The evolution of human intelligence and the coefficient of additive genetic variance in human brain size

Assisted migration is plausible for a boreal tree species under climate change: A quantitative and population genetics study of trembling aspen (Populus tremuloides Michx.) in western Canada

A novel method was tested for improving tree breeding strategies that integrate quantitative and population genetics based on range-wide reciprocal transplant experiments. Five reciprocal common garden tests of Populus tremuloides were investigated including 6450 trees across western Canada focusing on adaptation traits and growth. Both genetic parameters and home-site transplant models were evaluated. We found a genetic trade-off between growth and early spring leaf flush and late fall senescence. Coefficients of phenotypic variation (CVp) of cell lysis (CL), a measure of freezing injury, shrank from 0.28 to 0.10 during acclimation in the fall, and the CVp slope versus the freezing temperature was significantly different from zero (R 2 = 0.33, p = .02). There was more between-population genetic variation in fall phenology than in spring leaf phenology. We suggest that P. tremuloides demonstrated a discrepancy between the ecological optimum and the physiological optimum minimum winter temperature. The sub-optimal growing condition of P. tremuloides is potentially caused by the warmer ecological optimum than the physiological optimum. Assisted migration and breeding of fast growers to reforest cooler plantation sites can improve productivity. Transferring the study populations to less than 4°C of extreme minimum temperature appears safe for reforestation aligning with the historical recolonization direction of the species. This is equivalent to a 5-10° latitudinal northward movement. Fall frost hardiness is an effective criterion for family selection in the range tested in this study.

Of differing methods, disputed estimates and discordant interpretations: the meta-analytical multiverse of brain volume and IQ associations

Brain size and IQ are positively correlated. However, multiple meta-analyses have led to considerable differences in summary effect estimations, thus failing to provide a plausible effect estimate. Here we aim at resolving this issue by providing the largest meta-analysis and systematic review so far of the brain volume and IQ association (86 studies; 454 effect sizes from k = 194 independent samples; N = 26 000+) in three cognitive ability domains (full-scale, verbal, performance IQ). By means of competing meta-analytical approaches as well as combinatorial and specification curve analyses, we show that most reasonable estimates for the brain size and IQ link yield r-values in the mid-0.20s, with the most extreme specifications yielding rs of 0.10 and 0.37. Summary effects appeared to be somewhat inflated due to selective reporting, and cross-temporally decreasing effect sizes indicated a confounding decline effect, with three quarters of the summary effect estimations according to any reasonable specification not exceeding r = 0.26, thus contrasting effect sizes were observed in some prior related, but individual, meta-analytical specifications. Brain size and IQ associations yielded r = 0.24, with the strongest effects observed for more g-loaded tests and in healthy samples that generalize across participant sex and age bands.

The evolutionary genetics of personality

Genetic influences on personality differences are ubiquitous, but their nature is not well understood. A theoretical framework might help, and can be provided by evolutionary genetics. We assess three evolutionary genetic mechanisms that could explain genetic variance in personality differences: selective neutrality, mutation‐selection balance, and balancing selection. Based on evolutionary genetic theory and empirical results from behaviour genetics and personality psychology, we conclude that selective neutrality is largely irrelevant, that mutation‐selection balance seems best at explaining genetic variance in intelligence, and that balancing selection by environmental heterogeneity seems best at explaining genetic variance in personality traits. We propose a general model of heritable personality differences that conceptualises intelligence as fitness components and personality traits as individual reaction norms of genotypes across environments, with different fitness consequences in different environmental niches. We also discuss the place of mental health in the model. This evolutionary genetic framework highlights the role of gene‐environment interactions in the study of personality, yields new insight into the person‐situation‐debate and the structure of personality, and has practical implications for both quantitative and molecular genetic studies of personality. Copyright © 2007 John Wiley & Sons, Ltd.

Evolution, genes, and inter‐disciplinary personality research

Most commentaries welcomed an evolutionary genetic approach to personality, but several raised concerns about our integrative model. In response, we clarify the scientific status of evolutionary genetic theory and explain the plausibility and value of our evolutionary genetic model of personality, despite some shortcomings with the currently available theories and data. We also have a closer look at mate choice for personality traits, point to promising ways to assess evolutionarily relevant environmental factors and defend higher‐order personality domains and the g‐factor as the best units for evolutionary genetic analyses. Finally, we discuss which extensions of and alternatives to our model appear most fruitful, and end with a call for more inter‐disciplinary personality research grounded in evolutionary theory. Copyright © 2007 John Wiley & Sons, Ltd.

Absolute and relative estimates of genetic and environmental variance in brain structure volumes

Comparing estimates of the amount of genetic and environmental variance for different brain structures may elucidate differences in the genetic architecture or developmental constraints of individual brain structures. However, most studies compare estimates of relative genetic (heritability) and environmental variance in brain structure, which do not reflect differences in absolute variance between brain regions. Here we used a population sample of young adult twins and singleton siblings of twins (n = 791; M = 23 years, Queensland Twin IMaging study) to estimate the absolute genetic and environmental variance, standardised by the phenotypic mean, in the size of cortical, subcortical, and ventricular brain structures. Mean-standardised genetic variance differed widely across structures [23.5-fold range 0.52% (hippocampus) to 12.28% (lateral ventricles)], but the range of estimates within cortical, subcortical, or ventricular structures was more moderate (two to fivefold range). There was no association between mean-standardised and relative measures of genetic variance (i.e., heritability) in brain structure volumes. We found similar results in an independent sample (n = 1075, M = 29 years, Human Connectome Project). These findings open important new lines of enquiry: namely, understanding the bases of these variance patterns, and their implications regarding the genetic architecture, evolution, and development of the human brain.

Simulations of blood as a suspension predicts a depth dependent hematocrit in the circulation throughout the cerebral cortex

Recent advances in modeling oxygen supply to cortical brain tissue have begun to elucidate the functional mechanisms of neurovascular coupling. While the principal mechanisms of blood flow regulation after neuronal firing are generally known, mechanistic hemodynamic simulations cannot yet pinpoint the exact spatial and temporal coordination between the network of arteries, arterioles, capillaries and veins for the entire brain. Because of the potential significance of blood flow and oxygen supply simulations for illuminating spatiotemporal regulation inside the cortical microanatomy, there is a need to create mathematical models of the entire cerebral circulation with realistic anatomical detail. Our hypothesis is that an anatomically accurate reconstruction of the cerebrocirculatory architecture will inform about possible regulatory mechanisms of the neurovascular interface. In this article, we introduce large-scale networks of the murine cerebral circulation spanning the Circle of Willis, main cerebral arteries connected to the pial network down to the microcirculation in the capillary bed. Several multiscale models were generated from state-of-the-art neuroimaging data. Using a vascular network construction algorithm, the entire circulation of the middle cerebral artery was synthesized. Blood flow simulations indicate a consistent trend of higher hematocrit in deeper cortical layers, while surface layers with shorter vascular path lengths seem to carry comparatively lower red blood cell (RBC) concentrations. Moreover, the variability of RBC flux decreases with cortical depth. These results support the notion that plasma skimming serves a self-regulating function for maintaining uniform oxygen perfusion to neurons irrespective of their location in the blood supply hierarchy. Our computations also demonstrate the practicality of simulating blood flow for large portions of the mouse brain with existing computer resources. The efficient simulation of blood flow throughout the entire middle cerebral artery (MCA) territory is a promising milestone towards the final aim of predicting blood flow patterns for the entire brain.

The brain’s astonishing cognitive capacity depends on the coordination between neurons and the cerebral circulation, a system known as the neurovascular unit. The spatial and temporal coupling between these two networks is the object of intense research. However, the concise anatomical description of the cerebral circulation has so far been intractable. This paper introduces a methodology for the in silico creation of realistic models for the entire cerebral circulation. This innovation incorporates topological data from several neuroimaging modalities covering three lengths scales as input into a computer algorithm, which assembles anatomically accurate circulatory networks. When simulating blood flow as red blood cells suspended in plasma for experimental and synthetic cortical network models, we discovered that red blood cells tend to be more concentrated in deeper layers of the cortex compared to the surface. RBC fluxes are more homogenous in deeper layers. The phenomenon of depth dependent red blood cell supply supports the notion that the intricate architecture of the cortical microcirculation serves a self-regulating function to maintain uniform oxygen perfusion to neurons. We also demonstrate the practicality of predicting blood flow patterns for the entire brain with existing computer power.

Individual differences in developmental plasticity: A role for early androgens?

Developmental plasticity is a widespread property of living organisms, but different individuals in the same species can vary greatly in how susceptible they are to environmental influences. In humans, research has sought to link variation in plasticity to physiological traits such as stress reactivity, exposure to prenatal stress-related hormones such as cortisol, and specific genes involved in major neurobiological pathways. However, the determinants of individual differences in plasticity are still poorly understood. Here we present the novel hypothesis that, in both sexes, higher exposure to androgens during prenatal and early postnatal life should lead to increased plasticity in traits that display greater male variability (i.e., a majority of physical and behavioral traits). First, we review evidence of greater phenotypic variation and higher susceptibility to environmental factors in males; we then consider evolutionary models that explain greater male variability and plasticity as a result of sexual selection. These empirical and theoretical strands converge on the hypothesis that androgens may promote developmental plasticity, at least for traits that show greater male variability. We discuss a number of potential mechanisms that may mediate this effect (including upregulation of neural plasticity), and address the question of whether androgen-induced plasticity is likely to be adaptive or maladaptive. We conclude by offering suggestions for future studies in this area, and considering some research designs that could be used to empirically test our hypothesis.

Island Rule, quantitative genetics and brain-body size evolution in Homo floresiensis

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis, a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60-90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus, which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa.

The genetic basis of natural variation in mushroom body size in Drosophila melanogaster

Genetic variation in brain size may provide the basis for the evolution of the brain and complex behaviours. The genetic substrate and the selective pressures acting on brain size are poorly understood. Here we use the Drosophila Genetic Reference Panel to map polymorphic variants affecting natural variation in mushroom body morphology. We identify 139 genes and 39 transcription factors and confirm effects on development and adult plasticity. We show correlations between morphology and aggression, sleep and lifespan. We propose that natural variation in adult brain size is controlled by interaction of the environment with gene networks controlling development and plasticity.

Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean?

Positive associations between human intelligence and brain size have been suspected for more than 150 years. Nowadays, modern non-invasive measures of in vivo brain volume (Magnetic Resonance Imaging) make it possible to reliably assess associations with IQ. By means of a systematic review of published studies and unpublished results obtained by personal communications with researchers, we identified 88 studies examining effect sizes of 148 healthy and clinical mixed-sex samples (>8000 individuals). Our results showed significant positive associations of brain volume and IQ (r=.24, R(2)=.06) that generalize over age (children vs. adults), IQ domain (full-scale, performance, and verbal IQ), and sex. Application of a number of methods for detection of publication bias indicates that strong and positive correlation coefficients have been reported frequently in the literature whilst small and non-significant associations appear to have been often omitted from reports. We show that the strength of the positive association of brain volume and IQ has been overestimated in the literature, but remains robust even when accounting for different types of dissemination bias, although reported effects have been declining over time. While it is tempting to interpret this association in the context of human cognitive evolution and species differences in brain size and cognitive ability, we show that it is not warranted to interpret brain size as an isomorphic proxy of human intelligence differences.

Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution

The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h(2) = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks.

The more g-loaded, the more heritable, evolvable, and phenotypically variable: Homology with humans in chimpanzee cognitive abilities

Expanding on a recent study that identified a heritable general intelligence factor (g) among individual chimpanzees from a battery of cognitive tasks, we hypothesized that the cognitive abilities that are more g-loaded would be more heritable and would present more additive genetic variance, in addition to showing more phenotypic variability. This pattern was confirmed, and is comparable to that found in humans, indicating fundamental homology. Finally, tool use presented the highest heritability, the largest amount of additive genetic variance and of phenotypic variance, consistent with previous findings indicating that it is associated with high interspecies variance and evolutionary rates in comparative primate studies.

Exome sequencing to detect rare variants associated with general cognitive ability: a pilot study

Variation in human cognitive ability is of consequence to a large number of health and social outcomes and is substantially heritable. Genetic linkage, genome-wide association, and copy number variant studies have investigated the contribution of genetic variation to individual differences in normal cognitive ability, but little research has considered the role of rare genetic variants. Exome sequencing studies have already met with success in discovering novel trait-gene associations for other complex traits. Here, we use exome sequencing to investigate the effects of rare variants on general cognitive ability. Unrelated Scottish individuals were selected for high scores on a general component of intelligence (g). The frequency of rare genetic variants (in n = 146) was compared with those from Scottish controls (total n = 486) who scored in the lower to middle range of the g distribution or on a proxy measure of g. Biological pathway analysis highlighted enrichment of the mitochondrial inner membrane component and apical part of cell gene ontology terms. Global burden analysis showed a greater total number of rare variants carried by high g cases versus controls, which is inconsistent with a mutation load hypothesis whereby mutations negatively affect g. The general finding of greater non-synonymous (vs. synonymous) variant effects is in line with evolutionary hypotheses for g. Given that this first sequencing study of high g was small, promising results were found, suggesting that the study of rare variants in larger samples would be worthwhile.

A genetic study on sexual dimorphism of bodyweight in sheep

The aim of the present study was to investigate the genetic basis of sexual dimorphism of bodyweight in Zandi sheep. To do this, a pedigree including 1450 dams and 170 sires was used. Six bivariate animal models were applied for investigating direct and maternal effects for three age-specific bodyweights (bodyweight at birth, 3 and 6 months of age) in male and female Zandi lambs. The variance components were estimated via REML procedure. Males were, respectively, 6%, 7% and 9% heavier than females at birth, weaning and 6 months of age. Estimates of sexual dimorphism levels (expressed as M/F) were 1.11 at birth, 1.07 at weaning and 1.09 at 6 months of age, which indicated relatively low levels of sexual size dimorphism in the traits studied. Except for birthweight, for which estimates of additive genetic, residual and phenotypic variances as well as direct heritability and additive coefficient of variation were higher in females, for other traits studied, estimates were higher in males. However, regarding direct and maternal effects, none of the differences between the sexes was significant, indicating no need for sexual selection. Cross-sex genetic correlations were 0.862 at birth, 0.918 at weaning and 0.922 at 6 months of age, which highlighted birthweight as the most dimorphic trait. It was concluded that, owing to possible contribution of sexual chromosomes to variation of growth-related traits, bodyweight in male and female lambs may not be under the exactly same genetic control.

The total burden of rare, non-synonymous exome genetic variants is not associated with childhood or late-life cognitive ability

Human cognitive ability shows consistent, positive associations with fitness components across the life-course. Underlying genetic variation should therefore be depleted by selection, which is not observed. Genetic variation in general cognitive ability (intelligence) could be maintained by a mutation-selection balance, with rare variants contributing to its genetic architecture. This study examines the association between the total number of rare stop-gain/loss, splice and missense exonic variants and cognitive ability in childhood and old age in the same individuals. Exome array data were obtained in the Lothian Birth Cohorts of 1921 and 1936 (combined N = 1596). General cognitive ability was assessed at age 11 years and in late life (79 and 70 years, respectively) and was modelled against the total number of stop-gain/loss, splice, and missense exonic variants, with minor allele frequency less than or equal to 0.01, using linear regression adjusted for age and sex. In both cohorts and in both the childhood and late-life models, there were no significant associations between rare variant burden in the exome and cognitive ability that survived correction for multiple testing. Contrary to our a priori hypothesis, we observed no evidence for an association between the total number of rare exonic variants and either childhood cognitive ability or late-life cognitive ability.

The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level

Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father’s age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents’ trait levels measured with the same precision as offspring’s. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents’ intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (<1% of variance explained) on intelligence. We discuss future avenues for studies of paternal age effects and suggest that stronger research designs are needed to rule out confounding factors involving birth order and the Flynn effect.

Artificial selection on relative brain size reveals a positive genetic correlation between brain size and proactive personality in the guppy

Animal personalities range from individuals that are shy, cautious, and easily stressed (a “reactive” personality type) to individuals that are bold, innovative, and quick to learn novel tasks, but also prone to routine formation (a “proactive” personality type). Although personality differences should have important consequences for fitness, their underlying mechanisms remain poorly understood. Here, we investigated how genetic variation in brain size affects personality. We put selection lines of large- and small-brained guppies (Poecilia reticulata), with known differences in cognitive ability, through three standard personality assays. First, we found that large-brained animals were faster to habituate to, and more exploratory in, open field tests. Large-brained females were also bolder. Second, large-brained animals excreted less cortisol in a stressful situation (confinement). Third, large-brained animals were slower to feed from a novel food source, which we interpret as being caused by reduced behavioral flexibility rather than lack of innovation in the large-brained lines. Overall, the results point toward a more proactive personality type in large-brained animals. Thus, this study provides the first experimental evidence linking brain size and personality, an interaction that may affect important fitness-related aspects of ecology such as dispersal and niche exploration.

Estimated maximal and current brain volume predict cognitive ability in old age

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging.

The Cognitive Differentiation-Integration Effort Hypothesis: A Synthesis between the Fitness Indicator and Life History Models of Human Intelligence

This article presents a potential synthesis between the fitness indicator and life history models of human intelligence through consideration of the phenomena of ability differentiation and integration. The cognitive differentiation-integration effort hypothesis proposes that these effects result from a life history tradeoff between cognitive integration effort, a mating effort component associated with strengthening the positive manifold amongst abilities; and cognitive differentiation effort, a somatic effort component associated with the cultivation of specific abilities. This represents one of two largely independent sources of genetic variance in intelligence; the other is mediated by general fitness and mutation load and is associated with individual differences in levels of ‘genetic g‘. These two sources (along with a common source of environmental variance) combine to give rise to a variety of cognitive phenotypes characterized by different combinations of high or low levels of ‘genetic g‘ and cognitive specialism or generalism. Fundamental to this model is the assumption that measures of life history speed ( K) and g are essentially independent, which is demonstrated via meta-analysis of 10 studies reporting correlations between the variables (ρ = .023, ns, n = 2056). The implications of the model are discussed in an evolutionary, ecological, and developmental context. Seven key predictions are made in the discussion which if tested could provide definitive evidence for the hypothesis.

The neuroscience of human intelligence differences

Neuroscience is contributing to an understanding of the biological bases of human intelligence differences. This work is principally being conducted along two empirical fronts: genetics--quantitative and molecular--and brain imaging. Quantitative genetic studies have established that there are additive genetic contributions to different aspects of cognitive ability--especially general intelligence--and how they change through the lifespan. Molecular genetic studies have yet to identify reliably reproducible contributions from individual genes. Structural and functional brain-imaging studies have identified differences in brain pathways, especially parieto-frontal pathways, that contribute to intelligence differences. There is also evidence that brain efficiency correlates positively with intelligence.

White matter integrity in the splenium of the corpus callosum is related to successful cognitive aging and partly mediates the protective effect of an ancestral polymorphism in ADRB2

It has recently been reported that the evolutionarily ancestral alleles of two functional polymorphisms in the beta(2)-adrenergic receptor gene (ADRB2) were related to higher cognitive ability in the 70 year old participants of the Lothian Birth Cohort 1936 (LBC1936). One emerging important factor in cognitive aging is the integrity of white matter tracts in the brain. Here, we used diffusion tensor MRI-based tractography to assess the integrity of eight white matter tracts in a subsample of the LBC1936. Higher integrity of the splenium of the corpus callosum predicted better cognitive ability in old age, even after controlling for IQ at age 11. Also, the ancestral allele of one ADRB2 SNP was associated with both splenium integrity and better cognitive aging. While the effects of the SNP and splenium integrity on cognitive aging were largely independent, there was some evidence for a partial mediation effect of ADRB2 status via splenium integrity.

Dissing Oneself versus Dissing Rivals: Effects of Status, Personality, and Sex on the Short-Term and Long-Term Attractiveness of Self-Deprecating and Other-Deprecating Humor

This study explores the adaptive functions and design features of self-and other-deprecating humor. Sixty-four female and 32 male college students participated in a two-part study. In the first part, we examined the relationships among participant demographics, personality traits, and preferences for producing different types of humor. Men report using more other-deprecating humor than women do, and the use of other-deprecating humor decreases with age for both sexes. In the second part of the study, each participant listened to tape recordings of opposite-sex people who were described as having different levels of status, and who produced different types of humor; then participants rated each person's attractiveness as a potential short-term and long-term mate. Humor type and presenter status had no effects on short-term attractiveness, but self-deprecating humor by high-status presenters (but not low-status presenters) increased long-term attractiveness for both sexes. These results are discussed in the light of sexual selection theory and costly signaling theory.

SEXUAL SELECTION FOR MORAL VIRTUES

Moral evolution theories have emphasized kinship, reciprocity, group selection, and equilibrium selection. Yet, moral virtues are also sexually attractive. Darwin suggested that sexual attractiveness may explain many aspects of human morality. This paper updates his argument by integrating recent research on mate choice, person perception, individual differences, costly signaling, and virtue ethics. Many human virtues may have evolved in both sexes through mutual mate choice to advertise good genetic quality, parenting abilities, and/or partner traits. Such virtues may include kindness, fidelity, magnanimity, and heroism, as well as quasi-moral traits like conscientiousness, agreeableness, mental health, and intelligence. This theory leads to many testable predictions about the phenotypic features, genetic bases, and social-cognitive responses to human moral virtues.