The neuroscience of human intelligence differences

Questioning cognitive heterogeneity and intellectual functioning in fetal alcohol spectrum disorders from the Wechsler Intelligence Scale for Children

Introduction: Fetal Alcohol Spectrum Disorders (FASD) are characterized by a variety of multiple cognitive and behavioral impairments, with intellectual, attentional, and executive impairments being the most commonly reported. In populations with multiple neurodevelopmental disorders, the Full Scale Intelligence Quotient (FSIQ) may not be a proper measure of intellectual abilities, rarely interpreted in FASD clinical practice because the heterogeneity of the cognitive profile is deemed too strong. We propose a quantitative characterization of this heterogeneity, of the strengths and weaknesses profile, and a differential analysis between global cognitive (FSIQ) and elementary reasoning abilities in a large retrospective monocentric FASD sample. Methods: Using clinical and cognitive data (Wechsler Intelligence Scale for Children) from 107 children with FASD, we characterized subject heterogeneity (variance and scatter of scaled/composite scores), searched for strengths and weaknesses, and specified intellectual functioning in terms of FSIQ and elementary reasoning (General Abilities Index, Highest Reasoning Scaled Score), in comparison with standardization norms and a Monte-Carlo-simulated sample from normalization data. Results: Performance of children with FASD was lower on all subtests, with a significant weakness in working memory and processing speed. We found no increase in the variance and scatter of the scores, but a discordance between the assessment of global cognitive functioning (28% borderline, 23% deficient) and that of global and elementary reasoning abilities (23-9% borderline, 15-14% deficient). Conclusion: Our results question the notion of WISC profile heterogeneity in FASD and point to working memory and processing speed over-impairment, with global repercussions but most often preserved elementary reasoning abilities.

Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

Improving Predictability, Test-Retest Reliability and Generalisability of Brain-Wide Associations for Cognitive Abilities via Multimodal Stacking

Brain-wide association studies (BWASs) have attempted to relate cognitive abilities with brain phenotypes, but have been challenged by issues such as predictability, test-retest reliability, and cross-cohort generalisability. To tackle these challenges, we proposed "stacking" that combines brain magnetic resonance imaging of different modalities, from task-fMRI contrasts and functional connectivity during tasks and rest to structural measures, into one prediction model. We benchmarked the benefits of stacking, using the Human Connectome Projects: Young Adults and Aging and the Dunedin Multidisciplinary Health and Development Study. For predictability, stacked models led to out-of-sample r ∼.5-.6 when predicting cognitive abilities at the time of scanning and 36 years earlier. For test-retest reliability, stacked models reached an excellent level of reliability (ICC>.75), even when we stacked only task-fMRI contrasts together. For generalisability, a stacked model with non-task MRI built from one dataset significantly predicted cognitive abilities in other datasets. Altogether, stacking is a viable approach to undertake the three challenges of BWAS for cognitive abilities.

Imitating and exploring the human brain's resting and task-performing states via brain computing: scaling and architecture

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex (V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart, despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects.

Verbal and non-verbal skills in early childhood: dimensionality, developmental trajectories, and gender differences

This study examines the dimensionality of and relationships between two subscales from the British Ability Scales - Third Edition, measuring verbal (expressive vocabulary) and non-verbal (reasoning) cognitive skills for toddlers (age three) and preschoolers (age five), in a Norwegian context across genders. Descriptive statistics revealed item selection criteria that included specific items within each subscale. Subsequently, Confirmatory Factor Analysis established the subscales' dimensionality (Naming Vocabulary and Picture Similarities; N = 1094) and confirmed measurement invariance across genders. Further, the relationships between the verbal and non-verbal factors were investigated using correlation analysis and Structural Equation Modeling. The findings revealed that the verbal factor at age three strongly predicted the verbal factor at age five and significantly influenced the non-verbal factor at age five. The non-verbal factor at age three exhibited a moderate predictive relationship with the non-verbal factor at age five, and did not significantly predict the verbal factor at age five. In terms of gender differences, girls showed higher scores on the verbal factor at age three, and a stronger correlation between the non-verbal factor at age three and the verbal factor at age five. In summary, this research provides valuable insights into cognitive skill measurement and development in a Norwegian context and highlights possible variations across gender. The study's findings, limitations, and implications are discussed.

Structural-functional brain network coupling predicts human cognitive ability

Individual differences in general cognitive ability (GCA) have a biological basis within the structure and function of the human brain. Network neuroscience investigations revealed neural correlates of GCA in structural as well as in functional brain networks. However, whether the relationship between structural and functional networks, the structural-functional brain network coupling (SC-FC coupling), is related to individual differences in GCA remains an open question. We used data from 1030 adults of the Human Connectome Project, derived structural connectivity from diffusion weighted imaging, functional connectivity from resting-state fMRI, and assessed GCA as a latent g-factor from 12 cognitive tasks. Two similarity measures and six communication measures were used to model possible functional interactions arising from structural brain networks. SC-FC coupling was estimated as the degree to which these measures align with the actual functional connectivity, providing insights into different neural communication strategies. At the whole-brain level, higher GCA was associated with higher SC-FC coupling, but only when considering path transitivity as neural communication strategy. Taking region-specific variations in the SC-FC coupling strategy into account and differentiating between positive and negative associations with GCA, allows for prediction of individual cognitive ability scores in a cross-validated prediction framework (correlation between predicted and observed scores: r = 0.25, p < .001). The same model also predicts GCA scores in a completely independent sample (N = 567, r = 0.19, p < .001). Our results propose structural-functional brain network coupling as a neurobiological correlate of GCA and suggest brain region-specific coupling strategies as neural basis of efficient information processing predictive of cognitive ability.

From gifted to high potential and twice exceptional: A state-of-the-art meta-review

Despite the abundant literature on intelligence and high potential individuals, there is still a lack of international consensus on the terminology and clinical characteristics associated to this population. It has been argued that unstandardized use of diagnosis tools and research methods make comparisons and interpretations of scientific and epidemiological evidence difficult in this field. If multiple cognitive and psychological models have attempted to explain the mechanisms underlying high potentiality, there is a need to confront new scientific evidence with the old, to uproot a global understanding of what constitutes the neurocognitive profile of high-potential in gifted individuals. Another particularly relevant aspect of applied research on high potentiality concerns the challenges faced by individuals referred to as "twice exceptional" in the field of education and in their socio-affective life. Some individuals have demonstrated high forms of intelligence together with learning, affective or neurodevelopmental disorders posing the question as to whether compensating or exacerbating psycho-cognitive mechanisms might underlie their observed behavior. Elucidating same will prove relevant to questions concerning the possible need for differential diagnosis tools, specialized educational and clinical support. A meta-review of the latest findings from neuroscience to developmental psychology, might help in the conception and reviewing of intervention strategies.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability

BACKGROUND

Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG.

METHODS

We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources.

RESULTS

We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia.

CONCLUSION

We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.

The effects of musical instrument training on fluid intelligence and executive functions in healthy older adults: A systematic review and meta-analysis

Intervention studiescombiningcognitive and motor demands have reported far-transfer cognitive benefits in healthy ageing. This systematic review and meta-analysis evaluated the effects of music and rhythm intervention on cognition in older adulthood. Inclusion criteria specified: 1) musical instrument training; 2) healthy, musically-naïve adults (≥60 years); 3) control group; 4) measure of executive function. Ovid, PubMed, Scopus and the Cochrane Library online databases were searched in August 2023. Data from thirteen studies were analysed (N = 502 participants). Study quality was assessed using the Cochrane Risk of Bias tool (RoB 2; Sterne et al., 2019). Random effects models revealed: a low effect on inhibition (d = 0.27,p = .0335); a low-moderate effect on switching (d = -0.39, p = .0021); a low-moderate effect on verbal category switching (d =0.39,p = .0166); and a moderate effect on processing speed (d = 0.47,p < .0001). No effect was found for selective visual attention, working memory, or verbal memory. With regards to overall bias, three studies were rated as "high", nine studies were rated as having "some concerns" and one was rated "low". The meta-analysis suggests that learning to play a musical instrument enhances attention inhibition, switching and processing speed in ageing.

Composite adaptive fuzzy bipartite consensus of fractional-order multiagent systems with a switched event-triggered mechanism

This paper focuses on online recorded-data-based composite adaptive fuzzy bipartite consensus control for uncertain fractional-order multiagent systems with interconnected terms and external disturbances by employing a switched-threshold-based event-triggered mechanism (ETM) under the backstepping structure. Fuzzy logic system is used as a universal function approximation to deal with function uncertainties that are not prone to model in the system. A new composite learning adaptive parameter design scheme that synthesizes both prediction error and tracking error is developed to enhance the tracking performance, where the prediction error is raised from the utilization of online recorded data and instantaneous data. A unique switched-threshold-based ETM is introduced, in which the information transmission between the sensor and the controller is imposed on one of the individuals. One merit of this work consists in that it can automatically and rapidly switch and adjust between the fixed threshold and relative threshold ETM according to the amplitude of input signals to balance the network resources and impede the occurrence of pulse phenomenon. In addition, it is theoretically proven that the proposed scheme can ensure that all internal signals of the closed-loop system are bounded and achieve local bipartite consistent errors through the fractional Lyapunov stability criterion. Finally, a numerical example is provided to confirm the feasibility of the proposed approach.

The artificial intelligence revolution in primary care: Challenges, dilemmas and opportunities

Artificial intelligence (AI) can be a valuable tool for primary care (PC), as, among other things, it can help healthcare professionals improve diagnostic accuracy, chronic disease management and the overall efficiency of the care they provide. It is important to emphasise that AI should not be seen as a replacement tool, but as an aid to PC professionals. Although AI is capable of processing large amounts of data and generating accurate predictions, it cannot replace the skill and expertise of professionals in clinical decision making. AI still requires the interpretation and clinical judgement of a trained healthcare professional and cannot provide the empathy and emotional support often required in healthcare.

Cortical impoverishment in a stable subgroup of schizophrenia: Validation across various stages of psychosis

BACKGROUND

Cortical thinning is a well-known feature in schizophrenia. The considerable variation in the spatial distribution of thickness changes has been used to parse heterogeneity. A 'cortical impoverishment' subgroup with a generalized reduction in thickness has been reported. However, it is unclear if this subgroup is recoverable irrespective of illness stage, and if it relates to the glutamate hypothesis of schizophrenia.

METHODS

We applied hierarchical cluster analysis to cortical thickness data from magnetic resonance imaging scans of three datasets in different stages of psychosis (n = 288; 160 patients; 128 healthy controls) and studied the cognitive and symptom profiles of the observed subgroups. In one of the samples, we also studied the subgroup differences in 7-Tesla magnetic resonance spectroscopy glutamate concentration in the dorsal anterior cingulate cortex.

RESULTS

Our consensus-based clustering procedure consistently produced 2 subgroups of participants. Patients accounted for 75%-100% of participants in one subgroup that was characterized by significantly lower cortical thickness. Both subgroups were equally symptomatic in clinically unstable stages, but cortical impoverishment indicated a higher symptom burden in a clinically stable sample and higher glutamate levels in the first-episode sample. There were no subgroup differences in cognitive and functional outcome profiles or antipsychotic exposure across all stages.

CONCLUSIONS

Cortical thinning does not vary with functioning or cognitive impairment, but it is more prevalent among patients, especially those with glutamate excess in early stages and higher residual symptom burden at later stages, providing an important mechanistic clue to one of the several possible pathways to the illness.

Improved estimation of general cognitive ability and its neural correlates with a large battery of cognitive tasks

Elucidating the neural mechanisms of general cognitive ability (GCA) is an important mission of cognitive neuroscience. Recent large-sample cohort studies measured GCA through multiple cognitive tasks and explored its neural basis, but they did not investigate how task number, factor models, and neural data type affect the estimation of GCA and its neural correlates. To address these issues, we tested 1,605 Chinese young adults with 19 cognitive tasks and Raven's Advanced Progressive Matrices (RAPM) and collected resting state and n-back task fMRI data from a subsample of 683 individuals. Results showed that GCA could be reliably estimated by multiple tasks. Increasing task number enhances both reliability and validity of GCA estimates and reliably strengthens their correlations with brain data. The Spearman model and hierarchical bifactor model yield similar GCA estimates. The bifactor model has better model fit and stronger correlation with RAPM but explains less variance and shows weaker correlations with brain data than does the Spearman model. Notably, the n-back task-based functional connectivity patterns outperform resting-state fMRI in predicting GCA. These results suggest that GCA derived from a multitude of cognitive tasks serves as a valid measure of general intelligence and that its neural correlates could be better characterized by task fMRI than resting-state fMRI data.

From mother to child: How intergenerational transfer is reflected in similarity of corticolimbic brain structure and mental health

BACKGROUND

Intergenerational transfer effects include traits transmission from parent to child. While behaviorally well documented, studies on intergenerational transfer effects for brain structure or functioning are scarce, especially those examining relations of behavioral and neurobiological endophenotypes. This study aims to investigate behavioral and neural intergenerational transfer effects associated with the corticolimbic circuitry, relevant for socioemotional functioning and mental well-being.

METHODS

T1-neuroimaging and behavioral data was obtained from 72 participants (39 mother-child dyads/ 39 children; 7-13 years; 16 girls/ 33 mothers; 26-52 years). Gray matter volume (GMV) was extracted from corticolimbic regions (subcortical: amygdala, hippocampus, nucleus accumbens; neocortical: anterior cingulate, medial orbitofrontal areas). Mother-child similarity was quantified by correlation coefficients and comparisons to random adult-child pairs.

RESULTS

We identified significant corticolimbic mother-child similarity (r = 0.663) stronger for subcortical over neocortical regions. Mother-child similarity in mental well-being was significant (r = 0.409) and the degree of dyadic similarity in mental well-being was predicted by similarity in neocortical, but not subcortical GMV.

CONCLUSION

Intergenerational neuroimaging reveals significant mother-child transfer for corticolimbic GMV, most strongly for subcortical regions. However, variations in neocortical similarity predicted similarity in mother-child well-being. Ultimately, such techniques may enhance our knowledge of behavioral and neural familial transfer effects relevant for health and disease.

A Comparative Perspective on the Cerebello-Cerebral System and Its Link to Cognition

The longstanding idea that the cerebral cortex is the main neural correlate of human cognition can be elaborated by comparative analyses along the vertebrate phylogenetic tree that support the view that the cerebello-cerebral system is suited to support non-motor functions more generally. In humans, diverse accounts have illustrated cerebellar involvement in cognitive functions. Although the neocortex, and its transmodal association cortices such as the prefrontal cortex, have become disproportionately large over primate evolution specifically, human neocortical volume does not appear to be exceptional relative to the variability within primates. Rather, several lines of evidence indicate that the exceptional volumetric increase of the lateral cerebellum in conjunction with its connectivity with the cerebral cortical system may be linked to non-motor functions and mental operation in primates. This idea is supported by diverging cerebello-cerebral adaptations that potentially coevolve with cognitive abilities across other vertebrates such as dolphins, parrots, and elephants. Modular adaptations upon the vertebrate cerebello-cerebral system may thus help better understand the neuroevolutionary trajectory of the primate brain and its relation to cognition in humans. Lateral cerebellar lobules crura I-II and their reciprocal connections to the cerebral cortical association areas appear to have substantially expanded in great apes, and humans. This, along with the notable increase in the ventral portions of the dentate nucleus and a shift to increased relative prefrontal-cerebellar connectivity, suggests that modular cerebellar adaptations support cognitive functions in humans. In sum, we show how comparative neuroscience provides new avenues to broaden our understanding of cerebellar and cerebello-cerebral functions in the context of cognition.

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

Assessment of the corpus callosum size in male individuals with high intelligence quotient (members of Mensa International)

OBJECTIVES

The aim of this study was to assess the size of the corpus callosum in members of Mensa International, which is the world's largest and oldest high-intelligence quotient (IQ) society.

METHODS

We performed T2-weighted magnetic resonance imaging (Repetition Time, TR = 3200 ms, Time of Echo, TE = 409 ms) to examine the brain of members of Mensa International (Polish national group) in order to assess the size of the corpus callosum. Results from 113 male MENSA members and 96 controls in the age range of 21-40 years were analyzed.

RESULTS

The comparative analysis showed that the mean length of the corpus callosum and the thickness of the isthmus were significantly greater in the Mensa members compared to the control groups. A statistically significant difference was also identified in the largest linear dimension of the brain from the frontal lobe to the occipital lobe. The mean corpus callosum cross-sectional area and its ratio to the brain area were significantly greater in the Mensa members.

CONCLUSIONS

The results show that the dimensions (linear measures and midsagittal cross-sectional surface area) of the corpus callosum were significantly greater in the group of Mensa members than in the controls.

Association Study Between White Matter Microstructure and Intelligence Decline in Schizophrenia

Patients with schizophrenia can exhibit intelligence decline, which is an important element of cognitive impairment. Previous magnetic resonance imaging (MRI) studies have demonstrated that patients with schizophrenia have altered gray matter structures and functional connectivity associated with intelligence decline defined by a difference between premorbid and current intelligence quotients (IQs). However, it has remained unclear whether white matter microstructures are related to intelligence decline. In the present study, the indices of diffusion tensor imaging (DTI) obtained from 138 patients with schizophrenia and 554 healthy controls were analyzed. The patients were classified into three subgroups based on intelligence decline: deteriorated (94 patients), preserved (42 patients), and compromised IQ (2 patients) groups. Given that the DTI of each subject was acquired using either one of two different MRI scanners, we analyzed DTI indices separately for each scanner group. In the comparison between the deteriorated IQ group and the healthy controls, differences in some DTI indices were noted in three regions of interest irrespective of the MRI scanners, whereas differences in only one region of interest were noted between the preserved IQ group and the healthy controls. However, the comparisons between the deteriorated and preserved IQ groups did not show any reproducible differences. Together with the previous findings, it is thought that gray matter structures and functional connectivity are more promising as markers of intelligence decline in schizophrenia than white matter microstructures.

Greater maltreatment severity is associated with smaller brain volume with implication for intellectual ability in young children

Background

Childhood maltreatment profoundly alters trajectories of brain development, promoting markedly increased long-term health risks and impaired intellectual development. However, the immediate impact of maltreatment on brain development in children and the extent to which altered global brain volume contributes to intellectual development in children with maltreatment experience is currently unknown. We here utilized MRI data obtained from children within 6 months after the exposure to maltreatment to assess the association of maltreatment severity with global brain volume changes. We further assessed the association between maltreatment severity and intellectual development and tested for the mediating effect of brain volume on this association.

Method

We used structural MRI (3T) in a sample of 49 children aged 3-5 years with maltreatment exposure, i.e. emotional and physical abuse and/or neglect within 6 months, to characterize intracranial and tissue-specific volumes. Maltreatment severity was coded using the Maternal Interview for the Classification of Maltreatment. IQ was tested at study entry and after one year using the Snijders Oomen Nonverbal Test.

Results

Higher maltreatment severity was significantly correlated with smaller intracranial volume (r = -.393, p = .008), which was mainly driven by lower total brain volume (r = -.393, p = .008), which in turn was primarily due to smaller gray matter volume (r = -.454, p = .002). Furthermore, smaller gray matter volume was associated with lower IQ at study entry (r = -.548, p < .001) and predicted IQ one year later (r = -.493, p = .004.). The observed associations were independent of potential confounding variables, including height, socioeconomic status, age and sex.

Importance

We provide evidence that greater maltreatment severity in early childhood is related to smaller brain size at a very young age with significant consequences for intellectual ability, likely setting a path for far-reaching long-term disadvantages. Insights into the molecular and neural processes that underlie the impact of maltreatment on brain structure and function are urgently needed to derive mechanism-driven targets for early intervention.

Co-development among reading, math, science, and verbal working memory in the elementary stage

With a focus on within-person effects, this study investigated mutualism among academic skills (reading, math, science) and between those skills and verbal working memory in a general population sample and groups with high or low skills from Grades 2 to 5 (2010-2016, N = 859-9040, age 6.27-13.13 years, 49% female, ethnically diverse). Mutualism was found between reading and science in all high-ability groups, and between reading/math and verbal working memory only in high-math students. These results remained the same when controlled for socioeconomic status and gender, and with sensitivity analyses. High-skill students (especially high-math students) may improve academic performance through accumulation of academic knowledge and mutualism between academic and cognition. Such mutualism may be driven by high-quality, intensive academic practice.

A Bivariate Twin Study of Cortical Surface Area and Verbal and Nonverbal Intellectual Skills in Adolescence

Understanding the biological basis of cognitive differences between individuals is the goal in human intelligence research. The surface area of the cortex is considered to be a key determinant of human intelligence. Adolescence is a period of development characterized by physiological, emotional, behavioral, and psychosocial changes, which is related to the recombination and optimization of the cerebral cortex, and cognitive ability changes significantly in children and adolescents. This study examined the effects of common genetic and environmental factors between the surface area of the cerebral cortex and intelligence in typical developing adolescents (twins, n = 114, age 12-18 years old). Cortical surface area data were parsed into subregions (i.e., frontal, parietal, occipital, and temporal areas) and intelligence into verbal and nonverbal skills. We found a phenotypic correlation between regional surface areas and verbal intelligence. No correlation was observed between regional surface areas and nonverbal intelligence, except for the occipital lobe and the right hemisphere. In the bivariate twin analyses, the differences in phenotypic correlation between regional surface areas and verbal intelligence were not due to unshared environmental effects or measurement error, but to genetic effects. In summary, the current study has broadened the previous genetic investigations of cognitive ability and cortical surface area.

Different patterns of intrinsic functional connectivity at the default mode and attentional networks predict crystalized and fluid abilities in childhood

Crystallized abilities are skills used to solve problems based on experience, while fluid abilities are linked to reasoning without evoke prior knowledge. To what extent crystallized and fluid abilities involve dissociated or overlapping neural systems is debatable. Due to often deployed small sample sizes or different study settings in prior work, the neural basis of crystallized and fluid abilities in childhood remains largely unknown. Here we analyzed within and between network connectivity patterns from resting-state functional MRI of 2707 children between 9 and 10 years from the ABCD study. We hypothesized that differences in functional connectivity at the default mode network (DMN), ventral, and dorsal attentional networks (VAN, DAN) explain differences in fluid and crystallized abilities. We found that stronger between-network connectivity of the DMN and VAN, DMN and DAN, and VAN and DAN predicted crystallized abilities. Within-network connectivity of the DAN predicted both crystallized and fluid abilities. Our findings reveal that crystallized abilities rely on the functional coupling between attentional networks and the DMN, whereas fluid abilities are associated with a focal connectivity configuration at the DAN. Our study provides new evidence into the neural basis of child intelligence and calls for future comparative research in adulthood during neuropsychiatric diseases.

Preoperative thalamus volume is not associated with preoperative cognitive impairment (preCI) or postoperative cognitive dysfunction (POCD)

A growing body of literature suggests the important role of the thalamus in cognition and neurodegenerative diseases. This study aims to elucidate whether the preoperative thalamic volume is associated with preoperative cognitive impairment (preCI) and whether it is predictive for postoperative cognitive dysfunction at 3 months (POCD). We enrolled 301 patients aged 65 or older and without signs of dementia who were undergoing elective surgery. Magnetic resonance imaging was conducted prior to surgery. Freesurfer (version 5.3.) was used to automatically segment the thalamus volume. A neuropsychological test battery was administered before surgery and at a 3 month follow-up. It included the computerized tests Paired Associate Learning (PAL), Verbal Recognition Memory (VRM), Spatial Span Length (SSP), Simple Reaction Time (SRT), the pen-and-paper Trail-Making-Test (TMT) and the manual Grooved Pegboard Test (GPT). Using a reliable change index, preCI and POCD were defined as total Z-score > 1.96 (sum score over all tests) and/or Z-scores > 1.96 in ≥ 2 individual cognitive test parameters. For statistical analyses, multivariable logistic regression models were applied. Age, sex and intracranial volume were covariates in the models. Of 301 patients who received a presurgical neuropsychological testing and MRI, 34 (11.3%) had preCI. 89 patients (29.5%) were lost to follow-up. The remaining 212 patients received a follow-up cognitive test after 3 months, of whom 25 (8.3%) presented with POCD. Independently of age, sex and intracranial volume, neither preCI (OR per cm³ increment 0.81 [95% CI 0.60-1.07] p = 0.14) nor POCD (OR 1.02 per cm³ increment [95% CI 0.75-1.40] p = 0.87) were statistically significantly associated with patients' preoperative thalamus volume. In this cohort we could not show an association of presurgical thalamus volume with preCI or POCD.Clinical Trial Number: NCT02265263 ( https://clinicaltrials.gov/ct2/show/results/NCT02265263 ).

Genes associated with cognitive ability and HAR show overlapping expression patterns in human cortical neuron types

GWAS have identified numerous genes associated with human cognition but their cell type expression profiles in the human brain are unknown. These genes overlap with human accelerated regions (HARs) implicated in human brain evolution and might act on the same biological processes. Here, we investigated whether these gene sets are expressed in adult human cortical neurons, and how their expression relates to neuronal function and structure. We find that these gene sets are preferentially expressed in L3 pyramidal neurons in middle temporal gyrus (MTG). Furthermore, neurons with higher expression had larger total dendritic length (TDL) and faster action potential (AP) kinetics, properties previously linked to intelligence. We identify a subset of genes associated with TDL or AP kinetics with predominantly synaptic functions and high abundance of HARs.

Associations of sport participation with subjective well-being: a study consisting of a sample of Chinese school-attending students

Purpose

Past studies have illustrated that the impact of sports participation on school-attending students' well-being plays a significant role in the life course of adolescence, which is a golden period for developing sound psychological qualities. However, the relationship between sports participation and subjective well-being is not clear, particularly in Chinese primary and middle schools. Therefore, the current study was aimed to explore the relationship between sports participation and subjective well-being in elementary and middle schools in China.

Method

All involved children and adolescents were asked to conduct a self-report of their sociodemographic factors (e.g., sex, grade, and age), independence, and outcomes. The survey involved a two-stage sampling design (district school). Besides, in order to examine the relationship between participation in sports and subjective well-being, a self-report questionnaire was used. Logistic regression with 95% confidence interval and odds ratios (ORs), was conducted to investigate the relationship between sports participation and subjective well-being.

Results

A total of 67,281 participants in total provided complete data for the final analysis of the current study. The percentage of boys and girls was 51.9% and 48.1%, namely. The current study found that compared with children who never participate in sports, those children who participated sports in 1-3 times a month, 1-2 times a week, and 3 times a week and above were more likely to enjoy better well-being. Compared with children who never participate in sports, those children who in every grade participated sports in 1-3 times a month, 1-2 times a week, and 3 times a week and above were more likely to achieve better well-being.

Conclusion

Our current study offered the positive effect of sports participation on children and adolescents' subjective well-being. For schools and governments, further studies are needed to focus on sports participation and positive feedback on adolescents' mental health, and the three parties' endeavors should be intervened.

Arterial stiffness and its influence on cerebral morphology and cognitive function

Background

Recently, arterial stiffness has been associated with cerebral small vessel disease (SVD), brain atrophy and vascular dementia. Arterial stiffness is assessed via pulse wave velocity (PWV) measurement and is strongly dependent on arterial blood pressure. While circadian blood pressure fluctuations are important determinants of end-organ damage, the role of 24-h PWV variability is yet unclear.

Objectives

We here investigated the association between PWV and its circadian changes on brain morphology and cognitive function in community-dwelling individuals.

Design

Single-centre, prospective, community-based follow-up study.

Methods

The study cohort comprised elderly community-based participants of the Austrian Stroke Prevention Family Study which was started in 2006. Patients with any history of cerebrovascular disease or dementia were excluded. The study consists of 84 participants who underwent ambulatory 24-h PWV measurement. White matter hyperintensity volume and brain volume were evaluated by 3-Tesla magnetic resonance imaging (MRI). A subgroup of patients was evaluated for cognitive function using an extensive neuropsychological test battery.

Results

PWV was significantly related to reduced total brain volume (p = 0.013), which was independent of blood pressure and blood pressure variability. We found no association between PWV with markers of cerebral SVD or impaired cognitive functioning. Only night-time PWV values were associated with global brain atrophy (p = 0.005).

Conclusions

This study shows a relationship of arterial stiffness and reduced total brain volume. Elevations in PWV during night-time are of greater importance than day-time measures.

Meta-analytic relations between personality and cognitive ability

Cognitive ability and personality are fundamental domains of human psychology. Despite a century of vast research, most ability-personality relations remain unestablished. Using contemporary hierarchical personality and cognitive abilities frameworks, we meta-analyze unexamined links between personality traits and cognitive abilities and offer large-scale evidence of their relations. This research quantitatively summarizes 60,690 relations between 79 personality and 97 cognitive ability constructs in 3,543 meta-analyses based on data from millions of individuals. Sets of novel relations are illuminated by distinguishing hierarchical personality and ability constructs (e.g., factors, aspects, facets). The links between personality traits and cognitive abilities are not limited to openness and its components. Some aspects and facets of neuroticism, extraversion, and conscientiousness are also considerably related to primary as well as specific abilities. Overall, the results provide an encyclopedic quantification of what is currently known about personality-ability relations, identify previously unrecognized trait pairings, and reveal knowledge gaps. The meta-analytic findings are visualized in an interactive webtool. The database of coded studies and relations is offered to the scientific community to further advance research, understanding, and applications.

Structural architecture and brain network efficiency link polygenic scores to intelligence

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

Human and chimpanzee shared and divergent neurobiological systems for general and specific cognitive brain functions

A long-standing topic of interest in human neurosciences is the understanding of the neurobiology underlying human cognition. Less commonly considered is to what extent such systems may be shared with other species. We examined individual variation in brain connectivity in the context of cognitive abilities in chimpanzees (n = 45) and humans in search of a conserved link between cognition and brain connectivity across the two species. Cognitive scores were assessed on a variety of behavioral tasks using chimpanzee- and human-specific cognitive test batteries, measuring aspects of cognition related to relational reasoning, processing speed, and problem solving in both species. We show that chimpanzees scoring higher on such cognitive skills display relatively strong connectivity among brain networks also associated with comparable cognitive abilities in the human group. We also identified divergence in brain networks that serve specialized functions across humans and chimpanzees, such as stronger language connectivity in humans and relatively more prominent connectivity between regions related to spatial working memory in chimpanzees. Our findings suggest that core neural systems of cognition may have evolved before the divergence of chimpanzees and humans, along with potential differential investments in other brain networks relating to specific functional specializations between the two species.

Learning how network structure shapes decision-making for bio-inspired computing

To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications.

SORL1 rs1699102 Moderates the Effect of Sex on Language Network

BACKGROUND

Language ability differs between the sexes. However, it is unclear how this sex difference is moderated by genetic factors and how the brain interacts with genetics to support this specific language capacity. Previous studies have demonstrated that the sorting protein-related receptor (SORL1) polymorphism influences cognitive function and brain structure differently in males and females and is associated with Alzheimer's disease risk.

OBJECTIVE

The aim of this study was to investigate the effects of sex and the SORL1 rs1699102 (CC versus T carriers) genotype on language.

METHODS

103 non-demented Chinese older adults from Beijing Aging Brain Rejuvenation Initiative (BABRI) database were included in this study. Participants completed language tests, T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional MRI. Language test performance, gray matter volume, and network connections were compared between genotype and sex groups.

RESULTS

The rs1699102 polymorphism moderated the effects of sex on language performance, with the female having reversed language advantages in T carriers. The T allele carriers had lower gray matter volume in the left precentral gyrus. The effect of sex on language network connections was moderated by rs1699102; male CC homozygotes and female T carriers had higher internetwork connections, which were negatively correlated with language performance.

CONCLUSION

These results suggest that SORL1 moderates the effects of sex on language, with T being a risk allele, especially in females. Our findings underscore the importance of considering the influence of genetic factors when examining sex effects.

Cortical thickness, gray matter volume, and cognitive performance: a crosssectional study of the moderating effects of age on their interrelationships

In a sample comprising younger, middle-aged, and older cognitively healthy adults (N = 375), we examined associations between mean cortical thickness, gray matter volume (GMV), and performance in 4 cognitive domains-memory, speed, fluency, and crystallized intelligence. In almost all cases, the associations were moderated significantly by age, with the strongest associations in the older age group. An exception to this pattern was identified in a younger adult subgroup aged <23 years when a negative association between cognitive performance and cortical thickness was identified. Other than for speed, all associations between structural metrics and performance in specific cognitive domains were fully mediated by mean cognitive ability. Cortical thickness and GMV explained unique fractions of the variance in mean cognitive ability, speed, and fluency. In no case, however, did the amount of variance jointly explained by the 2 metrics exceed 7% of the total variance. These findings suggest that cortical thickness and GMV are distinct correlates of domain-general cognitive ability, that the strength and, for cortical thickness, the direction of these associations are moderated by age, and that these structural metrics offer only limited insights into the determinants of individual differences in cognitive performance across the adult lifespan.

Artificial intelligence in medical device software and high-risk medical devices - a review of definitions, expert recommendations and regulatory initiatives

INTRODUCTION

Artificial intelligence (AI) encompasses a wide range of algorithms with risks when used to support decisions about diagnosis or treatment, so professional and regulatory bodies are recommending how they should be managed.

AREAS COVERED

AI systems may qualify as standalone medical device software (MDSW) or be embedded within a medical device. Within the European Union (EU) AI software must undergo a conformity assessment procedure to be approved as a medical device. The draft EU Regulation on AI proposes rules that will apply across industry sectors, while for devices the Medical Device Regulation also applies. In the CORE-MD project (Coordinating Research and Evidence for Medical Devices), we have surveyed definitions and summarize initiatives made by professional consensus groups, regulators, and standardization bodies.

EXPERT OPINION

The level of clinical evidence required should be determined according to each application and to legal and methodological factors that contribute to risk, including accountability, transparency, and interpretability. EU guidance for MDSW based on international recommendations does not yet describe the clinical evidence needed for medical AI software. Regulators, notified bodies, manufacturers, clinicians and patients would all benefit from common standards for the clinical evaluation of high-risk AI applications and transparency of their evidence and performance.

Effective connectivity analysis of brain networks of mathematically gifted adolescents using transfer entropy

Using functional neuroimaging, electrophysiological techniques and neural data processing techniques, neuroscientists have found that mathematically gifted adolescents exhibit unusual neurocognitive features in the activation of task-related brain regions. Hemispheric information interaction, functional reorganization of networks, and utilization of task-related brain regions are beneficial to rapid and efficient task processing. Based on Granger causality channel selection, the transfer entropy (TE) value between effective channels was computed, and the information flow patterns in the directed functional brain networks derived from electroencephalography (EEG) data during deductive reasoning tasks were explored. We evaluated the workspace configuration patterns of the brain network and the global integration characteristics of separated brain regions using node strength, motif, directed clustering coefficient and characteristic path length in the brain networks of mathematically gifted adolescents with effective connectivity. The empirical results demonstrated that a more integrated functional network at the global level and a more efficient clique at the local level support a pattern of workspace configuration in the mathematically gifted brain that is more conducive to task-related information processing.

A General Cognitive Ability Factor for the UK Biobank

UK Biobank participants do not have a high-quality measure of intelligence or polygenic scores (PGSs) of intelligence to simultaneously examine the genetic and neural underpinnings of intelligence. We created a standardized measure of general intelligence (g factor) relative to the UK population and estimated its quality. After running a GWAS of g on UK Biobank participants with a g factor of good quality and without neuroimaging data (N = 187,288), we derived a g PGS for UK Biobank participants with neuroimaging data. For individuals with at least one cognitive test, the g factor from eight cognitive tests (N = 501,650) explained 29% of the variance in cognitive test performance. The PGS for British individuals with neuroimaging data (N = 27,174) explained 7.6% of the variance in g. We provided high-quality g factor estimates for most UK Biobank participants and g factor PGSs for UK Biobank participants with neuroimaging data.

Learning to read may help promote attention by increasing the volume of the left middle frontal gyrus and enhancing its connectivity to the ventral attention network

Attention and reading are essential skills for successful schooling and in adult life. While previous studies have documented that attention development supports reading acquisition, whether and how learning to read may improve attention among school-age children and the brain structural and functional development that may be involved remain unknown. In this prospective longitudinal study, we examined bidirectional and longitudinal predictions between attention and reading development and the neural mediators of attention and reading development among school-age children using cross-lagged panel modeling. The results showed that better baseline reading performance significantly predicted better attention performance one year later after controlling for baseline attention performance. In contrast, after controlling for baseline reading performance, attention did not significantly predict reading performance one year later, while more attention problems also significantly predicted worse reading performance. Both the increasing gray matter volume of the left middle frontal gyrus and the increasing connectivity between the left middle frontal gyrus and the ventral attention network mediated the above significant longitudinal predictions. This study, directly revealed that reading skills may predict the development of important cognitive functions, such as attention, in school-age children. Therefore, learning to read is not only a challenge for school-age children but is also an important way to optimize attention and brain development.

Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

(Lack of) neural efficiency related to general giftedness and mathematical excellence: An EEG study

Previous studies on intelligence have demonstrated that higher abilities are associated with lower brain activation, indicating a higher neural efficiency. In other words, more able individuals use fewer brain resources. However, it is unclear whether the neural efficiency phenomenon also appears for mathematical performance, which is influenced by both domain-general giftedness and domain-specific competencies. Therefore, this study examined the effects of general giftedness (G) and excellence in mathematics (EM) on performance and brain activation while solving learning-based mathematical tasks that required translation from graphical to symbolic representations of functions. Overall, 118 high school students (aged 16-18) participated in the present study and were divided according to G and EM using a 2 × 2 study design. Participants worked on a function task requiring translation between symbolic and graphical representations of functions. Analyses of the behavioral data revealed positive effects of both G and EM on the accuracy of solutions and an interaction effect of both factors on reaction times, reflecting a positive effect of EM only among the gifted individuals. EEG analyses focused on oscillatory activity in the theta and alpha frequency bands and showed a significant effect of EM in the upper alpha band (10-12 Hz) event-related desynchronization (ERD) for both graphical and symbolic representations. Specifically, higher (compared to lower) EM was associated with a larger alpha ERD, indicating a higher level of brain activity. This stands in contrast with the neural efficiency phenomenon. These findings suggest that the neural efficiency phenomenon cannot be generalized to higher-order mathematical demands in high-performing individuals. Several explanations for this limitation are offered.

Robust associations between white matter microstructure and general intelligence

Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.

Genome-wide association study of school grades identifies genetic overlap between language ability, psychopathology and creativity

Cognitive functions of individuals with psychiatric disorders differ from that of the general population. Such cognitive differences often manifest early in life as differential school performance and have a strong genetic basis. Here we measured genetic predictors of school performance in 30,982 individuals in English, Danish and mathematics via a genome-wide association study (GWAS) and studied their relationship with risk for six major psychiatric disorders. When decomposing the school performance into math and language-specific performances, we observed phenotypically and genetically a strong negative correlation between math performance and risk for most psychiatric disorders. But language performance correlated positively with risk for certain disorders, especially schizophrenia, which we replicate in an independent sample (n = 4547). We also found that the genetic variants relating to increased risk for schizophrenia and better language performance are overrepresented in individuals involved in creative professions (n = 2953) compared to the general population (n = 164,622). The findings together suggest that language ability, creativity and psychopathology might stem from overlapping genetic roots.

Individual consistency in the learning abilities of honey bees: cognitive specialization within sensory and reinforcement modalities

The question of whether individuals perform consistently across a variety of cognitive tasks is relevant for studies of comparative cognition. The honey bee (Apis mellifera) is an appropriate model to study cognitive consistency as its learning can be studied in multiple elemental and non-elemental learning tasks. We took advantage of this possibility and studied if the ability of honey bees to learn a simple discrimination correlates with their ability to solve two tasks of higher complexity, reversal learning and negative patterning. We performed four experiments in which we varied the sensory modality of the stimuli (visual or olfactory) and the type (Pavlovian or operant) and complexity (elemental or non-elemental) of conditioning to examine if stable correlated performances could be observed across experiments. Across all experiments, an individual's proficiency to learn the simple discrimination task was positively and significantly correlated with performance in both reversal learning and negative patterning, while the performances in reversal learning and negative patterning were positively, yet not significantly correlated. These results suggest that correlated performances across learning paradigms represent a distinct cognitive characteristic of bees. Further research is necessary to examine if individual cognitive consistency can be found in other insect species as a common characteristic of insect brains.

Multifactorial structure of cognitive assessment tests in the UK Biobank: A combined exploratory factor and structural equation modeling analyses

Introduction

The UK Biobank cognitive assessment data has been a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population. Given the diverse nature of this data, researchers use different approaches - from the use of a single test to composing the general intelligence score, g, across the tests. We argue that both approaches are suboptimal - one being too specific and the other one too general - and suggest a novel multifactorial solution to represent cognitive abilities.

Methods

Using a combined Exploratory Factor (EFA) and Exploratory Structural Equation Modeling Analyses (ESEM) we developed a three-factor model to characterize an underlying structure of nine cognitive tests selected from the UK Biobank using a Cattell-Horn-Carroll framework. We first estimated a series of probable factor solutions using the maximum likelihood method of extraction. The best solution for the EFA-defined factor structure was then tested using the ESEM approach with the aim of confirming or disconfirming the decisions made.

Results

We determined that a three-factor model fits the UK Biobank cognitive assessment data best. Two of the three factors can be assigned to fluid reasoning (Gf) with a clear distinction between visuospatial reasoning and verbal-analytical reasoning. The third factor was identified as a processing speed (Gs) factor.

Discussion

This study characterizes cognitive assessment data in the UK Biobank and delivers an alternative view on its underlying structure, suggesting that the three factor model provides a more granular solution than g that can further be applied to study different facets of cognitive functioning in relation to health outcomes and to further progress examination of its biological underpinnings.

Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter

In the past 20 years, white matter (WM) microstructure has been studied predominantly using diffusion tensor imaging (DTI). Decreases in fractional anisotropy (FA) and increases in mean (MD) and radial diffusivity (RD) have been consistently reported in healthy aging and neurodegenerative diseases. To date, DTI parameters have been studied individually (e.g., only FA) and separately (i.e., without using the joint information across them). This approach gives limited insights into WM pathology, increases the number of multiple comparisons, and yields inconsistent correlations with cognition. To take full advantage of the information in a DTI dataset, we present the first application of symmetric fusion to study healthy aging WM. This data-driven approach allows simultaneous examination of age differences in all four DTI parameters. We used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) in cognitively healthy adults (age 20-33, n = 51 and age 60-79, n = 170). Four-way mCCA + jICA yielded one high-stability modality-shared component with co-variant patterns of age differences in RD and AD in the corpus callosum, internal capsule, and prefrontal WM. The mixing coefficients (or loading parameters) showed correlations with processing speed and fluid abilities that were not detected by unimodal analyses. In sum, mCCA + jICA allows data-driven identification of cognitively relevant multimodal components within the WM. The presented method should be further extended to clinical samples and other MR techniques (e.g., myelin water imaging) to test the potential of mCCA+jICA to discriminate between different WM disease etiologies and improve the diagnostic classification of WM diseases.

A quantified comparison of cortical atlases on the basis of trait morphometricity

BACKGROUND

Many different brain atlases exist that subdivide the human cortex into dozens or hundreds of regions-of-interest (ROIs). Inconsistency across studies using one or another cortical atlas may contribute to the replication crisis across the neurosciences.

METHODS

Here, we provide a quantitative comparison between seven popular cortical atlases (Yeo, Desikan-Killiany, Destrieux, Jülich-Brain, Gordon, Glasser, Schaefer) and vertex-wise measures (thickness, surface area, and volume), to determine which parcellation retains the most information in the analysis of behavioural traits (incl. age, sex, body mass index, and cognitive ability) in the UK Biobank sample (N∼40,000). We use linear mixed models to compare whole-brain morphometricity; the proportion of trait variance accounted for when using a given atlas.

RESULTS

Commonly-used atlases resulted in a considerable loss of information compared to vertex-wise representations of cortical structure. Morphometricity increased linearly as a function of the log-number of ROIs included in an atlas, indicating atlas-based analyses miss many true associations and yield limited prediction accuracy. Likelihood ratio tests revealed that low-dimensional atlases accounted for unique trait variance rather than variance common between atlases, suggesting that previous studies likely returned atlas-specific findings. Finally, we found that the commonly-used atlases yielded brain-behaviour associations on par with those obtained with random parcellations, where specific region boundaries were randomly generated.

DISCUSSION

Our findings motivate future structural neuroimaging studies to favour vertex-wise cortical representations over coarser atlases, or to consider repeating analyses across multiple atlases, should the use of low-dimensional atlases be necessary. The insights uncovered here imply that cortical atlas choices likely contribute to the lack of reproducibility in ROI-based studies.

Brain volumes, thicknesses, and surface areas as mediators of genetic factors and childhood adversity on intelligence

Although genetic and environmental factors influence general intelligence (g-factor), few studies examined the neuroanatomical measures mediating environmental and genetic effects on intelligence. Here, we investigate the brain volumes, cortical mean thicknesses, and cortical surface areas mediating the effects of the g-factor polygenic score (gPGS) and childhood adversity on the g-factor in the UK Biobank. We first examined the global and regional brain measures that contribute to the g-factor. Most regions contributed to the g-factor through global brain size. Parieto-frontal integration theory (P-FIT) regions were not more associated with the g-factor than non-PFIT regions. After adjusting for global brain size and regional associations, only a few regions predicted intelligence and were included in the mediation analyses. We conducted mediation analyses on global measures, regional volumes, mean thicknesses, and surface areas, separately. Total brain volume mediated 7.04% of the gPGS' effect on the g-factor and 2.50% of childhood adversity's effect on the g-factor. In comparison, the fraction of the gPGS and childhood adversity's effects mediated by individual regional volumes, surfaces, and mean thicknesses was 10-15 times smaller. Therefore, genetic and environmental effects on intelligence may be mediated to a larger extent by other brain properties.

Evolution of cortical neurons supporting human cognition

Human cognitive abilities are generally thought to arise from cortical expansion over the course of human brain evolution. In addition to increased neuron numbers, this cortical expansion might be driven by adaptations in the properties of single neurons and their local circuits. We review recent findings on the distinct structural, functional, and transcriptomic features of human cortical neurons and their organization in cortical microstructure. We focus on the supragranular cortical layers, which showed the most prominent expansion during human brain evolution, and the properties of their principal cells: pyramidal neurons. We argue that the evolutionary adaptations in neuronal features that accompany the expansion of the human cortex partially underlie interindividual variability in human cognitive abilities.