Individual cognitive traits can be predicted from task-based dynamic functional connectivity with a deep convolutional-recurrent model.

There has been increased interest in understanding the neural substrates of intelligence and several human traits from neuroimaging data. Deep learning can be used to predict different cognitive measures, such as general and fluid intelligence, from different functional magnetic resonance imaging experiments providing information about the main brain areas involved in these predictions. Using neuroimaging and behavioral data from 874 subjects provided by the Human Connectome Project, we predicted various cognitive scores using dynamic functional connectivity derived from language and working memory functional magnetic resonance imaging task states, using a 360-region multimodal atlas. The deep model joins multiscale convolutional and long short-term memory layers and was trained under a 10-fold stratified cross-validation. We removed the confounding effects of gender, age, total brain volume, motion and the multiband reconstruction algorithm using multiple linear regression. We can explain 17.1% and 16% of general intelligence variance for working memory and language tasks, respectively. We showed that task-based dynamic functional connectivity has more predictive power than resting-state dynamic functional connectivity when compared to the literature and that removing confounders significantly reduces the prediction performance. No specific cortical network showed significant relevance in the prediction of general and fluid intelligence, suggesting a spatial homogeneous distribution of the intelligence construct in the brain.

Econeurobiology and brain development in children: key factors affecting development, behavioral outcomes, and school interventions.

The Econeurobiology of the brain describes the environment in which an individual's brain develops. This paper explores the complex neural mechanisms that support and evaluate enrichment at various stages of development, providing an overview of how they contribute to plasticity and enhancement of both achievement and health. It explores the deep benefits of enrichment and contrasts them with the negative effects of trauma and stress on brain development. In addition, the paper strongly emphasizes the integration of Gardner's intelligence types into the school curriculum environment. It emphasizes the importance of linking various intelligence traits to educational strategies to ensure a holistic approach to cognitive development. In the field of Econeurobiology, this work explains the central role of the environment in shaping the development of the brain. It examines brain connections and plasticity and reveals the impact of certain environmental factors on brain development in early and mid-childhood. In particular, the six key factors highlighted are an environment of support, nutrition, physical activity, music, sleep, and cognitive strategies, highlighting their potential to improve cognitive abilities, memory, learning, self-regulation, and social and emotional development. This paper also investigates the social determinants of health and education in the context of Econeurobiology. It emphasizes the transformative power of education in society, especially in vulnerable communities facing global challenges in accessing quality education.

Understanding the neural basis of natural intelligence.

Understanding the neural basis of natural intelligence necessitates a paradigm shift: from strict reductionism toward embracing complexity and diversity. New tools and theories enable us to tackle this challenge, providing unprecedented access to neural dynamics and behavior across time, contexts, and species. Principles for intelligent behavior and learning in the natural world are now, more than ever, within reach.

GABAergic inhibition in human hMT+ predicts visuo-spatial intelligence mediated through the frontal cortex.

The prevailing opinion emphasizes fronto-parietal network (FPN) is key in mediating general fluid intelligence (gF). Meanwhile, recent studies show that human MT complex (hMT+), located at the occipito-temporal border and involved in 3D perception processing, also plays a key role in gF. However, the underlying mechanism is not clear, yet. To investigate this issue, our study targets visuo-spatial intelligence, which is considered to have high loading on gF. We use ultra-high field magnetic resonance spectroscopy (MRS) to measure GABA/Glu concentrations in hMT+ combining resting-state fMRI functional connectivity (FC), behavioral examinations including hMT+ perception suppression test and gF subtest in visuo-spatial component. Our findings show that both GABA in hMT+ and frontal-hMT+ functional connectivity significantly correlate with the performance of visuo-spatial intelligence. Further, serial mediation model demonstrates that the effect of hMT+ GABA on visuo-spatial gF is fully mediated by the hMT+ frontal FC. Together our findings highlight the importance in integrating sensory and frontal cortices in mediating the visuo-spatial component of general fluid intelligence.

Stable individual differences from dynamic patterns of function: brain network flexibility predicts openness/intellect, intelligence, and psychoticism.

A growing understanding of the nature of brain function has led to increased interest in interpreting the properties of large-scale brain networks. Methodological advances in network neuroscience provide means to decompose these networks into smaller functional communities and measure how they reconfigure over time as an index of their dynamic and flexible properties. Recent evidence has identified associations between flexibility and a variety of traits pertaining to complex cognition including creativity and working memory. The present study used measures of dynamic resting-state functional connectivity in data from the Human Connectome Project (n = 994) to test associations with Openness/Intellect, general intelligence, and psychoticism, three traits that involve flexible cognition. Using a machine-learning cross-validation approach, we identified reliable associations of intelligence with cohesive flexibility of parcels in large communities across the cortex, of psychoticism with disjoint flexibility, and of Openness/Intellect with overall flexibility among parcels in smaller communities. These findings are reasonably consistent with previous theories of the neural correlates of these traits and help to expand on previous associations of behavior with dynamic functional connectivity, in the context of broad personality dimensions.

A Comparative Study of Intelligence Quotients of Almajirai Attending Quranic Schools and Pupils of Selected Primary Schools in Zaria, Northwest Nigeria.

BACKGROUND: Almajiri is a word that describes a child sent far away from his parents to study the Quran under the tutelage and care of a Muslim scholar, also known as a Mallam. In recent times, the capacity of the Mallam to cater for these children has declined, leading them to beg on the streets for sustenance. Cognitive capacity has rarely been studied amongst this population. This study was designed to compare the intelligence quotients of Almajirai attending Quranic Schools and that of pupils attending public primary school in Zaria, Northwest Nigeria. METHODS: A comparative cross-sectional study design was employed to compare the intelligence quotients of 401 participants (200 Almajirai and 201 public primary school pupils). All participants were administered a socio-demographic questionnaire and the Wechsler Intelligence Scale for Children Fourth Version (WISC-IV). RESULTS: Public primary school pupils performed significantly better than Almajirai on all administered subtests of the WISC-IV except arithmetic. The mean Full-Scale IQ score of Almajirai was significantly lower than that of public primary school pupils (60.30±11.49 vs. 70.12 ± 11.9, p< 0.001, 95% CI= -12.12-7.52). The intelligence quotient of Almajirai was associated with the age of the child and the father's level of education while that of public primary school pupils was associated with their current class in school. CONCLUSION: Public primary school pupils performed better than Almajirai on intelligence tests indicating a need to reform Almajiri Education. It is recommended that the system be strengthened and its curriculum expanded to include other modules rather than its current restriction to religious education.

CONTEXTE: Almajiri est un terme désignant un enfant envoyé loin de ses parents pour étudier le Coran sous la tutelle et les soins d'un érudit musulman, également appelé Mallam. Ces dernières années, la capacité du Mallam à subvenir aux besoins de ces enfants a diminué, les contraignant à mendier dans les rues pour survivre. La capacité cognitive de cette population a rarement été étudiée. Cette étude a été conçue pour comparer les quotients intellectuels des Almajirai fréquentant les écoles coraniques et ceux des élèves fréquentant les écoles primaires publiques à Zaria, dans le nord-ouest du Nigéria. MÉTHODES: Une étude comparative transversale a été menée pour comparer les quotients intellectuels de 401 participants (200 Almajirai et 201 élèves des écoles primaires publiques). Tous les participants ont rempli un questionnaire sociodémographique et le test d'intelligence pour enfants Wechsler, quatrième version (WISCIV). RÉSULTATS: Les élèves des écoles primaires publiques ont obtenu des résultats significativement meilleurs que les Almajirai dans tous les sous-tests du WISC-IV, à l'exception de l'arithmétique. Le score moyen de QI global des Almajirai était significativement inférieur à celui des élèves des écoles primaires publiques (60,30 ± 11,49 contre 70,12 ± 11,9, p < 0,001, IC à 95 % = -12,12 à -7,52). Le quotient intellectuel des Almajirai était associé à l'âge de l'enfant et au niveau d'éducation du père, tandis que celui des élèves des écoles primaires publiques était lié à leur classe actuelle à l'école. CONCLUSION: Les élèves des écoles primaires publiques ont mieux performé que les Almajirai aux tests d'intelligence, indiquant un besoin de réformer le système éducatif Almajiri. Il est recommandé de renforcer ce système et d'élargir son programme pour inclure d'autres modules au-delà de l'éducation religieuse actuelle. MOTS-CLÉS: Almajiri, Enfants des rues, Quotient intellectuel, Capacité cognitive, Nord-Ouest du Nigéria.

Kindness or Intelligence? Angry Men are Perceived as Less Intelligent by Their Female Romantic Partners.

We were interested in how people in a romantic relationship would perceive the intelligence of their partners who have high or low trait anger. Specifically, we referred to the tension between compassion (low anger) and competence (high intelligence) in mate choice. Some evolutionary theories suggest that mating might be considered a bargaining process between these two higher-order attributes. Our study involved 148 heterosexual couples in romantic relationships. We measured the relationship between relationship satisfaction, trait anger, objective intelligence, self-assessed intelligence, and subjectively assessed partners' intelligence. We found that angrier men were less satisfied in their romantic relationship than those men who were less angry, and their partners were also less satisfied in the relationship. Additionally, women perceived angrier men as less intelligent, an effect that remained after controlling for men's objective intelligence. Lastly, we found that women's perception of their partner's intelligence mediated the link between men's anger and relationship satisfaction for both sexes. Our findings suggest that both anger and intelligence play important roles in romantic relationship functioning, consistent with evolutionary theories that emphasize the value of competence (i.e., intelligence) and compassion (i.e., low anger) in romantic partners. Furthermore, our study highlights the importance of women's perception of their partner's intelligence in determining the quality of the relationship.

Executive functioning profiles and mathematical and reading achievement in Grades 2, 6, and 10.

Using a person-centered approach, we aimed to identify different executive functioning profiles to assess heterogeneity across individuals within the same school grade through latent profile analysis. A sample of 150 Grade 2 (7-8 years old), 150 Grade 6 (11-12 years old), and 150 Grade 10 (15-16 years old) children and adolescents were assessed on 11 different executive tasks representative of the three main executive functioning subcomponents (i.e., inhibition, cognitive flexibility, and working memory), fluid intelligence, processing speed, problem-solving, and reading comprehension. Three different executive functioning profiles of different patterns of interactions based on inhibition, cognitive flexibility, and working memory within and between grades were identified. Moreover, these profiles were differentially related to reading comprehension and mathematical achievement. Second, as expected, we did not find these profiles to be associated with sociodemographic variables such as chronological age or sex. Still, fluid intelligence and processing speed were differentially related to the different profiles at each grade. We also found that the executive functioning profiles interacted with each cognitive skill (i.e., fluid intelligence and processing speed) in predicting reading comprehension and math achievement. These findings provide valuable insights for developing preventive and intervention strategies in education.

Digital Twin Studies for Reverse Engineering the Origins of Visual Intelligence.

What are the core learning algorithms in brains? Nativists propose that intelligence emerges from innate domain-specific knowledge systems, whereas empiricists propose that intelligence emerges from domain-general systems that learn domain-specific knowledge from experience. We address this debate by reviewing digital twin studies designed to reverse engineer the learning algorithms in newborn brains. In digital twin studies, newborn animals and artificial agents are raised in the same environments and tested with the same tasks, permitting direct comparison of their learning abilities. Supporting empiricism, digital twin studies show that domain-general algorithms learn animal-like object perception when trained on the first-person visual experiences of newborn animals. Supporting nativism, digital twin studies show that domain-general algorithms produce innate domain-specific knowledge when trained on prenatal experiences (retinal waves). We argue that learning across humans, animals, and machines can be explained by a universal principle, which we call space-time fitting. Space-time fitting explains both empiricist and nativist phenomena, providing a unified framework for understanding the origins of intelligence.

Fluid intelligence but not need for cognition is associated with attitude change in response to the correction of misinformation.

Misinformation can profoundly impact an individual's attitudes-sometimes even after the misinformation has been corrected. In two preregistered experiments (N1 = 355, N2 = 725), we investigated whether individual differences in the ability and motivation to process information thoroughly influence the impact of misinformation in a news media context. More specifically, we tested whether fluid intelligence and need for cognition predicted the degree to which individuals who were exposed to misinformation changed their attitudes after receiving a correction message. We found consistent evidence that higher fluid intelligence is associated with a more pronounced correction effect, while need for cognition did not have a significant effect. This suggests that integrating a correction message with a previously encountered piece of misinformation can be challenging and that correction messages consequently need to be communicated in a way that is accessible to a broad audience.

What makes working memory work? A multifaceted account of the predictive power of working memory capacity.

Working memory capacity (WMC) has received a great deal of attention in cognitive psychology partly because WMC correlates broadly with other abilities (e.g., reading comprehension, second-language proficiency, fluid intelligence) and thus seems to be a critical aspect of cognitive ability. However, it is still rigorously debated why such correlations occur. Some theories posit a single ability (e.g., attention control, short-term memory capacity, controlled memory search) as the primary reason behind WMC's predictiveness, whereas others argue that WMC is predictive because it taps into multiple abilities. Here, we tested these single- and multifaceted accounts of WMC with a large-scale (N = 974) individual-differences investigation of WMC and three hypothesized mediators: attention control, primary memory, and secondary memory. We found evidence for a multifaceted account, such that no single ability could fully mediate the relation between WMC and higher order cognition (i.e., reading comprehension and fluid intelligence). Further, such an effect held regardless of whether WMC was measured via complex span or n-back. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Impact of Neurofeedback Training on Cognitive Abilities Assessed by the Wechsler Intelligence Scale for Children-Revised in Children with Attention Deficit: A Randomized Single-Blind Sham-Controlled Study.

Aim: This study aims to investigate the effects of a neurofeedback system on cognitive skills, as measured by the Wechsler Intelligence Scale for Children-Revised (WISC-R), in a cohort of 100 children aged 8 to 12 who were diagnosed with attention deficit.Materials and Methods: A randomized single-blind sham control group design was employed, with 50 participants assigned to the experimental group receiving neurofeedback training and 50 participants assigned to the sham group receiving simulated training. Participants were selected through random sampling from individuals seeking assistance at a specialized education center over the course of one year (May 2021-2022). Pre- and post-test WISC-R assessments were administered to both groups to evaluate participants' mental performance. The experimental group underwent a total of 60 sessions of quantitative electroencephalography-based infralow frequency neurofeedback training, with half-hour sessions conducted three days a week over a five-month period. The post-test WISC-R was administered at the end of the sixth month.Results: The results revealed significant differences between the pre- and post-training test scores, specifically in terms of verbal IQ, picture arrangement, performance IQ, and total IQ (p = 0.016, p = 0.001, p < 0.001, and p = 0.002, respectively), when comparing the differences between the two groups.Conclusion: These findings indicate a notable improvement in performance IQ, total IQ, and a reduction in attention deficits among the neurofeedback group based on the WISC-R assessments. Future studies should consider employing larger sample sizes, including appropriate control groups, and conducting long-term follow-ups to further elucidate the clinical significance of these results.

The minimal computational substrate of fluid intelligence.

The quantification of cognitive powers rests on identifying a behavioural task that depends on them. Such dependence cannot be assured, for the powers a task invokes cannot be experimentally controlled or constrained a priori, resulting in unknown vulnerability to failure of specificity and generalisability. Evaluating a compact version of Raven's Advanced Progressive Matrices (RAPM), a widely used clinical test of fluid intelligence, we show that LaMa, a self-supervised artificial neural network trained solely on the completion of partially masked images of natural environmental scenes, achieves representative human-level test scores a prima vista, without any task-specific inductive bias or training. Compared with cohorts of healthy and focally lesioned participants, LaMa exhibits human-like variation with item difficulty, and produces errors characteristic of right frontal lobe damage under degradation of its ability to integrate global spatial patterns. LaMa's narrow training and limited capacity suggest matrix-style tests may be open to computationally simple solutions that need not necessarily invoke the substrates of reasoning.

Sleep problems and duration in school-aged children at different levels of giftedness.

OBJECTIVES: Optimal sleep is crucial for developing and maintaining gifted children's cognitive abilities. However, only a few studies have explored the sleep profiles of gifted children and overlooked their internal variations. This study aimed to investigate subjective and object sleep profiles in school-aged gifted children with different levels of giftedness. METHODS: This study included 80 school-aged children (50 % male) aged 6-11 years. Giftedness was assessed using the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). Subjective and objective sleep were evaluated using the Children's Sleep Habits Questionnaire (CSHQ) and Actiwatch 2. RESULTS: The sample was divided into three groups based on their full scale intelligence quotient (IQ): 16 typically developing children (IQ < 130), 38 moderately gifted children (IQ: 130-145), and 26 highly gifted children (IQ > 145). The highly gifted children had the mildest sleep problems, particularly in sleep duration and daytime sleepiness. Moderately gifted children had the shortest subjective average sleep duration, while the three groups had no significant differences in Actiwatch-measured sleep variables. Furthermore, CSHQ total and daytime sleepiness subscale scores were negatively associated with the full scale IQ in gifted children after controlling for confounders including emotional and behavioral problems. CONCLUSIONS: Children with higher levels of giftedness experience fewer subjective sleep problems but have similar objective sleep parameters. It is imperative to implement tailored sleep strategies for fostering intellectual development and nurturing young talents.

Computational thinking in university students: The role of fluid intelligence and visuospatial ability.

Computational thinking (CT) is a set of problem-solving skills with high relevance in education and work contexts. The present paper explores the role of key cognitive factors underlying CT performance in non-programming university students. We collected data from 97 non-programming adults in higher education in a supervised setting. Fluid intelligence, crystallized intelligence, and visuospatial ability were assessed using computerized adaptive tests; CT was measured using the Computational Thinking test. The direct and indirect effects of gender and visuospatial ability through fluid intelligence on CT were tested in a serial multiple mediator model. Fluid intelligence predicted CT when controlling for the effects of gender, age, and visuospatial ability, while crystallized intelligence did not predict CT. Men had a small advantage in CT performance when holding the effects of cognitive abilities constant. Despite its large correlation with gender and CT, visuospatial ability did not directly influence CT performance. Overall, we found that programming-naive computational thinkers draw on their reasoning ability that does not rely on previously acquired knowledge to solve CT problems. Visuospatial ability and CT were spuriously associated. Drawing on the process overlap theory we propose that tests of fluid intelligence and CT sample an overlapping set of underlying visuospatial processes.

Predictive Representations: Building Blocks of Intelligence.

Adaptive behavior often requires predicting future events. The theory of reinforcement learning prescribes what kinds of predictive representations are useful and how to compute them. This review integrates these theoretical ideas with work on cognition and neuroscience. We pay special attention to the successor representation and its generalizations, which have been widely applied as both engineering tools and models of brain function. This convergence suggests that particular kinds of predictive representations may function as versatile building blocks of intelligence.

Characterising and differentiating cognitive and motor speed in older adults: structural equation modelling on a UK longitudinal birth cohort.

OBJECTIVES: Information processing speed (IPS) has been proposed to be a key component in healthy ageing and cognitive functioning. Yet, current studies lack a consistent definition and specific influential characteristics. This study aimed to investigate IPS as a multifaceted concept by differentiating cognitive and motor IPS. DESIGN, SETTING AND PARTICIPANTS: A retrospective data analysis using data from the Medical Research Council National Survey of Health and Development (a population-based cohort of UK adults born in 1946) at childhood (ages 8, 11 and 15) and adulthood (ages 60-64 and 68-70). Using structural equation modelling, we constructed two models of IPS with 2124 and 1776 participants, respectively. OUTCOME MEASURES: Measures of interest included IPS (ie, letter cancellation, simple and choice reaction time), intelligence (ie, childhood intelligence and National Adult Reading Test), verbal memory, socioeconomic status (SES) and cognitive functions measured by the Addenbrooke's Cognitive Examination III, as well as a variety of health indexes. RESULTS: We found distinct predictors for cognitive and motor IPS and how they relate to other cognitive functions in old age. In our first model, SES and antipsychotic medication usage emerged as significant predictors for cognitive IPS, intelligence and smoking as predictors for motor IPS while both share sex, memory and antiepileptic medication usage as common predictors. Notably, all differences between both IPS types ran in the same direction except for sex differences, with women performing better than men in cognitive IPS and vice versa in motor IPS. The second model showed that both IPS measures, as well as intelligence, memory, antipsychotic and sedative medication usage, explain cognitive functions later in life. CONCLUSION: Taken together, these results shed further light on IPS as a whole by showing there are distinct types and that these measures directly relate to other cognitive functions.

Cognitive ability, education, height and body mass index in relation to risk of schizophrenia and mortality following its diagnosis.

This study examines the hypotheses that the traits of higher IQ, longer education and taller height are associated with lower risk of death as compared to traits of low IQ, short education, and short height in men with schizophrenia compared to men without schizophrenia. In total, 937,919 men born 1939-59 and 1983-1997 with information from conscription were followed for incident schizophrenia in Danish registries. Higher levels of cognitive ability, longer education, and taller height were associated with fewer cases of schizophrenia. In a sub-sample of 652,368 men with information on body mass index, underweight was associated with more and overweight and obesity were associated with fewer cases of schizophrenia compared with normal weight. Higher cognitive ability, longer education, and taller height were associated with fewer deaths from both natural and unnatural causes in both men with and without schizophrenia. Underweight was associated with more deaths from natural and unnatural causes, whereas overweight and obesity were associated with more deaths from natural causes and fewer deaths from unnatural causes in both groups of men. Due to interaction, tall height and long educational duration were associated with fewer deaths from natural causes, and obesity was associated with fewer deaths from unnatural causes among men with schizophrenia compared to men without. In conclusion, traits in young adulthood are associated with higher mortality in men with and without schizophrenia, but traits of long educational duration and obesity seem to be especially important for lower mortality in men with schizophrenia.

Sensory intelligence for extraction of abstract auditory rules from a speech sound stream in children with cochlear implants.

OBJECTIVE: Sensory intelligence in the brain helps listeners automatically extract abstract auditory rules formed by invariant acoustic features from complex speech sound streams, presumably serving as the neural basis for speech comprehension. However, whether this intelligence is deficient in children with cochlear implants (CIs) remains unclear. METHODS: Mandarin Chinese monosyllables shared a flat lexical tone contour to form an abstract auditory rule but differed in other acoustic features to construct a complex speech sound stream. The abstract rule was occasionally violated by monosyllables with a rising or falling lexical tone. RESULTS: In normal hearing (NH) children, the abstract auditory rule could be extracted, as revealed by a mismatch negativity (MMN) and a late discriminative negativity (LDN). However, the MMN and LDN were only evoked in CI children with good hearing and speech performance. NH children with a higher speech perception or spatial hearing score had a greater MMN. The LDN was attenuated with increasing age in NH children. CONCLUSIONS: The sensory intelligence for extraction of auditory abstract rules, associated with speech perception, is deficient in CI children. This intelligence may gradually develop during childhood and adolescence. SIGNIFICANCE: Deficient sensory intelligence in CI children may aid in understanding poor speech comprehension in complex environments.

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

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