Fluid reasoning is equivalent to relation processing

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.

No effects of the theta-frequency transcranial electrical stimulation for recall, attention control, and relation integration in working memory

Introduction

Recent studies have suggested that transcranial alternating current stimulation (tACS), and especially the theta-frequency tACS, can improve human performance on working memory tasks. However, evidence to date is mixed. Moreover, the two WM tasks applied most frequently, namely the n-back and change-detection tasks, might not constitute canonical measures of WM capacity.

Method

In a relatively large sample of young healthy participants (N = 62), we administered a more canonical WM task that required stimuli recall, as well as we applied two WM tasks tapping into other key WM functions: attention control (the antisaccade task) and relational integration (the graph mapping task). The participants performed these three tasks three times: during the left frontal 5.5-Hz and the left parietal 5.5-Hz tACS session as well as during the sham session, with a random order of sessions. Attentional vigilance and subjective experience were monitored.

Results

For each task administered, we observed significant gains in accuracy neither for the frontal tACS session nor for the parietal tACS session, as compared to the sham session. By contrast, the scores on each task positively inter-correlated across the three sessions.

Discussion

The results suggest that canonical measures of WM capacity are strongly stable in time and hardly affected by theta-frequency tACS. Either the tACS effects observed in the n-back and change detection tasks do not generalize onto other WM tasks, or the tACS method has limited effectiveness with regard to WM, and might require further methodological advancements.

Working memory load affects intelligence test performance by reducing the strength of relational item bindings and impairing the filtering of irrelevant information

There is a broad consensus that individual differences in working memory capacity (WMC) are strongly related to individual differences in intelligence. However, correlational studies do not allow conclusions about the causal nature of the relationship between WMC and fluid intelligence. While research on the cognitive basis of intelligence typically assumes that simpler lower-level cognitive processes contribute to individual differences in higher-order reasoning processes, a reversed causality or a third variable giving rise to two intrinsically uncorrelated variables may exist. In two studies (n₁ = 65, n₂ = 113), we investigated the causal nature of the relationship between WMC and intelligence by assessing the experimental effect of working memory load on intelligence test performance. Moreover, we tested if the effect of working memory load on intelligence test performance increased under time constraints, as previous studies have shown that the association between the two constructs increases if intelligence tests are administered with a strict time limit. We show that working memory load impaired intelligence test performance, but that this experimental effect was not affected by time constraints, which suggests that the experimental manipulations of working memory capacity and processing time did not affect the same underlying cognitive process. Using a computational modeling approach, we demonstrated that external memory load affected both the building and maintenance of relational item bindings and the filtering of irrelevant information in working memory. Our results confirm that WMC causally contributes to higher-order reasoning processes. Moreover, they support the hypothesis that working memory capacity in general and the abilities to maintain arbitrary bindings and to disengage from irrelevant information in particular are intrinsically related to intelligence.

Cognitive strategies in matrix-reasoning tasks: State of the art

Cognitive strategies in matrix-reasoning tasks have been investigated for the last decade and a half. Several steps were made since the first paper in the field, but the advances have been sparse and with little connection. Here we present a review of the state of the art in this subject. We introduce how this topic was born and how to measure these strategies, covering the diverse methods and measures that are presented in the literature to progress on this subject and the applications that were developed, as well as the knowledge that resulted from these applications. Furthermore, the future directions are discussed with the intention to engage new researchers in this topic, as well as to bring awareness to limitations that were found given the available scientific literature.

The Associations between Results in Different Domains of Cognitive and Psychomotor Abilities Measured in Medical Students

We aimed to investigate the associations between intelligence quotient test scores obtained using the Raven's Advanced Progressive Matrices (APM) and psychomotor testing using the Complex Reactionmeter Drenovac (CRD) test battery, while taking into account previous theoretical approaches recognizing intelligent behavior as the cumulative result of a general biological speed factor reflected in the reaction time for perceptual detections and motor decisions. A total of 224 medical students at the University of Split School of Medicine were recruited. Their IQ scores were assessed using Raven's APM, while the computerized tests of CRD-series were used for testing the reaction time of perception to visual stimulus (CRD311), psychomotor limbs coordination task (CRD411), and solving simple arithmetic operations (CRD11). The total test-solving (TTST) and the minimum single-task-solving (MinT) times were analyzed. On the CRD11 test, task-solving times were shorter in students with higher APM scores (r = -0.48 for TTST and r = -0.44 for MinT; p < 0.001 for both). Negative associations between task-solving times and APM scores were reported on CRD311 (r = -0.30 for TTST and r = -0.33 for MinT, p < 0.001 for both). Negative associations between task-solving times in CRD411 and APM scores (r = -0.40 for TTST and r = -0.30 for MinT, p < 0.001 for both) were found. Faster reaction time in psychomotor limbs coordination tasks, the reaction time of perception to visual stimulus, and the reaction time of solving simple arithmetic operations were associated with a higher APM score in medical students, indicating the importance of mental speed in intelligence test performance. However, executive system functions, such as attention, planning, and goal weighting, might also impact cognitive abilities and should be considered in future research.

Graph Mapping: A novel and simple test to validly assess fluid reasoning

We present Graph Mapping - a simple and effective computerized test of fluid intelligence (reasoning ability). The test requires structure mapping - a key component of the reasoning process. Participants are asked to map a pair of corresponding nodes across two mathematically isomorphic but visually different graphs. The test difficulty can be easily manipulated - the more complex structurally and dissimilar visually the graphs, the higher response error rate. Graph Mapping offers high flexibility in item generation, ranging from trivial to extremally difficult items, supporting progressive item sequences suitable for correlational studies. It also allows multiple item instances (clones) at a fixed difficulty level as well as full item randomization, both particularly suitable for within-subject experimental designs, longitudinal studies, and adaptive testing. The test has short administration times and is unfamiliar to participants, yielding practical advantages. Graph Mapping has excellent psychometric properties: Its convergent validity and reliability is comparable to the three leading traditional fluid reasoning tests. The convenient software allows a researcher to design the optimal test variant for a given study and sample. Graph Mapping can be downloaded from: https://osf.io/wh7zv/.

Fluid Intelligence Emerges from Representing Relations

Based on recent findings in cognitive neuroscience and psychology as well as computational models of working memory and reasoning, I argue that fluid intelligence (fluid reasoning) can amount to representing in the mind the key relation(s) for the task at hand. Effective representation of relations allows for enormous flexibility of thinking but depends on the validity and robustness of the dynamic patterns of argument–object (role–filler) bindings, which encode relations in the brain. Such a reconceptualization of the fluid intelligence construct allows for the simplification and purification of its models, tests, and potential brain mechanisms.