of approximate number sense functions similar to that of mathematics and general cognitive skills.

Reaction time (RT) has played a prominent part in research on mental ability for over a century. Throughout this time a number of questions have been repeatedly posed: what is the relationship of RT to general mental ability, and is this the same for simple and choice RT? Does the relationship change with age? How important is RT variability compared with mean values? Here we examine these questions in three population representative cohorts.

To extend previous literature that suggests higher IQ in youth is associated with living longer. Previous studies have been unable to assess reliably whether the effect differs across sexes and ages of death, and whether the effect is graded across different levels of IQ.

Maintaining good cognitive function is important for successful aging, and it has been suggested recently that having and optimistic outlook may also be valuable. However few have studied the relationship between cognitive ability and dispositional optimism and pessimism in older age. It is unclear whether associations found previously between cognitive ability and pessimism in older age, are evident across the life course, and are consistent at different points in older age. In the present study we examined associations between dispositional optimism and pessimism measured in the eighth and ninth decade of life and childhood and older age cognitive ability, and lifetime change in cognitive ability. Participants were two independent narrow-age samples of older individuals with mean ages about 73 ( = 847) and 87 ( = 220) years from the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921), respectively. Higher cognitive ability in childhood and older-age, and healthier cognitive change across the lifetime were associated with lower pessimism in older age: age-11 IQ (LBC1936: β = - 0.17,  < 0.001; LBC1921: β = - 0.29,  = 0.001), older-age IQ (LBC1936: β = - 0.18,  < 0.001; LBC1921: β = - 0.27,  < 0.001), cognitive change (LBC1936: β = - 0.06,  < 0.04; LBC1921: β = - 0.15,  = 0.05). Cognitive ability was not significantly associated with optimism in bivariate analyses, and after adjustment for covariates had only small associations with optimism and only in the LBC1936. The results are consistent with differential associations between cognitive functions and optimism and pessimism, and indicate that their associations with cognitive ability are similar in the eighth and ninth decades of life.

Intelligence is an important individual difference factor related to mental health, academic achievement, and life success, yet there is a lack of research into its early cognitive predictors. This study investigated the predictive value of infant developmental assessment scores for school-age intelligence in a large, heterogeneous sample of single- and twin-born subjects (N = 521). We found that Early Learning Composite (ELC) scores from the Mullen Scales of Early Learning have similar predictive power to that of other infant tests. ELC scores at age 2 were predictive of Stanford-Binet abbreviated intelligence (ABIQ) scores at age 6 ( = 0.46) even after controlling for sex, gestation number, and parental education. ELC scores at age 1 were less predictive of 6-year ABIQ scores ( = 0.17). When the sample was split to test robustness of findings, we found that results from the full sample replicated in a subset of children born at ≥32 weeks gestation without birth complications (n = 405), though infant cognitive scores did not predict IQ in a subset born very prematurely or with birth complications (n = 116). Scores at age 2 in twins and singletons showed similar predictive ability for scores at age 6, though twins had particularly high correlations between ELC at age 1 and ABIQ at age 6.

Age moderation of genetic and environmental contributions to Digits Forward, Digits Backward, Block Design, Symbol Digit, Vocabulary, and Synonyms was investigated in a sample of 14,534 twins aged 26 to 98 years. The Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium contributed the sample, which represents nine studies from three countries (USA, Denmark, and Sweden). Average test performance was lower in successively older age groups for all tests. Significant age moderation of additive genetic, shared environmental, and non-shared environmental variance components was observed, but the pattern varied by test. The genetic contribution to phenotypic variance across age was smaller for both Digit Span tests, greater for Synonyms, and stable for Block Design and Symbol Digit. The non-shared environmental contribution was greater with age for the Digit Span tests and Block Design, while the shared environmental component was small for all tests, often more so with age. Vocabulary showed similar age-moderation patterns as Synonyms, but these effects were nonsignificant. Findings are discussed in the context of theories of cognitive aging.

The current study evaluated sex differences in (1) self-perceptions of everyday and academic spatial ability, and (2) metacognitive monitoring accuracy for measures of spatial visualization and spatial orientation. Undergraduate students completed the Paper Folding Test, Spatial Relations Test, and the Revised Purdue Spatial Visualization Test while making confidence judgments (CJs) for each trial. They also made global estimates of performance and rated their ability to perform several everyday and academic spatial scenarios. Across multiple spatial measures, female students displayed lower confidence in their item-level monitoring and global assessments of performance than did male students, even when no actual differences in spatial performance occurred. Women were also less confident in their self-assessments of their visualspatial ability for scientific domains than were men. However, the absolute and relative accuracy of CJs did not differ as a function of sex suggesting that women can monitor their spatial performance as well as men.

While adoption studies have provided key insights into the influence of the familial environment on IQ scores of adolescents and children, few have followed adopted offspring long past the time spent living in the family home. To improve confidence about the extent to which shared environment exerts enduring effects on IQ, we estimated genetic and environmental effects on adulthood IQ in a unique sample of 486 biological and adoptive families. These families, tested previously on measures of IQ when offspring averaged age 15, were assessed a second time nearly two decades later ( offspring age = 32 years). We estimated the proportions of the variance in IQ attributable to environmentally mediated effects of parental IQs, sibling-specific shared environment, and gene-environment covariance to be .01 [95% CI .00, .02], .04 [95% CI .00, .15], and .03 [95% CI .00, .07] respectively; these components jointly accounted for 8 percent of the IQ variance in adulthood. The heritability was estimated to be .42 [95% CI .21, .64]. Together, these findings provide further evidence for the predominance of genetic influences on adult intelligence over any other systematic source of variation.

[This corrects the article DOI: 10.1016/j.intell.2014.05.006.].

We investigated the association between intelligence in youth and a range of health-related behaviours in middle age.

It is well documented that memory is heritable and that older adults tend to have poorer memory performance than younger adults. However, whether the magnitudes of genetic and environmental contributions to late-life verbal episodic memory ability differ from those at earlier ages remains unresolved. Twins from 12 studies participating in the Interplay of Genes and Environment in Multiple Studies (IGEMS) consortium constituted the analytic sample. Verbal episodic memory was assessed with immediate word list recall ( = 35,204 individuals; 21,792 twin pairs) and prose recall ( = 3,805 individuals; 2,028 twin pairs), with scores harmonized across studies. Average test performance was lower in successively older age groups for both measures. Twin models found significant age moderation for both measures, with total inter-individual variance increasing significantly with age, although it was not possible definitively to attribute the increase specifically to either genetic or environmental sources. Pooled results across all 12 studies were compared to results where we successively dropped each study (leave-one-out) to assure results were not due to an outlier. We conclude the models indicated an overall increase in variance for verbal episodic memory that was driven by a combination of increases in the genetic and nonshared environmental parameters that were not independently statistically significant. In contrast to reported results for other cognitive domains, differences in environmental exposures are comparatively important for verbal episodic memory, especially word list learning.

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,  = 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 ( = -0.18, < .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.

The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small and heterogeneous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall  = 29,004, with  = 18,426 participants providing both brain MRI and at least one cognitive test, and a complete four-test battery with MRI data available in a minimum  = 7201, depending upon the MRI measure. Participants' age range was 44-81 years (M = 63.13, SD = 7.48). A general factor of intelligence () was derived from four varied cognitive tests, accounting for one third of the variance in the cognitive test scores. The association between (age- and sex- corrected) total brain volume and a latent factor of general intelligence is  = 0.276, 95% C.I. = [0.252, 0.300]. A model that incorporated multiple global measures of grey and white matter macro- and microstructure accounted for more than double the variance in older participants compared to those in middle-age (13.6% and 5. 4%, respectively). There were no sex differences in the magnitude of associations between and total brain volume or other global aspects of brain structure. The largest brain regional correlates of were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices, thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor. Many of these regions exhibited unique contributions to intelligence, and showed highly stable out of sample prediction.

This study documents differences in childhood IQ trajectories of Guatemala City children, aged 6-15 years and born 1961-1993, according to school attended, height-for-age -scores (HAZ) and over time (Flynn effect). IQ data come from the Universidad del Valle de Guatemala Longitudinal Study of Child and Adolescent Development. IQ was measured using standardised tests from the Otis-Lennon Mental Ability Test-series. A multilevel model was developed to describe 60,986 IQ observations (level 1), in 22,724 children (level 2), in five schools representing students of different socioeconomic status (SES) (level 3). Average IQ trajectories differed by school. The difference in average IQ at age 11 years between the students of high and low SES schools was 28.7 points. A one-unit increase in HAZ was associated with a 1.42 (0.72, 2.11) unit higher IQ if HAZ was <0, this association was stronger in public compared to private schools. Conversely, one unit increase in HAZ was only associated with a 0.3 (0.001, 0.5) unit higher IQ if HAZ was ≥0. With each birth year increase, IQ at age 11 years increased by 0.14 (95% CI 0.12, 0.16) units, although this Flynn effect attenuated slightly across adolescence. We found no evidence of secular change in the inequality in IQ trajectories (according to school or HAZ). Shorter children from disadvantaged schools in Guatemala City have lower IQ than their taller and wealthier peers, possibly reflecting the damaging effects of poor early life environments both for linear growth and cognitive development.

Generational changes in IQ (the Flynn Effect) have been extensively researched and debated. Within the US, gains of 3 points per decade have been accepted as consistent across age and ability level, suggesting that tests with outdated norms yield spuriously high IQs. However, findings are generally based on small samples, have not been validated across ability levels, and conflict with reverse effects recently identified in Scandinavia and other countries. Using a well-validated measure of fluid intelligence, we investigated the Flynn Effect by comparing scores normed in 1989 and 2003, among a representative sample of American adolescents ages 13-18 (n=10,073). Additionally, we examined Flynn Effect variation by age, sex, ability level, parental age, and SES. Adjusted mean IQ differences per decade were calculated using generalized linear models. Overall the Flynn Effect was not significant; however, effects varied substantially by age and ability level. IQs increased 2.3 points at age 13 (95% CI=2.0, 2.7), but decreased 1.6 points at age 18 (95% CI=-2.1, -1.2). IQs decreased 4.9 points for those with IQ<70 (95% CI=-4.9, -4.8), but increased 3.5 points among those with IQ>130 (95% CI=3.4, 3.6). The Flynn Effect was not meaningfully related to other background variables. Using the largest sample of US adolescent IQs to date, we demonstrate significant heterogeneity in fluid IQ changes over time. Reverse Flynn Effects at age 18 are consistent with previous data, and those with lower ability levels are exhibiting worsening IQ over time. Findings by age and ability level challenge generalizing IQ trends throughout the general population.

There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance (), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies ( < 100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project ( = 1,022) and found a highly significant correlation (disattenuated = 0.18, < .001). We replicated this result in the Minnesota Center for Twin and Family Research ( = 2,698), finding a highly significant within-family correlation between head circumference and intelligence (disattenuated = 0.19, < .001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies (GWAS) of head size ( ≈ 10,000) and measures of cognition (257,000 < < 767,000). Using bivariate LD Score regression, we found a genetic correlation between intracranial volume (ICV) and years of education () of 0.41 ( < .001). Using the Latent Causal Variable method, we found a genetic causality proportion of 0.72 ( < .001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with ICV also being associated with but many genetic variants associated with not being associated with ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural selection favoring general intelligence.

Although prior theory suggests that rumination contributes to cognitive impairments associated with depression, recent work suggests that rumination is associated with higher levels of intelligence. The present study examined the relations between two ruminative subtypes (brooding and reflective pondering) and multiple measures and types of intelligence (verbal and performance) after controlling for rumination's overlapping variance with depression. Participants were 751 individuals from the Colorado Longitudinal Twin Study who completed the Ruminative Response Scale; the Center for Epidemiological Studies-Depression Scale and a fully structured clinical interview as measures of depression; and verbal and performance intelligence tasks at age 16 and the Raven's Advanced Progressive Matrices at age 23. Reflective pondering was positively associated with all measures of intelligence, whereas brooding was not associated with intelligence. Our findings indicate that any negative associations between rumination and intelligence are attributable to shared variance with depression, and that examination of rumination as a multifaceted construct may provide new insights into the relations between rumination and cognition.

In two large-scale longitudinal datasets (combined  = 5761), we investigated ability-related political polarization in responses to the COVID-19 pandemic. We observed more polarization with greater ability in emotional responses, risk perceptions, and product-purchase intentions across five waves of data collection with a diverse, convenience sample from February 2020 through July 2020 (Study 1,  = 1267). Specifically, more liberal participants had more negative emotional responses and greater risk perceptions of COVID-19 than conservative participants. Compared to conservatives, liberal participants also interpreted quantitative information as indicating higher COVID-19 risk and sought COVID-related news more from liberal than conservative news media. Of key importance, we also compared verbal and numeric cognitive abilities for their independent capacity to predict greater polarization. Although measures of numeric ability, such as objective numeracy, are often used to index ability-related polarization, ideological differences were more pronounced among those higher in verbal ability specifically. Similar results emerged in secondary analysis of risk perceptions in a nationally representative longitudinal dataset (Study 2,  = 4494; emotions and purchase intentions were not included in this dataset). We further confirmed verbal-ability-related polarization findings on non-COVID policy attitudes (i.e., weapons bans and Medicare-for-all) measured cross-sectionally. The present Study 2 documented ability-related polarization emerging over time for the first time (rather than simply measuring polarization in existing beliefs). Both studies demonstrated verbal ability measures as the most robust predictors of ability-related polarization. Together, these results suggest that polarization may be a function of the amount and/or application of verbal knowledge rather than selective application of quantitative reasoning skills.

From the genetic side, giftedness in cognitive development is the result of contribution of many common genetic variants of small effect size, so called polygenicity (Spain et al., 2016). From the environmental side, educationalists have argued for the importance of the environment for sustaining early potential in children, showing that bright poor children are held back in their subsequent development (Feinstein, 2003a). Such correlational data need to be complemented by mechanistic models showing how gifted development results from the respective genetic and environmental influences. A neurocomputational model of cognitive development is presented, using artificial neural networks to simulate the development of a population of children. Variability was produced by many small differences in neurocomputational parameters each influenced by multiple artificial genes, instantiating a polygenic model, and by variations in the level of stimulation from the environment. The simulations captured several key empirical phenomena, including the non-linearity of developmental trajectories, asymmetries in the characteristics of the upper and lower tails of the population distribution, and the potential of poor environments to hold back bright children. At a computational level, 'gifted' networks tended to have higher capacity, higher plasticity, less noisy neural processing, a lower impact of regressive events, and a richer environment. However, individual instances presented heterogeneous contributions of these neurocomputational factors, suggesting giftedness has diverse causes.

Most research on individual differences in performance on tests of cognitive ability focuses on general cognitive ability (g), the highest level in the three-level Cattell-Horn-Carroll (CHC) hierarchical model of intelligence. About 50% of the variance of g is due to inherited DNA differences (heritability) which increases across development. Much less is known about the genetics of the middle level of the CHC model, which includes 16 broad factors such as fluid reasoning, processing speed, and quantitative knowledge. We provide a meta-analytic review of 747,567 monozygotic-dizygotic twin comparisons from 77 publications for these middle-level factors, which we refer to as specific cognitive abilities (SCA), even though these factors are not independent of g. Twin comparisons were available for 11 of the 16 CHC domains. The average heritability across all SCA is 56%, similar to that of g. However, there is substantial differential heritability across SCA and SCA do not show the developmental increase in heritability seen for g. We also investigated SCA independent of g (SCA.g). A surprising finding is that SCA.g remain substantially heritable (53% on average), even though 25% of the variance of SCA that covaries with g has been removed. Our review highlights the need for more research on SCA and especially on SCA.g. Despite limitations of SCA research, our review frames expectations for genomic research that will use polygenic scores to predict SCA and SCA.g. Genome-wide association studies of SCA.g are needed to create polygenic scores that can predict SCA profiles of cognitive abilities and disabilities independent of g.

The association of premorbid cognitive ability with all-cause mortality is now well established. However, since all-cause mortality is relatively uninformative about aetiology, evidence has been sought, and is beginning to accumulate, for associations with specific causes of mortality. Likewise, the underlying causal pathways may be illuminated by considering associations with different measures of cognitive ability. For example, critics of IQ type measures point to possible cultural or social biases and there is, consequently, a need for more culturally neutral measures such as reaction times. We examine the associations of cognitive ability with major causes of mortality, including: cardiovascular disease, cancer and respiratory disease and compare the results for a standard IQ test, the Alice Heim 4 (AH4), with those for simple and four-choice reaction times.

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years ( = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety of sociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors (e.g. approximately one third of the variance in general cognitive change). However, beyond physical fitness and possession of the e4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal-range heterogeneity in aging-related cognitive declines.

Slower and more variable performance in speeded reaction time tasks is a prominent cognitive signature among children with Attention Deficit Hyperactivity Disorder (ADHD), and is often also negatively associated with executive functioning ability. In the current study, we utilize a visual inspection time task and an ex-Gaussian decomposition of the reaction time data from the same task to better understand which of several cognitive subprocesses (i.e. perceptual encoding, decision-making, or fine-motor output) may be responsible for these important relationships. Consistent with previous research, children with ADHD ( = 190; 68 girls) had longer/slower SD and tau than non-ADHD peers ( = 76; 42 girls), but there were no group differences in inspection time, mu, or sigma. Smaller mu, greater sigma, longer tau, and slower inspection time together predicted worse performance on a latent executive function factor, but only tau partially mediated the relationship between ADHD symptomology and EF. These results suggest that the speed of information accumulation during the decision-making process may be an important mechanism that explains ADHD-related deficits in executive control.

Meta-analytic structural equation modeling was used to estimate the relative contributions of general cognitive ability or (defined by executive functions, short-term memory, and intelligence) and basic domain-specific mathematical abilities to performance in more complex mathematics domains. The domain-specific abilities included mathematics fluency (e.g., speed of retrieving basic facts), computational skills (i.e., accuracy at solving multi-step arithmetic, algebra, or geometry problems), and word problems (i.e., mathematics problems presented in narrative form). The core analysis included 448 independent samples and 431,344 participants and revealed that predicted performance in all three mathematics domains. Mathematics fluency contributed to the prediction of computational skills, and both mathematics fluency and computational skills predicted word problem performance, controlling . The relative contribution of was consistently larger than basic domain-specific abilities, although the latter may be underestimated. The patterns were similar across younger and older individuals, individuals with and without a disability (e.g., learning disability), concurrent and longitudinal assessments, and family socioeconomic status, and have implications for fostering mathematical development.

The Scarr-Rowe hypothesis predicts that the heritability of cognitive abilities is higher in more privileged socioeconomic conditions, meaning that genetic potential can be more fully expressed in environments characterized by high socioeconomic status (SES) compared to low SES. This gene × SES interaction, however, has been replicated mostly in the United States, but not in other Western nations like the United Kingdom. In the current study, we tested the interaction between childhood SES and the heritability of cognitive ability in 3,074 German twin pairs comprising three age cohorts at different developmental stages (mean ages of 11, 17, and 23 years). Higher SES was associated with significantly higher mean cognitive ability scores in the two younger cohorts, with reduced variances at higher SES levels. Results further support the Scarr-Rowe hypothesis in middle childhood, and to some degree in adolescence, but not in adulthood. This indicates that the role of family SES as a moderator of the heritability of cognitive ability changes as children grow older. Moreover, children's shared experiences appear to be explain more variance in cognitive ability at the lower end of the SES distribution in middle childhood and adolescence.

There is substantial evidence for the association between higher early life IQ and better cognition in late life. To advance knowledge on potential pathways, the present study tested whether Five-Factor Model personality traits in adulthood mediate the association between adolescent IQ and later-life cognition. Participants were from the Graduate sample of the Wisconsin Longitudinal Study on Aging (WLS; N= 3,585). IQ was assessed in 1957 (about age 17), personality was assessed in 2003-2005 (age = 64), and cognition was assessed in 2011 (age = 71). Controlling for demographic factors, higher IQ in adolescence was related to higher openness, lower neuroticism, lower extraversion, lower agreeableness and lower conscientiousness in adulthood. Higher openness partially mediated the association between higher IQ and better cognition. Additional analyses indicated that the pattern of associations between IQ, personality and cognition was similar when the polygenic score for cognition was included as an additional covariate. Although effect size were small, this study provides new evidence that openness in adulthood is on the pathway between early life IQ and later-life cognition.

The Trail Making Test Part B (TMT-B) is commonly used as a brief and simple neuropsychological assessment of executive dysfunction. The TMT-B is thought to rely on a number of distinct cognitive processes that predict individual differences in performance. The current study examined the unique and shared contributions of latent component variables in a large cohort of older people. Five hundred and eighty-seven healthy, community-dwelling older adults who were all born in 1936 were assessed on the TMT-B and multiple tasks tapping cognitive domains of visuospatial ability, processing speed, memory and reading ability. Firstly, a first-order measurement model examining independent contributions of the four cognitive domains was fitted; a significant relationship between TMT-B completion times and processing speed was found (β = -0.610, p < .001). Secondly, a bifactor model examined the unique influence of each cognitive ability when controlling for a general cognitive factor. Importantly, both a general cognitive factor (; β = -0.561, p < .001) and additional -independent variance from processing speed (β = -0.464, p < .001) contributed to successful TMT-B performance. These findings suggest that older adults' TMT-B performance is influenced by both general intelligence and processing speed, which may help understand poor performance on such tasks in clinical populations.

It remains unclear whether performance of non-human animals on cognitive test batteries can be explained by domain general cognitive processes, as is found in humans. The persistence of this dispute is likely to stem from a lack of clarity of the psychological or neural processes involved. One broadly accepted cognitive process, that may predict performance in a range of psychometric tasks, is associative learning. We therefore investigated intra-individual performances on tasks that incorporate processes of associative learning, by assessing the speed of acquisition and reversal learning in up to 187 pheasants () on four related binary colour discrimination tasks. We found a strong, positive significant bivariate relationship between an individual's acquisition and reversal learning performances on one cue set. Weak, positive significant bivariate relationships were also found between an individual's performance on pairs of reversal tasks and between the acquisition and reversal performances on different cue sets. A single factor, robust to parallel analysis, explained 36% of variation in performance across tasks. Inter-individual variation could not be explained by differential prior experience, age, sex or body condition. We propose that a single factor explanation, which we call '', summarises the covariance among scores obtained from these visual discrimination tasks, as they all assess capacities for associative learning. We argue that 'a' may represent an underlying cognitive ability exhibited by an individual, which manifests across a variety of tasks requiring associative processes.

Populations worldwide are aging. Cognitive decline is an important precursor of dementia, illness and death and, even within the normal range, is associated with poorer performance on everyday tasks. However, the impact of age on cognitive function does not always receive the attention it deserves.

Intelligence is correlated with a range of left-wing and liberal political beliefs. This may suggest intelligence directly alters our political views. Alternatively, the association may be confounded or mediated by socioeconomic and environmental factors. We studied the effect of intelligence within a sample of over 300 biological and adoptive families, using both measured IQ and polygenic scores for cognitive performance and educational attainment. We found both IQ and polygenic scores significantly predicted all six of our political scales. Polygenic scores predicted social liberalism and lower authoritarianism, within-families. Intelligence was able to significantly predict social liberalism and lower authoritarianism, within families, even after controlling for socioeconomic variables. Our findings may provide the strongest causal inference to date of intelligence directly affecting political beliefs.