Individual Differences In Fluid Intelligence Research Articles

Neural correlates of intelligence: ERP Components of temporary storage predict fluid intelligence over and above those of executive functions.

Previous research has revealed that individuals with different levels of intelligence exhibit distinct patterns of event-related potentials (ERPs) related to executive functions and temporary storage. However, there is a lack of studies investigating the relative contributions of these ERPs in predicting individual differences in fluid intelligence. This study aims to examine the extent to which ERPs associated with executive functions and temporary storage can predict individual differences in fluid intelligence. Special attention is given to determining whether electrophysiological activities of temporary storage can predict fluid intelligence after accounting for executive functions, and vice versa. Both executive attention and temporary storage were measured by two experimental tasks, while electroencephalographic data were collected simultaneously. Fluid intelligence was assessed by two established tests. To address previous inconsistencies due to small sample sizes, a relatively large sample of young adults (N = 136) was recruited. The results revealed that participants with lower fluid intelligence displayed larger P3 amplitudes in the executive functions and temporary storage tasks compared to those with higher fluid intelligence. Additionally, the amplitudes of frontal and parietal P3s elicited by both executive functions and temporary storage significantly predicted fluid intelligence. Interestingly, the frontal and parietal P3s associated with temporary storage predicted fluid intelligence beyond the contributions of executive functions, supporting the storage account of individual differences in fluid intelligence. This study provides an original and fresh understanding of how executive functions and temporary storage contribute to fluid intelligence, offering new insights into the neurocognitive mechanisms underlying intelligence.

Baseline pupil diameter does not correlate with fluid intelligence.

There has been debate regarding the correlation between baseline/resting state measures of pupil diameter and cognitive abilities such as working memory capacity and fluid intelligence. A positive correlation between baseline pupil diameter and cognitive ability has been cited as evidence for a role of the locus coeruleus-norepinephrine (LC-NE) and its functional connection with cortical networks as a reason for individual differences in fluid intelligence (Tsukahara & Engle, Proceedings of the National Academy of Sciences, 118(46), e2110630118, 2021a). Several recent attempts to replicate this correlation have failed. The current studies make another attempt and find substantial evidence against a positive correlation between pupil diameter and intelligence. Given the data from the current studies in combination with other recent failures to replicate, we conclude that individual differences in baseline pupil diameter should not be used as evidence for a role of the LC-NE system in goal-directed cognitive activity.

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects.

Brain aging is a complex process that requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization, and vascular dynamics. However, most neuroimaging studies of aging have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in aging. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging (MRI) of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18-88 years (main dataset n=215 and secondary dataset n=433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns. Split-sample (n=108/107) and out-of-sample (n=433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with age-related and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy aging.

Semantic memory and creativity: the costs and benefits of semantic memory structure in generating original ideas

Despite its theoretical importance, little is known about how semantic memory structure facilitates and constrains creative idea generation. We examine whether the semantic richness of a concept has both benefits and costs to creative idea generation. Specifically, we tested whether cue set size—an index of semantic richness reflecting the average number of elements associated with a given concept—impacts the quantity (fluency) and quality (originality) of responses generated during the Alternate Uses Task (AUT). Across four studies, we show that low-association, sparse, AUT cues benefit originality at the cost of fluency compared to high-association, rich, AUT cues. Furthermore, we found an interaction with individual differences in fluid intelligence in the low-association AUT cues, suggesting that constraints of sparse semantic knowledge can be overcome with top-down intervention. Our findings indicate that semantic richness differentially impacts the quality and quantity of generated ideas, and that cognitive control processes can facilitate idea production when conceptual knowledge is limited.

Do your eye movements reveal your performance on an IQ test? A study linking eye movements and socio-demographic information to fluid intelligence.

Understanding the main factors contributing to individual differences in fluid intelligence is one of the main challenges of psychology. A vast body of research has evolved from the theoretical framework put forward by Cattell, who developed the Culture-Fair IQ Test (CFT 20-R) to assess fluid intelligence. In this work, we extend and complement the current state of research by analysing the differential and combined relationship between eye-movement patterns and socio-demographic information and the ability of a participant to correctly solve a CFT item. Our work shows that a participant’s eye movements while solving a CFT item contain discriminative information and can be used to predict whether the participant will succeed in solving the test item. Moreover, the information related to eye movements complements the information provided by socio-demographic data when it comes to success prediction. In combination, both types of information yield a significantly higher predictive performance than each information type individually. To better understand the contributions of features related to eye movements and socio-demographic information to predict a participant’s success in solving a CFT item, we employ state-of-the-art explainability techniques and show that, along with socio-demographic variables, eye-movement data. Especially the number of saccades and the mean pupil diameter, significantly increase the discriminating power. The eye-movement features are likely indicative of processing efficiency and invested mental effort. Beyond the specific contribution to research on how eye movements can serve as a means to uncover mechanisms underlying cognitive processes, the findings presented in this work pave the way for further in-depth investigations of factors predicting individual differences in fluid intelligence.

Dissociated brain functional connectivity of fast versus slow frequencies underlying individual differences in fluid intelligence: a DTI and MEG study

Brain network analysis represents a powerful technique to gain insights into the connectivity profile characterizing individuals with different levels of fluid intelligence (Gf). Several studies have used diffusion tensor imaging (DTI) and slow-oscillatory resting-state fMRI (rs-fMRI) to examine the anatomical and functional aspects of human brain networks that support intelligence. In this study, we expand this line of research by investigating fast-oscillatory functional networks. We performed graph theory analyses on resting-state magnetoencephalographic (MEG) signal, in addition to structural brain networks from DTI data, comparing degree, modularity and segregation coefficient across the brain of individuals with high versus average Gf scores. Our results show that high Gf individuals have stronger degree and lower segregation coefficient than average Gf participants in a significantly higher number of brain areas with regards to structural connectivity and to the slower frequency bands of functional connectivity. The opposite result was observed for higher-frequency (gamma) functional networks, with higher Gf individuals showing lower degree and higher segregation across the brain. We suggest that gamma oscillations in more intelligent individuals might support higher local processing in segregated subnetworks, while slower frequency bands would allow a more effective information transfer between brain subnetworks, and stronger information integration.

Attentional resource allocation among individuals with different fluid intelligence: The integrated control hypothesis and its evidence from pupillometry

To clarify the effects of individual differences in fluid intelligence (Gf) on attentional resource allocation, the present study proposes a new hypothesis (i.e., the integrated control hypothesis) based on previous studies and provides preliminary empirical evidence through a pupillometry study. The results showed that both task type and task difficulty play crucial roles in the relationship between Gf and attentional resource allocation when participants perform visuospatial-domain tasks. In particular, in the exploitation task, higher Gf individuals allocated fewer attentional resources than those with average Gf at all the difficulty levels. In contrast, in the exploration task, those with higher intelligence allocated equivalent resources in the low- and medium-difficulty trials and more resources in the high-difficulty trials; this phenomenon was more significant among the male subjects. In conclusion, this study suggests that high Gf individuals tend to control their attention state in tasks with diverse demands, allowing them to dynamically optimize the use of attentional resources and flexibly adapt to changing conditions.

Multilayer Functional Connectome Fingerprints: Individual Identification via Multimodal Convolutional Neural Network

As a neural fingerprint, functional connectivity networks (FCNs) have been used to identify subjects from group. However, a number of studies have only paid attention to cerebral cortex when constructing the brain FCN. Other areas of the brain also play important roles in brain activities. It is widely accepted that the human brain is composed of many highly complex functional networks of cortex. Moreover, recent studies have confirmed correlations between signals of cortex and white matter (WM) bundles. Therefore, it is difficult to reflect the functional characteristics of the brain through a single-layer FCN. In this paper, a multilayer FCN involving both cerebral cortex and WM was proposed to characterize different levels of FCNs based on resting-state functional Magnetic Resonance Imaging (fMRI) data. The multilayer FCN is regarded as a neural fingerprint to realize individual identification and the individual variability of which is related to individual differences in fluid intelligence and gender. In addition, the proposed multilayer FCN has been learned by a multimodal convolutional neural network (CNN) algorithm to achieve individual identification. Compared with the existing FCN that only involves the cerebral cortex, the accuracy of individual recognition illustrates the effectiveness of our method. Meanwhile, the proposed multilayer FCN also achieves better results than the traditional single-layer FCN in gender classification and fluid intelligence prediction.

In Search of the Executive Cognitive Processes Proposed by Process-Overlap Theory.

Process-Overlap Theory (POT) suggests that measures of cognitive abilities sample from sets of independent cognitive processes. These cognitive processes can be separated into domain-general executive processes, sampled by the majority of cognitive ability measures, and domain-specific processes, sampled only by measures within a certain domain. According to POT, fluid intelligence measures are related because different tests sample similar domain-general executive cognitive processes to some extent. Re-analyzing data from a study by De Simoni and von Bastian (2018), we assessed domain-general variance from executive processing tasks measuring inhibition, shifting, and efficiency of removal from working memory, as well as examined their relation to a domain-general factor extracted from fluid intelligence measures. The results showed that domain-general factors reflecting general processing speed were moderately and negatively correlated with the domain-general fluid intelligence factor (r = −.17–−.36). However, domain-general factors isolating variance specific to inhibition, shifting, and removal showed only small and inconsistent correlations with the domain-general fluid intelligence factor (r = .02–−.22). These findings suggest that (1) executive processing tasks sample only few domain-general executive processes also sampled by fluid intelligence measures, as well as (2) that domain-general speed of processing contributes more strongly to individual differences in fluid intelligence than do domain-general executive processes.

Interactive effects of dopamine transporter genotype and aging on resting-state functional networks.

Aging and dopamine modulation have both been independently shown to influence the functional connectivity of brain networks during rest. Dopamine modulation is known to decline during the course of aging. Previous evidence also shows that the dopamine transporter gene (DAT1) influences the re-uptake of dopamine and the anyA9 genotype of this gene is associated with higher striatal dopamine signaling. Expanding these two lines of prior research, we investigated potential interactive effects between aging and individual variations in the DAT1 gene on the modular organization of brain acvitiy during rest. The graph-theoretic metrics of modularity, betweenness centrality and participation coefficient were assessed in 41 younger (age 20–30 years) and 37 older (age 60–75 years) adults. Age differences were only observed in the participation coefficient in carriers of the anyA9 genotype of the DAT1 gene and this effect was most prominently observed in the default mode network. Furthermore, we found that individual differences in the values of the participation coefficient correlated with individual differences in fluid intelligence and a measure of executive control in the anyA9 carriers. The correlation between participation coefficient and fluid intelligence was mainly shared with age-related differences, whereas the correlation with executive control was independent of age. These findings suggest that DAT1 genotype moderates age differences in the functional integration of brain networks as well as the relation between network characteristics and cognitive abilities.

Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.

The human brain integrates diverse cognitive processes into a coherent whole, shifting fluidly as a function of changing environmental demands. Despite recent progress, the neurobiological mechanisms responsible for this dynamic system-level integration remain poorly understood. Here we investigated the spatial, dynamic, and molecular signatures of system-wide neural activity across a range of cognitive tasks. We found that neuronal activity converged onto a low-dimensional manifold that facilitates the execution of diverse task states. Flow within this attractor space was associated with dissociable cognitive functions, unique patterns of network-level topology, and individual differences in fluid intelligence. The axes of the low-dimensional neurocognitive architecture aligned with regional differences in the density of neuromodulatory receptors, which in turn relate to distinct signatures of network controllability estimated from the structural connectome. These results advance our understanding of functional brain organization by emphasizing the interface between neural activity, neuromodulatory systems, and cognitive function.

Metaphor comprehension: An individual-differences approach

The nature of the mental processes involved in metaphor comprehension has been the focus of debate, with controversy focusing on the relative role of general analogical reasoning versus language-specific conceptual combination. In the present set of studies, we take an individual-differences approach to examine the comprehension of a variety of metaphors, some taken from literary sources, using several types of comprehension tests. In a series of metaphor-comprehension studies with college students, we measured both fluid intelligence (using the nonverbal Raven’s Progressive Matrices test) and crystalized verbal intelligence (using a new Semantic Similarities Test as well as the Vocabulary subscale of the Wechsler Adult Intelligence Scale). Previous work has shown that measures of fluid intelligence are closely linked to individual differences in analogical reasoning, whereas measures of crystalized verbal intelligence are linked to language-specific abilities. We found that each measure had a dissociable predictive relationship to metaphor comprehension. The pattern of individual differences indicated that crystalized intelligence influences metaphor comprehension across a broad range of metaphor types, whereas individual differences in fluid intelligence mainly impact comprehension of more cognitively complex metaphors, such as those that arise in literary sources.

The benefits of retrieval practice depend on item difficulty and intelligence.

The authors examined whether individual differences in fluid intelligence (gF) modulate the testing effect. Participants studied Swahili-English word pairs and repeatedly studied half the pairs or attempted retrieval, with feedback, for the remaining half. Word pairs were easy or difficult to learn. Overall, participants showed a benefit of testing over restudy. However, almost 1/3 of the sample had a negative testing effect and benefitted more from restudy than testing, as well as performing better overall. These individuals self-reported less use of shallower encoding strategies than positive testing effect participants but did not differ in other dimensions. For individuals with a positive testing effect, difficulty had differential effects on participants who scored high or low on a measure of gF, with high gF participants showing larger testing effects for difficult over easy items, whereas low gF participants showed the opposite. Working memory performance was not related to the magnitude of the testing effect; however, vocabulary knowledge revealed a similar pattern as gF, with higher vocabulary associated with a testing effect for difficult but not easy items. This suggests that the benefit of retrieval practice varies with item difficulty and participant abilities. Thus, recommendations to engage in retrieval practice should take into consideration the interactive effects of to-be-learned materials and individual differences in the learners. (PsycINFO Database Record

The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank.

Background:Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods:In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results:We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions:In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

Mental rotation and fluid intelligence: A brain potential analysis

The current study examined the relation between mental rotation and fluid intelligence using performance measures augmented with brain potential indices. Participants took a Raven's Progressive Matrices Test and performed on a mental rotation task presenting upright and rotated letter stimuli (60°, 120° or 180°) in normal and mirror image requiring a response execution or inhibition depending on instructions. The performance results showed that the linear slope relating performance accuracy, but not speed, to the angular rotation of the stimuli was related to individual differences in fluid intelligence. For upright stimuli, P3 amplitude recorded at frontal and central areas was positively associated with fluid intelligence scores. The mental rotation process was related to a negative shift of the brain potential recorded over the parietal cortex. The linear function relating the amplitude of the rotation-related negativity to rotation angle was associated with fluid intelligence. The slope was more pronounced for high- relative to low-ability participants suggesting that the former flexibly adjust their expenditure of mental effort to the mental rotation demands while the latter ones are less proficient in doing so.

The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

Signatures of multiple processes contributing to fluid reasoning performance

We aimed to achieve a better understanding of the cognitive processes of fluid reasoning (or fluid intelligence; Gf), the ability to reason in novel conditions. While fluid reasoning has often been considered a unitary construct, multiple cognitive processes are expected to affect fluid reasoning performance. Yet, the contribution of various cognitive processes in fluid reasoning performance remains under-explored. We hypothesized that individual differences in fluid intelligence can be viewed as a composite of individual differences in performance in various processes of Gf. Change detection, rule verification, and rule generation were the three processes-of-interest that were additively recruited in a novel visuospatial reasoning task. We observed decreases in accuracy and increases in response time as the processing requirements increased across task conditions. Hierarchical multiple linear regression analyses showed that individual differences in the likelihood of success and speed of each of these processes, accounted for different aspects of individual differences in accuracy and response time in fluid reasoning performance, as measured by Raven's Progressive Matrices. Change detection was a significant contributor to performance in problems with higher visuospatial demand, however, rule verification and rule generation consistently contributed to performance for all problem types. Our findings support the position that individual differences in fluid intelligence emerge as a composite of performance on separable cognitive operations, with rule processing being important for differentiating performance on high difficulty problems.

Short-Term Storage and Executive Working Memory Processing Predict Fluid Intelligence in Primary School Children.

Working memory (WM) includes short-term storage and executive processing of information. WM has been suggested to be one of the key concepts to explain individual differences in fluid intelligence (Gf). However, only a few studies have investigated the association of the two different aspects of WM in relation to Gf. Furthermore, even fewer studies have included children. Therefore, we first investigated the inter-relations between the WM aspects (verbal and visual-spatial storage, verbal and visual-spatial executive processing). Second, we explored the relation between a general WM factor and Gf. Third, we analyzed the relations between the different WM aspects and Gf while we controlled for common variance among all WM tasks. Nine- to 11-year olds had to solve simple and complex span tasks. Correlations and structural equation modeling techniques were used to examine these relations. Most inter-relations among simple and complex spans were found to be substantial and positive. The general WM factor was related to Gf. Furthermore, after controlling for common variance among all WM tasks, individual differences in verbal storage, visual-spatial storage and verbal processing still uniquely related to Gf. Visual-spatial processing, however, was not related to Gf. Results are discussed in terms of underlying mechanisms.

Goal neglect, fluid intelligence and processing speed: Manipulating instruction load and inter-stimulus interval

Goal maintenance is the process where task rules and instructions are kept active to exert their control on behavior. When this process fails, an individual may ignore a rule while performing the task, despite being able to describe it after task completion. Previous research has suggested that the goal maintenance system is limited by the number of concurrent rules which can be maintained during a task, and that this limit is dependent on an individual's level of fluid intelligence. However, the speed at which an individual can process information may also limit their ability to use task rules when the task demands them. In the present study, four experiments manipulated the number of instructions to be maintained by younger and older adults and examined whether performance on a rapid letter-monitoring task was predicted by individual differences in fluid intelligence or processing speed. Fluid intelligence played little role in determining how frequently rules were ignored during the task, regardless of the number of rules to be maintained. In contrast, processing speed predicted the rate of goal neglect in older adults, where increasing the presentation rate of the letter-monitoring task increased goal neglect. These findings suggest that goal maintenance may be limited by the speed at which it can operate.