scholarly journals Fluid Intelligence: Review of Foreign Studies

2018 ◽  
Vol 7 (4) ◽  
pp. 19-43 ◽  
Author(s):  
I.E. Rzhanova ◽  
V.S. Britova ◽  
O.S. Alekseeva ◽  
Yu.A. Burdukova
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Cognitive Deficits ◽  
Cognitive Abilities ◽  
Clinical Evidence ◽  
Fluid Intelligence ◽  
General Intelligence ◽  
Children With Adhd ◽  
Fluid Reasoning ◽  
The Relationship

The present review focuses on modern research of fluid intelligence. The concept of fluid intelligence, the place of fluid intelligence in the structure of cognitive abilities, its relation to general intelligence is revealed. The current models of fluid intelligence are considered, including the current leading Cattell–Horn–Carroll model. The neurobiological processes underlying the flexibility of fluid reasoning processes in solving novel problems are discussed. In particular, studies are presented showing that fluid intelligence is mediated by subregions of the prefrontal cortex. Studies of the relationship between fluid intelligence and working memory, as well as studies of fluid intelligence in clinical groups such as children with ADHD and adults with schizophrenia are also discussed. Clinical evidence suggests that fluid intelligence may be key to understanding the structure of cognitive deficits in ADHD syndrome.

scholarly journals Developmental Fractionation of Working Memory and Response Inhibition During Childhood

2007 ◽  
Vol 54 (1) ◽  
pp. 30-37 ◽  
Author(s):  
Satoshi Tsujimoto ◽  
Mariko Kuwajima ◽  
Toshiyuki Sawaguchi
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Response Inhibition ◽  
Cognitive Functions ◽  
Cognitive Abilities ◽  
Childhood Development ◽  
Neural Systems ◽  
Older Children ◽  
Efficient Processing ◽  
The Relationship

Abstract. The lateral prefrontal cortex (LPFC) plays a major role in both working memory (WM) and response inhibition (RI), which are fundamental for various cognitive abilities. We explored the relationship between these LPFC functions during childhood development by examining the performance of two groups of children in visuospatial and auditory WM tasks and a go/no-go RI task. In the younger children (59 5- and 6-year-olds), performance on the visuospatial WM task correlated significantly with that in the auditory WM task. Furthermore, accuracy in these tasks correlated significantly with performance on the RI task, particularly in the no-go trials. In contrast, there were no significant correlations among those tasks in older children (92 8- and 9-year-olds). These results suggest that functional neural systems for visuospatial WM, auditory WM, and RI, especially those in the LPFC, become fractionated during childhood, thereby enabling more efficient processing of these critical cognitive functions.

Understanding the Relationship Between Rationality and Intelligence: A Latent-Variable Approach

2021 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Cody Mashburn ◽  
Jason S. Tsukahara ◽  
Zach Hambrick ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Equation Modeling ◽  
General Intelligence ◽  
Variable Approach ◽  
The Relationship

A hallmark of intelligent behavior is rationality—the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability, and therefore align with normative principles of decision making. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a large sample of participants (N = 331), we used latent variable analyses to assess the relationship between rationality and intelligence. The results indicated that there was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Indeed, after accounting for variance in performance attributable to general intelligence, rationality measures still cohered on a latent factor. Confirmatory factor analysis indicated that rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Structural equation modeling revealed that attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. Results are interpreted in light of the executive attention framework, which holds that attention control supports information maintenance and disengagement in service of complex cognition. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.

Working memory, executive function, and general fluid intelligence are not the same

2006 ◽  
Vol 29 (2) ◽  
pp. 135-136 ◽  
Author(s):  
Richard P. Heitz ◽  
Thomas S. Redick ◽  
David Z. Hambrick ◽  
Michael J. Kane ◽  
Andrew R. A. Conway ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Executive Function ◽  
Fluid Intelligence ◽  
Good Reason ◽  
Normal Functioning ◽  
Controlled Attention ◽  
The Relationship

Blair equates the constructs of working memory (WM), executive function, and general fluid intelligence (gF). We argue that there is good reason not to equate these constructs. We view WM and gF as separable but highly related, and suggest that the mechanism behind the relationship is controlled attention – an ability that is dependent on normal functioning of the prefrontal cortex.

scholarly journals ADHD subtype-specific cognitive correlates and association with self-esteem: a quantitative difference

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Parviz Molavi ◽  
Mehriar Nadermohammadi ◽  
Habibeh Salvat Ghojehbeiglou ◽  
Carmelo M. Vicario ◽  
Michael A. Nitsche ◽  
...  
Keyword(s):  
Working Memory ◽  
Cognitive Deficits ◽  
Cognitive Abilities ◽  
Self Esteem ◽  
Parent Rating ◽  
Adhd Subtypes ◽  
Cognitive Domains ◽  
Children With Adhd ◽  
Cognitive Correlates ◽  
Adhd Subtype

Abstract Background Attention-deficit hyperactivity disorder (ADHD) is a major neurodevelopmental disorder with heterogeneous symptoms, subtypes, and cognitive deficits. Cognitive deficits are central to ADHD pathophysiology and one potential source of heterogeneity in ADHD. Subtype-specific cognitive correlates are not, however, well-studied. We explored cognitive correlates of ADHD subtypes based on the Wechsler Intelligence Scale for Children (WISC-IV) scores. We also assessed subtype-specific self-esteem rating in ADHD subtypes and explored its association with cognitive correlates. Methods One hundred thirty-nine children with ADHD (80.6% boy, 19.4% girl) were categorized into the predominantly “hyperactive (ADHD-H)”, “inattentive (ADHD-I)” and “combined (ADHD-C)” subtype based on their symptoms and scores on the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL) and Conners Parent-Rating Scale (CPRS-RS). They were then individually administrated the WISC-IV and completed a self-esteem inventory. Group differences in the WISC-IV indices and their predictability in discriminating ADHD subtypes were analyzed. Results We found a quantitative differentiation of cognitive abilities among ADHD subtypes with “working memory” as the most compromised cognitive domain. ADHD-I had the poorest cognitive profile while ADHD-H scored highest in all cognitive domains. Importantly, cognitive abilities were negatively correlated with inattention and positively correlated with hyperactive symptoms. Moreover, self-esteem ratings were positively correlated with the cognitive domains and were rated differently based on the subtypes. ADHD-H, with the highest cognitive strength, reported the highest level of self-esteem among all subtypes. Conclusions ADHD subtype-specific symptoms, cognitive deficits, and self-esteem problems should be considered for precise diagnosis and effective and personalized treatment in ADHD in light of further supporting evidence and assessments. Cognitive interventions might be more compatible with and effective in inattentive and combined subtypes of ADHD. Working memory improving-based interventions can benefit all ADHD subtypes. A supportive educational system in school and providing adjunct supportive interventions should be considered for children with ADHD as well.

scholarly journals Predicting Academic Achievement with Cognitive Abilities: Cross-Sectional Study across School Education

2020 ◽  
Vol 10 (10) ◽  
pp. 158
Author(s):  
Tatiana Tikhomirova ◽  
Artem Malykh ◽  
Sergey Malykh
Keyword(s):  
Academic Achievement ◽  
Working Memory ◽  
Information Processing ◽  
Processing Speed ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Number Sense ◽  
Information Processing Speed ◽  
Cross Sectional ◽  
The Relationship

The relationship between cognitive abilities and academic achievement across schooling from the first to the eleventh grade was analyzed. Information processing speed, visuospatial working memory, number sense, and fluid intelligence were considered predictors of general academic achievement, which was derived from grades in mathematics, language, and biology. This cross-sectional study involved 1560 pupils who were in grades 1–11 at general education schools and were aged from 6.8 to 19.1 years (50.4% were boys). Information processing speed, visuospatial working memory, and number sense were measured using the Choice Reaction Time, Corsi Block-Tapping, and Number Sense computerized tests, respectively. Fluid intelligence was measured using the paper-and-pencil version of the Standard Progressive Matrices test. Correlation analysis and structural equation modeling were carried out. It was shown that it is possible to describe the structure of the relationship between cognitive abilities and academic achievement for all levels of schooling with a single model. In this model, information processing speed is the key predictor of fluid intelligence, working memory, and number sense, which in turn contribute to individual differences in academic success. Additionally, the specificity of the relationship between individual indicators of cognitive abilities and academic achievement at each level of schooling was revealed.

scholarly journals Expertise Within Working Memory and Fluid Intelligence

2019 ◽  
Author(s):  
Addie Wikowsky ◽  
Erin Michelle Buchanan
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Critical Factor ◽  
Quality Measures ◽  
Psychology Students ◽  
General Intelligence ◽  
State University ◽  
Previous Knowledge ◽  
The Relationship ◽  
Typing Task

Working memory, fluid intelligence, and expertise are all psychological concepts that have been explored in the field. Working memory, defined by Baddeley (1986), is the temporary storage of stimuli presented to a person. The relationship between working memory and fluid intelligence is a common theme among studies. Fluid intelligence is one of the components of general intelligence (g). Specifically, fluid intelligence can be described as being able to adapt thinking, even with no previous knowledge (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008). Expertise is another critical factor in these studies and is the acquisition of knowledge and being able to apply that knowledge (Chi, Glaser, & Rees, 1982). This thesis looks at the inter-relationships of those concepts in Missouri State University psychology students. The researchers confirmed the previously noted relationship between working memory and fluid intelligence (r = .50), but there were no other significant correlations between the tasks. It was interesting that working memory and fluid intelligence had similar correlations for the typing task (r = .23, r = .19), although not significant. These effects disappeared after controlling for the data quality measures used in the study (i.e., ways to show the participants put effort into the study). More research is needed to confirm that the current measures of expertise, or different ones, are related to working memory or fluid intelligence.

A New View of the Relationship between Creativity and Intelligence

1981 ◽  
Vol 5 (4) ◽  
pp. 295-307
Author(s):  
Steven Harvey
Keyword(s):  
Cognitive Abilities ◽  
Structural Equation ◽  
Creative Thinking ◽  
Fluid Intelligence ◽  
Juvenile Justice System ◽  
Factor Model ◽  
Equation Model ◽  
General Intelligence ◽  
Age Appropriate ◽  
The Relationship

One hundred and fourteen youths involved in a juvenile justice system, half of whom were included because of potential giftedness, were administered the age appropriate Weschler Intelligence Scales and the Torrance Test of Creative Thinking to assess their cognitive abilities. The resulting multivariate data were analyzed using maximum likehood factor analysis and structural equation model to develop a factor model of intellectual and creative abilities and the relationships among them. Two high order factor and five lower level characteristics were isolated. These were defined as general intelligence and general fluency at the higher level, and crystallized and fluid intelligence, verbal and figural divergent production, along with creative energy, at the lower level. While no relationship was found between general intelligence and general fluency, the creative energy factor was found to be influenced by both of these higher order factors. This result was used in discussion related to the theory of creativity.

scholarly journals Working Memory, Fluid Reasoning, and Complex Problem Solving: Different Results Explained by the Brunswik Symmetry

2021 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
André Kretzschmar ◽  
Stephan Nebe
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Cognitive Abilities ◽  
Latent Variables ◽  
Complex Problem ◽  
Equation Modeling ◽  
Complex Problem Solving ◽  
Symmetry Principle ◽  
Fluid Reasoning ◽  
The Impact

In order to investigate the nature of complex problem solving (CPS) within the nomological network of cognitive abilities, few studies have simultantiously considered working memory and intelligence, and results are inconsistent. The Brunswik symmetry principle was recently discussed as a possible explanation for the inconsistent findings because the operationalizations differed greatly between the studies. Following this assumption, 16 different combinations of operationalizations of working memory and fluid reasoning were examined in the present study (N = 152). Based on structural equation modeling with single-indicator latent variables (i.e., corrected for measurement error), it was found that working memory incrementally explained CPS variance above and beyond fluid reasoning in only 2 of 16 conditions. However, according to the Brunswik symmetry principle, both conditions can be interpreted as an asymmetrical (unfair) comparison, in which working memory was artificially favored over fluid reasoning. We conclude that there is little evidence that working memory plays a unique role in solving complex problems independent of fluid reasoning. Furthermore, the impact of the Brunswik symmetry principle was clearly demonstrated as the explained variance in CPS varied between 4 and 31%, depending on which operationalizations of working memory and fluid reasoning were considered. We argue that future studies investigating the interplay of cognitive abilities will benefit if the Brunswik principle is taken into account.

scholarly journals Possible Effect of Headphone Usage on Working Memory Among Students in Faculty of Medicine, Ahmadu Bello University, Zaria‒Nigeria

2019 ◽  
pp. 1-4
Author(s):  
Yushau Yusuf ◽  
Muhammad U.A ◽  
Isah F.A
Keyword(s):  
Working Memory ◽  
Signal Processing ◽  
Cognitive Abilities ◽  
Healthy Subjects ◽  
Significant Difference ◽  
Stored Information ◽  
Age Range ◽  
The Relationship ◽  
The Brain ◽  
Back Task

Working memory is a system that is responsible for transient holding and processing of new and already stored information. It also involves processing for reasoning, comprehension, learning and memory updating. Headphones are a pair of small loudspeakers that are designed to be held in place close to a user’s ear. They are electroacoustic transducers which convert electrical signals to a corresponding sound in the user’s ear. Several studies have recently shown a link between cognitive abilities and response to hearing aid and signal processing in the brain. Therefore, the relationship between headphone usage among healthy subjects become pertinent. This study is aimed at evaluating the effect of headphone on working memory using N-back task. One hundred (100) participants (55 headphone users and 45 non-headphone user’s) within the age range of 18-31 years were assessed. Participants were instructed to keep in memory, a series of letters and say “target” whenever there was a repetition of letter with exactly one intervening letter and to remain silent when any other letter appeared. The results of this study showed that there was no statistically significant difference in working memory between headphone and non-headphone users with p>0.05. In conclusion, this study revealed headphone use has no effect on working memory of the participants subjected to N–back test.

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