Mendelian Randomization Estimates the Effects of Plasma and Cerebrospinal Fluid Proteins on Intelligence, Fluid Intelligence Score, and Cognitive Performance.

Observational studies have revealed associations between levels of plasma and cerebrospinal fluid (CSF) proteins and cognition-related traits. However, these associations may be influenced by confounding factors inherent in observational research. This study aims to identify plasma and CSF proteins associated with intelligence, fluid intelligence score, and cognitive performance through the application of Mendelian randomization (MR). Proteomic quantitative trait locus (pQTL) data for plasma and CSF proteins were sourced from existing genome-wide association study (GWAS). Intelligence, fluid intelligence score, and cognitive performance GWAS summary statistics provided comprehensive data for two-sample MR analysis. Extensive sensitivity analyses, including Steiger testing, reverse MR analysis, and Bayesian co-localization, were conducted to validate associations and identify shared genetic variants. Phenotype scanning explored potential pleiotropic effects. MR analysis identified several proteins in plasma and CSF significantly associated with intelligence, fluid intelligence scores, and cognitive performance. For intelligence, negatively associated proteins in plasma include endoplasmic reticulum aminopeptidase 2 (ERAP2) and secretogranin III (SCG3), while positively associated proteins are myeloperoxidase (MPO), signal regulatory protein alpha (SIRPA), regulator of microtubule dynamics 1 (RMDN1), and endoplasmic reticulum lectin 1 (ERLEC1). In CSF, C1-esterase inhibitor and carboxypeptidase E (CBPE) both exhibited positive associations with intelligence. For fluid intelligence scores, negatively associated proteins in plasma are copine 1 (CPNE1) and SCG3, while positively associated proteins are nudix hydrolase 12 (NUDT12) and RMDN1. In CSF, Macrophage Stimulating Protein (MSP) demonstrated a significant negative impact. For cognitive performance, negatively associated proteins in plasma include ERAP2, tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1), and SCG3, while positively associated proteins are NUDT12, RMDN1, ERLEC1, and ectonucleotide pyrophosphatase/phosphodiesterase family member 5 (ENPP5). In CSF, C1-esterase inhibitor was positively associated, while MSP and soluble tyrosine kinase with immunoglobulin-like and EGF-like domains 1(sTie-1) showed a negative association. Bayesian co-localization analysis revealed significant genetic overlaps between SIRPA, RMDN1, and ERLEC1 in plasma with intelligence; NUDT12 and SCG3 in plasma with fluid intelligence scores; and TIE1, NUDT12, RMDN1, ERLEC1, and ENPP5 in plasma with cognitive performance. Additionally, significant co-localization was identified between C1-esterase inhibitor and CBPE in CSF with intelligence, as well as between C1-esterase inhibitor and sTie-1 in CSF with cognitive performance. Reverse causality analysis confirmed the causal direction from proteins to cognitive traits. This study identifies specific plasma and CSF proteins that significantly impact intelligence, fluid intelligence scores, and cognitive performance. These proteins could serve as biomarkers and targets for future research and therapeutic interventions aimed at sustaining cognitive abilities and reducing impairment risks.

Bridging Experimental Neuroscience and Clinical Neuropsychology: Fluid Intelligence in Frontal Lobe Assessments.

This viewpoint explores the gap between theoretical frameworks in experimental neuroscience and clinical neuropsychology. It highlights how John Duncan's theory of the Multiple Demand (MD) system, which links the frontal lobe to fluid intelligence (g), helps explain general performance on classical executive tests. However, it also discusses how traditional scores often fail to capture the complexity of behaviours associated with frontal lobe damage, and we suggest that developing improved scoring methods could be useful for integrating experimental and clinical neuropsychology insights.

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.

The near and far transfer effects of computerized working memory training in typically developing preschool children: Evidence from event-related potentials.

Working memory (WM) refers to the ability to actively maintain and process information needed to complete complex tasks such as comprehension, learning, and reasoning. Recent studies have examined the efficacy of computerized working memory training (WMT) in improving cognitive functions in general and WM in particular, with mixed results. Thus, to what extent can WMT produce near and far transfer effects to cognitive function is currently unclear. This study investigated the transfer effects of a computerized WMT for preschool children and also examined the possible neural correlates using the event-related potential (ERP) technique. A total of 50 Chinese preschoolers (64.44 ± 7.76 months old; 24 girls) received 4-week training during school hours. Compared with those in the active control group, children in the training group showed better gains in behavioral performance in the WM task and significantly more changes in ERP markers of the WM and inhibitory control tasks (near transfer effect). However, no evidence was found for transfer to fluid intelligence (far transfer effect). These findings suggest that WMT is capable of enhancing cognitive functioning in preschool children, and as such this work has important implications for educational practice and it may help to design and refine cognitive interventions for typically developing children and those with WM problems or other cognitive deficits (e.g., children with attention-deficit/hyperactivity disorder).

Reorganization of structural connectivity in the brain supports preservation of cognitive ability in healthy aging.

The global population is aging rapidly, and a research question of critical importance is why some older adults suffer tremendous cognitive decline while others are mostly spared. Past aging research has shown that older adults with spared cognitive ability have better local short-range information processing while global long-range processing is less efficient. We took this research a step further to investigate whether the underlying structural connections, measured in vivo using diffusion magnetic resonance imaging (dMRI), show a similar shift to support cognitive ability. We analyzed the structural connectivity streamline probability (representing the probability of connection between regions) and nodal efficiency and local efficiency regional graph theory metrics to determine whether age and cognitive ability are related to structural network differences. We found that the relationship between structural connectivity and cognitive ability with age was nuanced, with some differences with age that were associated with poorer cognitive outcomes, but other reorganizations that were associated with spared cognitive ability. These positive changes included strengthened local intrahemispheric connectivity and increased nodal efficiency of the ventral occipital-temporal stream, nucleus accumbens, and hippocampus for older adults, and widespread local efficiency primarily for middle-aged individuals.

We utilized network neuroscience methods to investigate why some older adults suffer tremendous cognitive decline while others are mostly spared. Past functional research found that older adults with spared cognitive ability have better local short-range information processing while global long-range processing is less efficient. We took this research a step further to investigate whether structural connectivity reorganizes to preserve cognitive ability. We analyzed age and fluid intelligence as a function of structural connectivity and regional graph theory measures using partial least squares. Some differences with age were associated with poorer cognitive outcomes, but other reorganizations spared cognitive ability. Beneficial reorganizations included strengthened local intrahemispheric connectivity and increased nodal efficiency of focal regions for older adults, as well as widespread increased local efficiency for middle-aged individuals.

Age-related changes of node degree in the multiple-demand network predict fluid intelligence.

Fluid intelligence is an individual's innate ability to cope with complex situations and is gradually reduced across adults aging. The realization of fluid intelligence requires the simultaneous activity of multiple brain regions and depends on the structural connection of distributed brain regions. Uncovering the structural features of brain connections associated with fluid intelligence decline will provide reference for the development of intervention and treatment programs for cognitive decline. Using structural magnetic resonance imaging data of 454 healthy participants (18-87 years) from the Cam-CAN dataset, we constructed structural similarity network for each participant and calculated the node degree. Spearman correlation analysis showed that age was positively correlated with degree centrality in the cingulate cortex, left insula and subcortical regions, while negatively correlated with that in the orbito-frontal cortex, right middle temporal and precentral regions. Partial least squares (PLS) regression showed that the first PLS components explained 32 % (second PLS component: 20 %, p perm < 0.001) of the variance in fluid intelligence. Additionally, the degree centralities of anterior insula, supplementary motor area, prefrontal, orbito-frontal and anterior cingulate cortices, which are critical nodes of the multiple-demand network (MDN), were linked to fluid intelligence. Increased degree centrality in anterior cingulate cortex and left insula partially mediated age-related decline in fluid intelligence. Collectively, these findings suggest that the structural stability of MDN might contribute to the maintenance of fluid intelligence.

Large-Scale Item-Level Analysis of the Figural Matrices Test in the Norwegian Armed Forces: Examining Measurement Precision and Sex Bias.

Figural matrices tests are common in intelligence research and have been used to draw conclusions regarding secular changes in intelligence. However, their measurement properties have seldom been evaluated with large samples that include both sexes. Using data from the Norwegian Armed Forces, we study the measurement properties of a test used for selection in military recruitment. Item-level data were available from 113,671 Norwegian adolescents (32% female) tested between the years 2011 and 2017. Utilizing item response theory (IRT), we characterize the measurement properties of the test in terms of difficulty, discrimination, precision, and measurement invariance between males and females. We estimate sex differences in the mean and variance of the latent variable and evaluate the impact of violations to measurement invariance on the estimated distribution parameters. The results show that unidimensional IRT models fit well in all groups and years. There is little difference in precision and test difficulty between males and females, with precision that is generally poor on the upper part of the scale. In the sample, male latent proficiency is estimated to be slightly higher on average, with higher variance. Adjusting for measurement invariance generally reduces the sex differences but does not eliminate them. We conclude that previous studies using the Norwegian GMA data must be interpreted with more caution but that the test should measure males and females equally fairly.

Age differences in BOLD modulation to task difficulty as a function of amyloid burden.

Effective cognitive performance often requires the allocation of additional neural resources (i.e. blood-oxygen-level-dependent [BOLD] activation) as task demands increase, and this demand-related modulation is affected by amyloid-beta deposition and normal aging. The present study investigated these complex relationships between amyloid, modulation, and cognitive function (i.e. fluid ability). Participants from the Dallas Lifespan Brain Study (DLBS, n = 252, ages 50-89) completed a semantic judgment task during functional magnetic resonance imaging (fMRI) where the judgments differed in classification difficulty. Amyloid burden was assessed via positron emission tomography (PET) using 18F-florbetapir. A quadratic relationship between amyloid standardized value uptake ratios (SUVRs) and BOLD modulation was observed such that modulation was weaker in those with moderately elevated SUVRs (e.g. just reaching amyloid-positivity), whereas those with very high SUVRs (e.g. SUVR > 1.5) showed strong modulation. Greater modulation was related to better fluid ability, and this relationship was strongest in younger participants and those with lower amyloid burden. These results support the theory that effective demand-related modulation contributes to healthy cognitive aging, especially in the transition from middle age to older adulthood, whereas high modulation may be dysfunctional in those with substantial amyloid deposition.

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.

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.

Evidence for separate backward recall and n-back working memory factors: a large-scale latent variable analysis.

Multiple studies have explored the factor structure of working memory (WM) tasks, yet few have done so controlling for both the domain and category of the memory items in a single study. In the current pre-registered study, we conducted a large-scale latent variable analysis using variant forms of n-back and backward recall tasks to test whether they measured a single underlying construct, or were distinguished by stimuli-, domain-, or paradigm-specific factors. Exploratory analyses investigated how the resulting WM factor(s) were linked to fluid intelligence. Participants (N = 703) completed a fluid reasoning test and multiple n-back and backward recall tasks containing memoranda that varied across (spatial or verbal material) and within (verbal digits or letters) domain, allowing the variance specific to task content and paradigm to be assessed. Two distinct but related backward recall and n-back constructs best captured the data, in comparison to other plausible model constructions (single WM factor, two-factor domain, and three-factor materials models). Common variance associated with WM was a stronger predictor of fluid reasoning than a residual n-back factor, but the backward recall factor predicted fluid reasoning as strongly as the common WM factor. These data emphasise the distinctiveness between backward recall and n-back tasks.

Prediction of Adolescents' Fluid Intelligence Scores based on Deep Learning with Reconstruction Regularization.

Objective: The aim of this study was to develop a predictive model for uncorrected/actual fluid intelligence scores in 9-10 year old children using magnetic resonance T1-weighted imaging. Explore the predictive performance of an autoencoder model based on reconstruction regularization for fluid intelligence in adolescents. Methods: We collected actual fluid intelligence scores and T1-weighted MRIs of 11,534 adolescents who completed baseline tasks from ABCD Data Release 3.0. A total of 148 ROIs were selected and 604 features were proposed by FreeSurfer segmentation. The training and testing sets were divided in a ratio of 7:3. To predict fluid intelligence scores, we used AE, MLP and classic machine learning models, and compared their performance on the test set. In addition, we explored their performance across gender subpopulations. Moreover, we evaluated the importance of features using the SHapley Additive Explain method. Results: The proposed model achieves optimal performance on the test set for predicting actual fluid intelligence scores (PCC = 0.209 ± 0.02, MSE = 105.212 ± 2.53). Results show that autoencoders with refactoring regularization are significantly more effective than MLPs and classical machine learning models. In addition, all models performed better on female adolescents than on male adolescents. Further analysis of relevant characteristics in different populations revealed that this may be related to gender differences in underlying fluid intelligence mechanisms. Conclusions: We construct a weak but stable correlation between brain structural features and raw fluid intelligence using autoencoders. Future research may need to explore ensemble regression strategies utilizing multiple machine learning algorithms on multimodal data in order to improve the predictive performance of fluid intelligence based on neuroimaging features.

Harnessing the frontal aslant tract's structure to assess its involvement in cognitive functions: new insights from 7-T diffusion imaging.

The first therapeutical goal followed by neurooncological surgeons dealing with prefrontal gliomas is attempting supramarginal tumor resection preserving relevant neurological function. Therefore, advanced knowledge of the frontal aslant tract (FAT) functional neuroanatomy in high-order cognitive domains beyond language and speech processing would help refine neurosurgeries, predicting possible relevant cognitive adverse events and maximizing the surgical efficacy. To this aim we performed the recently developed correlational tractography analyses to evaluate the possible relationship between FAT's microstructural properties and cognitive functions in 27 healthy subjects having ultra-high-field (7-Tesla) diffusion MRI. We independently assessed FAT segments innervating the dorsolateral prefrontal cortices (dlPFC-FAT) and the supplementary motor area (SMA-FAT). FAT microstructural robustness, measured by the tract's quantitative anisotropy (QA), was associated with a better performance in episodic memory, visuospatial orientation, cognitive processing speed and fluid intelligence but not sustained selective attention tests. Overall, the percentual tract volume showing an association between QA-index and improved cognitive scores (pQACV) was higher in the SMA-FAT compared to the dlPFC-FAT segment. This effect was right-lateralized for verbal episodic memory and fluid intelligence and bilateralized for visuospatial orientation and cognitive processing speed. Our results provide novel evidence for a functional specialization of the FAT beyond the known in language and speech processing, particularly its involvement in several higher-order cognitive domains. In light of these findings, further research should be encouraged to focus on neurocognitive deficits and their impact on patient outcomes after FAT damage, especially in the context of glioma surgery.

The factorial structure of executive functions in preschool and elementary school children and relations with intelligence.

The timing of structural changes in executive functions (EFs) across development is a matter of controversy; whereas some studies suggest a uniform structure of EFs in early childhood, findings in middle and late childhood are mixed. There are results indicating uniformity of EFs as well as several studies suggesting multidimensionality of the construct. In addition, studies demonstrate an age-related differentiation of the relation between EFs and intelligence. We conducted a comparative analysis of the EF structure and relations with fluid intelligence in two distinct age groups. A sample of n = 145 preschool children (5.2-6.7 years of age) and n = 109 elementary school children (8.8-11.8 years) completed measures of working memory, inhibition, cognitive flexibility, and fluid intelligence. Confirmatory factor analysis (CFA) revealed that a single-factor model best represented performance on EF tasks in both preschool and elementary school children. Multi-group CFA indicated equivalent and strong relations between EFs and intelligence across both age groups (r = .64 in preschool and elementary school children). Our results confirm that EFs are significantly related to fluid intelligence but might not underlie a uniform pattern of successive differentiation into multiple EF components in childhood. We discuss how methodological artifacts such as simultaneous interference might have contributed to previous findings on differentiation in middle and late childhood.

Regional brain structure mediates the association between sleep quality and intellectual abilities: the moderating role of socioeconomic status.

This study aims to reveal the association between sleep quality and crystallized intelligence (Gc), fluid intelligence (Gf), and the underlying brain structural basis. Using the data from the Human Connectome Project (N = 1087), we performed mediation analysis to explore whether regional brain structure related to sleep quality mediate the association between sleep quality and intellectual abilities, and further examined whether socioeconomic status (i.e., income and education level) moderate the mediation effect. Results showed that poorer sleep quality was associated with lower Gc rather than Gf, and worse sleep quality was associated with smaller volume and surface area in temporal lobe, including inferior temporal gyrus and middle temporal gyrus. Notably, temporal lobe structures mediated the association between sleep quality and Gc rather than Gf. Furthermore, socioeconomic status (i.e., income and education level) moderated the mediating effect, showing low socioeconomic status has a more significant mediating effect with stronger association between sleep quality and Gc as well as stronger association between temporal lobe structure and Gc in low socioeconomic status group. These findings suggest that individuals with higher socioeconomic status are less susceptible to the effect of sleep quality on Gc.

The causal effects of intelligence and fluid intelligence on Parkinson's disease: a Mendelian randomization study.

Background: Parkinson's disease (PD) is a chronic neurodegenerative disease that affects the central nervous system, primarily the motor nervous system, and occurs most often in older adults. A large number of studies have shown that high intelligence leads to an increased risk of PD. However, whether there is a causal relationship between intelligence on PD has not yet been reported. Methods: In this study, Mendelian randomization (MR) analysis was performed with intelligence (ebi-a-GCST006250) and fluid intelligence score (ukb-b-5238) as exposure factors and PD (ieu-b-7) as an outcome, which the datasets were mined from the IEU OpenGWAS database. MR analysis was performed through 3 methods [MR Egger, weighted median, inverse variance weighted (IVW)], of which IVW was the primary method. In addition, the reliability of the results of the MR analysis was assessed via the heterogeneity test, the horizontal polytropy test, and Leave-One-Out (LOO). Finally, based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, the genes corresponding to intelligence and fluid intelligence score related to SNPs were enriched for functional features and pathways. Results: The results of MR analysis suggested that elevated intelligence indicators can increase the risk of PD [p = 0.015, Odd Ratio (OR) = 1.316]. Meanwhile, fluid intelligence score was causally associated with the PD (p = 0.035), which was a risk factor (OR = 1.142). The reliability of the results of MR analysis was demonstrated by sensitivity analysis. Finally, the results of GO enrichment analysis for 87 genes corresponding to intelligence related SNPs mainly included regulation of synapse organization, developmental cell growth, etc. These genes were enriched in the synaptic vessel cycle, polycomb expressive complex in KEGG. Similarly, 44 genes corresponding to SNPs associated with fluid intelligence score were used for enrichment analysis. Based on the GO database, these genes were mainly enriched in regulation of developmental growth, negative regulation of neuron projection development, etc. In KEGG, 44 genes corresponding to SNPs associated with fluid intelligence score were enriched in signaling pathways including Alzheimer's disease, the cellular senescence, etc. Conclusion: The causal relationships between intelligence and fluid intelligence scores, and PD were demonstrated through MR analysis, providing an important reference and evidence for the study of PD.

Subjective Cognitive Impairment Can Be Detected from the Decline of Complex Cognition: Findings from the Examination of Remedes 4 Alzheimer's (R4Alz) Structural Validity.

R4Alz is utilized for the early detection of minor neurocognitive disorders. It was designed to assess three main dimensions of cognitive-control abilities: working-memory capacity, attentional control, and executive functioning. OBJECTIVES: To reveal the cognitive-control dimensions that can differentiate between adults and older adults with healthy cognition, people with subjective cognitive impairment, and people diagnosed with mild cognitive impairment by examining the factorial structure of the R4Alz tool. METHODS: The study comprised 404 participants: (a) healthy adults (n = 192), (b) healthy older adults (n = 29), (c) people with SCI (n = 74), and (d) people diagnosed with MCI (n = 109). The R4Alz battery was administered to all participants, including tests that assess short-term memory storage, information processing, information updating in working memory, and selective, sustained and divided attention), task/rule-switching, inhibitory control, and cognitive flexibility. RESULTS: A two-factorial structural model was confirmed for R4Alz, with the first factor representing "fluid intelligence (FI)" and the second factor reflecting "executive functions (EF)". Both FI and EFs discriminate among all groups. CONCLUSIONS: The R4Alz battery presents sound construct validity, evaluating abilities in FI and EF. Both abilities can differentiate very early cognitive impairment (SCI) from healthy cognitive aging and MCI.

Global brain connectivity: Test-retest stability and association with biological and neurocognitive variables.

BACKGROUND: Global brain connectivity (GBC) enables measuring brain regions' functional connectivity strength at rest by computing the average correlation between each brain voxel's time-series and that of all other voxels. NEW METHOD: We used resting-state fMRI (rs-fMRI) data of young adult participants from the Human Connectome Project (HCP) dataset to explore the test-retest stability of GBC, the brain regions with higher or lower GBC, as well as the associations of this measure with age, sex, and fluid intelligence. GBC was computed by considering separately the positive and negative correlation coefficients (positive GBC and negative GBC). RESULTS: Test-retest stability was higher for positive compared to negative GBC. Areas with higher GBC were located in the default mode network, insula, and visual areas, while regions with lower GBC were in subcortical regions, temporal cortex, and cerebellum. Higher age was related to global reduction of positive GBC. Males displayed higher positive GBC in the whole brain. Fluid intelligence was associated to increased positive GBC in fronto-parietal, occipital and temporal regions. COMPARISON WITH EXISTING METHOD: Compared to previous works, this study adopted a larger sample size and tested GBC stability using data from different rs-fMRI sessions. Moreover, these associations were examined by testing positive and negative GBC separately. CONCLUSIONS: Lower stability for negative compared to positive GBC suggests that negative correlations may reflect less stable couplings between brain regions. Our findings indicate a greater importance of positive compared to negative GBC for the associations of functional connectivity strength with biological and neurocognitive variables.

Baseline Pupil Size Seems Unrelated to Fluid Intelligence, Working Memory Capacity, and Attentional Control.

Over the past few years, several studies have explored the relationship between resting-state baseline pupil size and cognitive abilities, including fluid intelligence, working memory capacity, and attentional control. However, the results have been inconsistent. Here we present the findings from two experiments designed to replicate and expand previous research, with the aim of clarifying previous mixed findings. In both experiments, we measured baseline pupil size while participants were not engaged in any tasks, and assessed fluid intelligence using a matrix task. In one experiment we also measured working memory capacity (letter-number-sequencing task) and attentional control (attentional-capture task). We controlled for several personal and demographic variables known to influence pupil size, such as age and nicotine consumption. Our analyses revealed no relationship between resting-state pupil size (average or variability) and any of the measured constructs, neither before nor after controlling for confounding variables. Taken together, our results suggest that any relationship between resting-state pupil size and cognitive abilities is likely to be weak or non-existent.

Associations between Fluid Intelligence and Physical Fitness in School Children.

Previous research has highlighted that active lifestyles that contribute to improved physical fitness are positively related to cognitive functioning in children and adolescents. Specifically, the increase in physical condition at school age is considered relevant because it is related to better cognitive ability and greater academic performance. Thus, the aim of this study was to analyze the relationships between explosive strength, speed-agility, and fluid reasoning in schoolchildren. To achieve this objective, an associative, comparative, and predictive design was used in this research. A total of 129 children participated in this study (age: M = 9.48; SD = 0.99). To assess fluid reasoning, the Raven test's Standard Progressive Matrices Subtest and the Wechsler Intelligence Scale for Children (WISC-V) were used. To assess physical fitness, the speed-agility test and the horizontal jump test (ALPHA-fitness battery tests), as well as the ball throw test (2 kg), were used. The results showed that the speed-agility test significantly predicted WISC-V Fluid Reasoning Index scores, and the medicine ball toss test significantly predicted Raven test scores. The results obtained highlight the associations between physical condition at these ages and fluid intelligence. This suggests that promoting active lifestyles that improve physical fitness could have a positive impact on children's cognitive health.