Finding the g-factor in brain structure using the method of correlated vectors

"Non-Eloquent" brain regions predict neuropsychological outcome in tumor patients undergoing awake craniotomy

Supratotal resection of primary brain tumors is being advocated especially when involving "non-eloquent" tissue. However, there is extensive neuropsychological data implicating functions critical to higher cognition in areas considered "non-eloquent" by most surgeons. The goal of the study was to determine pre-surgical brain regions that would be predictive of cognitive outcome at 4-6 months post-surgery. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer-v6.0 image analysis suite. Linear regression models were used to regress cortical volumes from both hemispheres, against the total cognitive z-score to determine the relationship between brain structure and broad cognitive functioning while controlling for age, sex, and total segmented brain volume. We identified 62 consecutive patients who underwent planned awake resections of primary (n = 55, 88%) and metastatic at the University of New Mexico Hospital between 2015 and 2019. Of those, 42 (23 males, 25 left hemispheric lesions) had complete pre and post-op neuropsychological data available and were included in this study. Overall, total neuropsychological functioning was somewhat worse (p = 0.09) at post-operative neuropsychological outcome (Mean = -.20) than at baseline (Mean = .00). Patients with radiation following resection (n = 32) performed marginally worse (p = .036). We found that several discrete brain volumes obtained pre-surgery predicted neuropsychological outcome post-resection. For the total sample, these volumes included: left fusiform, right lateral orbital frontal, right post central, and right paracentral regions. Regardless of lesion lateralization, volumes within the right frontal lobe, and specifically right orbitofrontal cortex, predicted neuropsychological difference scores. The current study highlights the gaps in our current understanding of brain eloquence. We hypothesize that the volume of tissue within the right lateral orbital frontal lobe represents important cognitive reserve capacity in patients undergoing tumor surgery. Our data also cautions the neurosurgeon when considering supratotal resections of tumors that do not extend into areas considered "non-eloquent" by current standards.

Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study

Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.

The use of neuropsychological tests to assess intelligence

OBJECTIVE

We sought to derive a 'neuropsychological intelligence quotient' (NIQ) to replace IQ testing in some routine assessments.

METHOD

We administered neuropsychological testing and a seven-subtest short form of the Wechsler Adult Intelligence Scale to a community sample of 394 adults aged 18-96 years. We regressed Wechsler Full Scale IQs (W-FSIQ) on 23 neuropsychological scores and derived an NIQ from 9 measures that explained significant variance in W-FSIQ. We then compared subgroups of 284 healthy and 108 unhealthy participants in NIQ and W-FSIQ to assess criterion validity, correlated NIQ and W-FSIQ scores with education level and independence for activities of daily living to assess convergent validity, and compared validity coefficients for the NIQ with those of 'hold' and 'no-hold' indices.

RESULTS

By design, NIQ and W-FSIQ scores correlated highly (r = .84), and both were higher in healthy participants. The difference was larger for NIQ, which accounted for more variability in activities of daily living. The NIQ and 'no-hold' index were better predicted by health status and less predicted by educational status than the 'hold' index.

CONCLUSIONS

We constructed an NIQ that correlates highly with Wechsler FSIQ. Tests required to obtain NIQ are commonly used and can be administered in about 45 min. Validity properties of NIQ and W-FSIQ are similar. The NIQ bore greater resemblance to a 'no-hold' than 'hold' index. One can obtain a reasonably accurate estimate of current Full Scale IQ without formal intelligence testing from a brief neuropsychological battery.

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions.

Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools

Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up tor= 0.95) and much less by teachers’ skill (up tor= 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed.

Regional gray matter density is associated with achievement motivation: evidence from voxel-based morphometry

Achievement motivation can be defined as a recurrent need to improve one's past performance. Despite previous functional imaging studies on motivation-related functional activation, the relationship between regional gray matter (rGM) morphology and achievement motivation has never been investigated. We used voxel-based morphometry and a questionnaire (achievement motivation scale) to measure individual achievement motivation and investigated the association between rGM density (rGMD) and achievement motivation [self-fulfillment achievement motivation (SFAM) and competitive achievement motivation (CAM) across the brain in healthy young adults (age 21.0 ± 1.8 years, men (n = 94), women (n = 91)]. SFAM and rGMD significantly and negatively correlated in the orbitofrontal cortex (OFC). CAM and rGMD significantly and positively correlated in the right putamen, insula, and precuneus. These results suggest that the brain areas that play central roles in externally modulated motivation (OFC and putamen) also contribute to SFAM and CAM, respectively, but in different ways. Furthermore, the brain areas in which rGMD correlated with CAM are related to cognitive processes associated with distressing emotions and social cognition, and these cognitive processes may characterize CAM.

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

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

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.

Gray matter correlates of cognitive ability tests used for vocational guidance

Background

Individual differences in cognitive abilities provide information that is valuable for vocational guidance, but there is an ongoing debate about the role of ability factors, including general intelligence (g), compared to individual tests. Neuroimaging can help identify brain parameters that may account for individual differences in both factors and tests. Here we investigate how eight tests used in vocational guidance correlate to regional gray matter. We compare brain networks identified by using scores for ability factors (general and specific) to those identified by using individual tests to determine whether these relatively broad and narrow approaches yield similar results.

Findings

Using MRI and voxel-based morphometry (VBM), we correlated gray matter with independent ability factors (general intelligence, speed of reasoning, numerical, spatial, memory) and individual test scores from a battery of cognitive tests completed by 40 individuals seeking vocational guidance. Patterns of gray matter correlations differed between group ability factors and individual tests. Moreover, tests within the same factor showed qualitatively different brain correlates to some degree.

Conclusions

The psychometric factor structure of cognitive tests can help identify brain networks related to cognitive abilities beyond a general intelligence factor (g). Correlates of individual ability tests with gray matter, however, appear to have some differences from the correlates for group factors.

Sexual Dimorphism in the Parietal Substrate Associated with Visuospatial Cognition Independent of General Intelligence

Sex differences in visuospatial cognition (VSC) with male advantage are frequently reported in the literature. There is evidence for sexual dimorphisms in the human brain, one of which postulates more gray matter (GM) in females and more white matter (WM) in males relative to total intracranial volume. We investigated the neuroanatomy of VSC independent of general intelligence (g) in sex-separated populations, homogenous in age, education, memory performance, a memory- and brain morphology-related gene, and g. VSC and g were assessed with the Wechsler adult intelligence scale. The influence of g on VSC was removed using a hierarchical factor analysis and the Schmid–Leiman solution. Structural high-resolution magnetic resonance images were acquired and analyzed with voxel-based morphometry. As hypothesized, the clusters of positive correlations between local volumes and VSC performance independent of g were found mainly in parietal areas, but also in pre- and postcentral regions, predominantly in the WM in males, whereas in females these correlations were located in parietal and superior temporal areas, predominantly in the GM. Our results suggest that VSC depends more strongly on parietal WM structures in males and on parietal GM structures in females. This sex difference might have to do with the increased axonal and decreased somatodendritic tissue in males relative to females. Whether such sex-specific implementations of the VSC network can be explained genetically as suggested in investigations into the Turner syndrome or as a result of structural neural plasticity upon different experience and usage remains to be shown.

Whole brain size and general mental ability: a review

We review the literature on the relation between whole brain size and general mental ability (GMA) both within and between species. Among humans, in 28 samples using brain imaging techniques, the mean brain size/GMA correlation is 0.40 (N = 1,389; p < 10⁻¹⁰); in 59 samples using external head size measures it is 0.20 (N = 63,405; p < 10⁻¹⁰). In 6 samples using the method of correlated vectors to distill g, the general factor of mental ability, the mean r is 0.63. We also describe the brain size/GMA correlations with age, socioeconomic position, sex, and ancestral population groups, which also provide information about brain–behavior relationships. Finally, we examine brain size and mental ability from an evolutionary and behavior genetic perspective.

Lesion mapping of cognitive abilities linked to intelligence

The Wechsler Adult Intelligence Scale (WAIS) assesses a wide range of cognitive abilities and impairments. Factor analyses have documented four underlying indices that jointly comprise intelligence as assessed with the WAIS: verbal comprehension (VCI), perceptual organization (POI), working memory (WMI), and processing speed (PSI). We used nonparametric voxel-based lesion-symptom mapping in 241 patients with focal brain damage to investigate their neural underpinnings. Statistically significant lesion-deficit relationships were found in left inferior frontal cortex for VCI, in left frontal and parietal cortex for WMI, and in right parietal cortex for POI. There was no reliable single localization for PSI. Statistical power maps and cross-validation analyses quantified specificity and sensitivity of the index scores in predicting lesion locations. Our findings provide comprehensive lesion maps of intelligence factors, and make specific recommendations for interpretation and application of the WAIS to the study of intelligence in health and disease.

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

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

The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence

"Is there a biology of intelligence which is characteristic of the normal human nervous system?" Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.

Intelligence? What intelligence?

Neuroimaging evidence, both within and between research strategies, is largely heterogeneous. This results from the way the construct of interest (i.e., intelligence) is measured. Every single available measure comprises several cognitive abilities, although the so-called g factor is always present. Here I suggest that studies must always control for this empirical fact to arrive at solid conclusions.