Neuroanatomical Correlates of Intelligence

Adaptation, expertise, and giftedness: towards an understanding of cortical, subcortical, and cerebellar network contributions

Current cortico-centric models of cognition lack a cohesive neuroanatomic framework that sufficiently considers overlapping levels of function, from "pathological" through "normal" to "gifted" or exceptional ability. While most cognitive theories presume an evolutionary context, few actively consider the process of adaptation, including concepts of neurodevelopment. Further, the frequent co-occurrence of "gifted" and "pathological" function is difficult to explain from a cortico-centric point of view. This comprehensive review paper proposes a framework that includes the brain's vertical organization and considers "giftedness" from an evolutionary and neurodevelopmental vantage point. We begin by discussing the current cortico-centric model of cognition and its relationship to intelligence. We then review an integrated, dual-tiered model of cognition that better explains the process of adaptation by simultaneously allowing for both stimulus-based processing and higher-order cognitive control. We consider the role of the basal ganglia within this model, particularly in relation to reward circuitry and instrumental learning. We review the important role of white matter tracts in relation to speed of adaptation and development of behavioral mastery. We examine the cerebellum's critical role in behavioral refinement and in cognitive and behavioral automation, particularly in relation to expertise and giftedness. We conclude this integrated model of brain function by considering the savant syndrome, which we believe is best understood within the context of a dual-tiered model of cognition that allows for automaticity in adaptation as well as higher-order executive control.

Neuroanatomical correlates of intellectual ability across the life span

Attempts to correlate measures of intellectual ability with localized anatomical imaging features of the brain have yielded variable findings distributed across frontal, parietal, and temporal lobes. To better define the gray and white matter correlates of intellectual ability and the effects of sex and age, we analyzed the brains of 105 healthy individuals, ages 7-57 years, who had a Full Scale Intelligence Quotient (FSIQ) of 70 or higher. We examined associations of FSIQ with cortical thickness and with white matter volume throughout the cerebrum. Thinning of left ventromedial and right dorsolateral prefrontal cortices correlated significantly with FSIQ. Sex modified correlations of cortical thickness with FSIQ in the left inferior frontal, left cingulate, and right dorsomedial prefrontal cortices. Correlations of local white matter volumes with FSIQ varied by age, with adults showing inverse correlations of white matter volume with FSIQ in a large territory of right frontal white matter likely corresponding to fiber tracts of the superior corona radiata and superior longitudinal fasciculus. These findings corroborate the role of frontal and parietal association cortices and long association white matter fibers in higher intelligence and suggest ways in which the neuroanatomical correlates of higher intelligence may vary by sex and age.

Total brain white matter is a major determinant of IQ in adolescents born preterm

OBJECTIVE

In preterm infants, white matter (WM) abnormalities detected on magnetic resonance imaging (MRI) at term-age are associated with early developmental delay. We set out to study this association in adolescents born pre-term, by examining intellectual outcome in relation to markers of brain injury, focusing on the effects of WM reduction.

METHODS

Seventy-nine participants were recruited and assessed at a mean age of 16 years: 49 adolescents born preterm (<32 weeks' gestation) with a wide spectrum of brain injuries (including 22 with no identifiable brain injury at birth) and 30 term-born controls. Data collected included: brain MRI scans, full-scale intelligence quotient (IQ) scores, educational attainments, and behavioral scores. Measures of WM reduction included total volume, cross-sectional area of the corpus callosum (CC), and ventricular dilatation. Cerebellar volumes and neuroradiological ratings were also included.

RESULTS

WM volume and IQ were reduced in the preterm groups (both with and without brain injury). Total WM volume and CC area jointly explained 70% of IQ variance in the adolescents born preterm, irrespective of the presence or severity of brain abnormalities detected at birth or on follow-up MRI. This relationship was not seen in controls. Importantly, correlations were also found with real-world measures of academic achievement and behavioral difficulties.

INTERPRETATION

Preterm birth has a long-term effect on cognition, behavior, and future academic success primarily as a consequence of global brain WM reduction. This emphasizes the need for early therapeutic efforts to prevent WM injury and promote or optimize its development in preterm neonates.

Human intelligence and brain networks

Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

The link between callosal thickness and intelligence in healthy children and adolescents

The link between brain structure and intelligence is a well-investigated topic, but existing analyses have mainly focused on adult samples. Studies in healthy children and adolescents are rare, and normative data specifically addressing the association between corpus callosum morphology and intellectual abilities are quite limited. To advance this field of research, we mapped the correlations between standardized intelligence measures and callosal thickness based on high-resolution magnetic resonance imaging (MRI) data. Our large and well-matched sample included 200 normally developing subjects (100 males, 100 females) ranging from 6 to 17 years of age. Although the strongest correlations were negative and confined to the splenium, the strength and the direction of intelligence-callosal thickness associations varied considerably. While significant correlations in females were mainly positive, significant correlations in males were exclusively negative. However, only the negative correlations in the overall sample (i.e., males and females combined) remained significant when controlling for multiple comparisons. The observed negative correlations between callosal thickness and intelligence in children and adolescents contrast with the positive correlations typically reported in adult samples. However, negative correlations are in line with reports from other pediatric studies relating cognitive measures to other brain attributes such as cortical thickness, gray matter volume, and gray matter density. Altogether, these findings suggest that relationships between callosal morphology and cognition are highly dynamic during brain maturation. Sex effects on links between callosal thickness and intelligence during childhood and adolescence are present but appear rather weak in general.

Genetic influences on brain asymmetry: a DTI study of 374 twins and siblings

Brain asymmetry, or the structural and functional specialization of each brain hemisphere, has fascinated neuroscientists for over a century. Even so, genetic and environmental factors that influence brain asymmetry are largely unknown. Diffusion tensor imaging (DTI) now allows asymmetry to be studied at a microscopic scale by examining differences in fiber characteristics across hemispheres rather than differences in structure shapes and volumes. Here we analyzed 4Tesla DTI scans from 374 healthy adults, including 60 monozygotic twin pairs, 45 same-sex dizygotic pairs, and 164 mixed-sex DZ twins and their siblings; mean age: 24.4years+/-1.9 SD). All DTI scans were nonlinearly aligned to a geometrically-symmetric, population-based image template. We computed voxel-wise maps of significant asymmetries (left/right differences) for common diffusion measures that reflect fiber integrity (fractional and geodesic anisotropy; FA, GA and mean diffusivity, MD). In quantitative genetic models computed from all same-sex twin pairs (N=210 subjects), genetic factors accounted for 33% of the variance in asymmetry for the inferior fronto-occipital fasciculus, 37% for the anterior thalamic radiation, and 20% for the forceps major and uncinate fasciculus (all L>R). Shared environmental factors accounted for around 15% of the variance in asymmetry for the cortico-spinal tract (R>L) and about 10% for the forceps minor (L>R). Sex differences in asymmetry (men>women) were significant, and were greatest in regions with prominent FA asymmetries. These maps identify heritable DTI-derived features, and may empower genome-wide searches for genetic polymorphisms that influence brain asymmetry.

Obesity is linked with lower brain volume in 700 AD and MCI patients

Obesity is associated with lower brain volumes in cognitively normal elderly subjects, but no study has yet investigated the effects of obesity on brain structure in patients with mild cognitive impairment (MCI) or Alzheimer's disease (AD). To determine if higher body mass index (BMI) is associated with brain volume deficits in cognitively impaired elderly subjects, we analyzed brain magnetic resonance imaging (MRI) scans of 700 MCI or AD patients from 2 different cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Cardiovascular Health Study-Cognition Study (CHS-CS). Tensor-based morphometry (TBM) was used to create 3-dimensional maps of regional tissue excess or deficits in subjects with MCI (ADNI, n = 399; CHS-CS, n = 77) and AD (ADNI, n = 188; CHS, n = 36). In both AD and MCI groups, higher body mass index was associated with brain volume deficits in frontal, temporal, parietal, and occipital lobes; the atrophic pattern was consistent in both ADNI and CHS populations. Cardiovascular risk factors, especially obesity, should be considered as influencing brain structure in those already afflicted by cognitive impairment and dementia.

Human face recognition ability is specific and highly heritable

Compared with notable successes in the genetics of basic sensory transduction, progress on the genetics of higher level perception and cognition has been limited. We propose that investigating specific cognitive abilities with well-defined neural substrates, such as face recognition, may yield additional insights. In a twin study of face recognition, we found that the correlation of scores between monozygotic twins (0.70) was more than double the dizygotic twin correlation (0.29), evidence for a high genetic contribution to face recognition ability. Low correlations between face recognition scores and visual and verbal recognition scores indicate that both face recognition ability itself and its genetic basis are largely attributable to face-specific mechanisms. The present results therefore identify an unusual phenomenon: a highly specific cognitive ability that is highly heritable. Our results establish a clear genetic basis for face recognition, opening this intensively studied and socially advantageous cognitive trait to genetic investigation.

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.

Human intelligence and brain networks

Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

Genetics of brain fiber architecture and intellectual performance

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal (a(2)=0.55, p=0.04, left; a(2)=0.74, p=0.006, right), bilateral parietal (a(2)=0.85, p<0.001, left; a(2)=0.84, p<0.001, right), and left occipital (a(2)=0.76, p=0.003) lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata (p=0.04 for FIQ and p=0.01 for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.