There has been some controversy as to whether baseline pupil size is related to individual differences in cognitive ability. Previously, we had shown that a larger baseline pupil size was associated ...with higher cognitive ability and that the correlation to fluid intelligence was larger than that to working memory capacity (Tsukahara, Harrison, & Engle, 2016). However, other researchers have not been able to replicate our findings – though they only measured working memory capacity and not fluid intelligence. Many of the studies showing no relationship had major methodological issues, namely small baseline pupil size values – down to the physiological minimum – that resulted in reduced variability on baseline pupil size. We conducted two large-scale studies to investigate how different lighting conditions affect baseline pupil size values and the correlation with cognitive abilities. We found that fluid intelligence, working memory capacity, and attention control did correlate with baseline pupil size except in the brightest lighting conditions. We showed that a reduced variability in baseline pupil size values is due to the monitor settings being too bright. Overall, our findings demonstrated that the baseline pupil size – working memory capacity relationship was not as strong or robust as that with fluid intelligence or attention control. Our findings have strong methodological implications for researchers investigating individual differences in task-free or task-evoked pupil size. We conclude that fluid intelligence does correlate with baseline pupil size and that this is related to the functional organization of the resting-state brain through the locus coeruleus-norepinephrine system.
Eye movement studies are subject of interest in human cognition. Cortical activity and cognitive load impress eye movement influentially. Here, we investigated whether fluid intelligence (FI) has any ...effect on eye movement pattern in a comparative visual search (CVS) task. FI of individuals was measured using the Cattell test, and participants were divided into three groups: low FI, middle FI, and high FI. Eye movements of individuals were then recorded during the CVS task. Eye movement patterns were extracted and compared statistically among the three groups. Our experiment demonstrated that eye movement patterns were significantly different among the three groups. Pearson correlation coefficients between FI and eye movement parameters were also calculated to assess which of the eye movement parameters were most affected by FI. Our findings illustrate that saccade peak velocity had the greatest positive correlation with FI score and the ratio of total fixation duration to total saccade duration had the greatest negative correlation with FI. Next, we extracted 24 features from eye movement patterns and designed: (1) a classifier to categorize individuals and (2) a regression analysis to predict the FI score of individuals. In the best case examined, the classifier categorized subjects with 68.3% accuracy, and the regression predicted FI of individuals with a 0.54 correlation between observed FI and predicted FI. In our investigation, the results have emphasized that imposed loads on low FI individuals is greater than that of high FI individuals in the cognitive load tasks.
Our recent meta-analysis concluded that training on working memory can improve performance on tests of fluid intelligence (Au et al., Psychon Bull Rev, 22(2), 366-377,
2015
). Melby-Lervåg and Hulme ...(Psychon Bull Rev, doi:
10.3758/s13423-015-0862-z
) challenge this conclusion on the grounds that it did not take into consideration baseline differences on a by-study level and that the effects were primarily driven by purportedly less rigorous studies that did not include active control groups. Their re-analysis shows that accounting for baseline differences produces a statistically significant, but considerably smaller, overall effect size (g = 0.13 vs g = 0.24 in Au et al.), which loses significance after excluding studies without active controls. The present report demonstrates that evidence of impact variation by the active/passive nature of control groups is ambiguous and also reveals important discrepancies between Melby-Lervåg and Hulme’s analysis and our original meta-analysis in terms of the coding and organization of data that account for the discrepant effect sizes. We demonstrate that there is in fact no evidence that the type of control group
per se
moderates the effects of working memory training on measures of fluid intelligence and reaffirm the original conclusions in Au et al., which are robust to multiple methods of calculating effect size, including the one proposed by Melby-Lervåg and Hulme.
There has been growing interest in enhancing cognition in older adulthood via computerized cognitive training (CCT), though, there is controversy surrounding the efficacy of CCT in promoting ...improvements to functional everyday activities. As core executive-functions (EFs)-cognitive-flexibility, inhibition, working memory-are applicable to most aspects of daily living, CCT targeting these processes would likely promote gains on trained tasks, and potentially on similar untrained tasks (near-transfer), and general cognitive performance (far-transfer). We report two meta-analyses investigating the immediate (pretest to posttest) and long-term efficacy (pretest to follow-up) of core-EF CCT in improving cognition among older adults. Sixty-four studies (encompassing 3,594 participants) included an eligible CCT intervention targeting at least 1 core-EF (e.g., working memory training). Both immediate and long-term efficacy analyses revealed significant, large training effects for trained outcomes, and significant, small training effects for near-transfer and far-transfer outcomes. When comparing the same studies, effect sizes from immediate and long-term efficacy analyses were comparable, suggesting that CCT gains were maintained over time. Further analyses of immediate efficacy revealed significant, small training effects for performance on executive functioning, fluid intelligence, memory, and visuospatial domains, but not for attention or processing speed. After adjusting for publication bias, the training effect for fluid intelligence was nonsignificant, whereas processing speed was significant. It is recommended that future studies employ adaptive multidomain training as these studies were shown to produce significant training effects at each transfer level. Overall, core-EF CCT interventions show promise in promoting immediate and long-term improvements in cognitive performance among older adults.
Public Significance Statement
This meta-analytic investigation suggests that cognitive training targeting multiple core executive functions (working memory, inhibition, cognitive flexibility) promotes cognitive enhancement in older adulthood. Improvements in cognitive performance are shown not only on trained tasks, but on many untrained tasks as well (near- and far-transfer), though these transfer effects are small and limited to select cognitive domains. These improvements in cognitive performance appear to be maintained over time.
We meta-analytically investigated relations between the four-branch model of ability emotional intelligence (EI) with fluid (Gf) and crystallized intelligence (Gc; 352 effect sizes; ntotal = 15,333). ...We found that for each branch, the strength of relations with Gf and Gc were equivalent. Understanding emotions has the strongest relation with Gf/Gc combined (ρ = .43, k = 81, n = 11,524), relative to facilitating thought using emotion (ρ = .19, k = 51, n = 7,254), managing emotions (ρ = .20, k = 74, n = 11,359), and perceiving emotion (ρ = .20, k = 79, n = 9,636); for the latter, relations were also moderated by stimulus type. We conclude with implications and recommendations for the study of ability EI.
Evidence is mixed whether fluid intelligence (Gf) is associated with increased or decreased alpha and beta band activity (7–30 Hz). Moreover, the Gf relationship with the delta and theta band ...activity (1–7 Hz) is unknown. We recorded electroencephalographic (EEG) data in 160 healthy adults solving Raven's Advanced Progressive Matrices with a randomized item order to control for item difficulty unaffected by sequential effects. The participants studied each matrix for 30 s before the response bank onset, so we could track the time course of neural activity during problem solving. We measured Gf using six tests. Gf positively correlated with the delta band power, while there was no correlation with the theta band power. For almost all of the participants, we identified the specific slow rhythm frequency, which varied in power as a function of item difficulty. We observed that the lower this frequency, the higher Gf, but only in men. Finally, the alpha and low-beta activity correlated negatively with Gf after we had filtered out the activity during idle intervals (the latter reflecting waiting for the response bank). Overall, the brain activity in the delta, alpha, and beta bands explained 22.6% of Gf variance.
•The delta band power positively correlated with fluid intelligence.•The brain activity in the delta, alpha, and beta bands explained 26% of fluid intelligence variance.•Frequency of slow rhythm activation negatively correlate with intelligence.•The slow rhythm frequency mattered for males, but not for females.
•Zero-order correlations demonstrated positive relationships between fluid intelligence and divergent and convergent thinking.•Level of education and socioeconomic status moderated the relationship ...between creative thinking components and fluid intelligence.•No moderation effects of age, sex, and multilingualism on the fluid intelligence-creative thinking relationship.•Results highlight the need to consider the role of contextual variables in cognitive testing.
The nature of the relationship between creativity and intelligence is a matter of ongoing debate. It has been investigated in various ways using a range of methods, participants, and measures, leading to conflicting empirical findings and theoretical models. Research suggests that fluid intelligence, convergent and divergent thinking are fundamental to both creativity and intelligence. To contribute towards the creativity-intelligence debate, we investigated the relationships between these constructs in an under-researched sample of older adults (aged 64 years +). Furthermore, associations between these constructs may be influenced by demographic qualities, such as age, sex, and number of languages spoken, as well as contextual factors, such as socioeconomic status (SES) and level of education. Thus, we explored whether fluid intelligence is separately related to convergent and divergent thinking and whether the abovementioned demographic and contextual qualities moderate these relationships. Our findings suggest that both years of education and SES are important in fluid intelligence, divergent and convergent thinking, and, therefore, are likely to be influential in creative thinking. Number of languages spoken had some (negative) association with fluid intelligence but was not significantly related to either convergent or divergent thinking. Further, neither age nor sex were significantly associated with fluid intelligence, divergent thinking, or convergent thinking.
This study provides a comprehensive assessment of the associations of personality and intelligence. It presents a meta-analysis (N = 162,636, k = 272) of domain, facet, and item-level correlations ...between personality and intelligence (general, fluid, and crystallized) for the major Big Five and HEXACO hierarchical frameworks of personality: NEO Personality Inventory-Revised, Big Five Aspect Scales, Big Five Inventory-2, and HEXACO Personality Inventory-Revised. It provides the first meta-analysis of personality and intelligence to comprehensively examine (a) facet-level correlations for these hierarchical frameworks of personality, (b) item-level correlations, (c) domain- and facet-level predictive models. Age and sex differences in personality and intelligence, and study-level moderators, are also examined. The study was complemented by four of our own unpublished data sets (N = 26,813) which were used to assess the ability of item-level models to provide generalizable prediction. Results showed that openness (ρ = .20) and neuroticism (ρ = −.09) were the strongest Big Five correlates of intelligence and that openness correlated more with crystallized than fluid intelligence. At the facet level, traits related to intellectual engagement and unconventionality were more strongly related to intelligence than other openness facets, and sociability and orderliness were negatively correlated with intelligence. Facets of gregariousness and excitement seeking had stronger negative correlations, and openness to aesthetics, feelings, and values had stronger positive correlations with crystallized than fluid intelligence. Facets explained more than twice the variance of domains. Overall, the results provide the most nuanced and robust evidence to date of the relationship between personality and intelligence.
Public Significance Statement
This meta-analysis provides a comprehensive examination of the relationship between personality traits and general intelligence. It is the first to meta-analytically compare how intelligence relates to domains, facets, and items on the major hierarchical measures of personality. In so doing, it provides a robust empirical basis for informing discussion of the reciprocal pathways through which personality and intelligence interact.
Green spaces may have beneficial impacts on children's cognition. However, few studies explored the exposure to green spaces beyond residential areas, and their availability, accessibility and uses ...at the same time. The aim of the present study was to describe patterns of availability, accessibility, and uses of green spaces among primary school children and to explore how these exposure dimensions are associated with cognitive development. Exposures to green space near home, school, commuting route, and other daily activity locations were assessed for 1607 children aged 6–11 years from six birth cohorts across Europe, and included variables related to: availability (NDVI buffers: 100, 300, 500 m), potential accessibility (proximity to a major green space: linear distance; within 300 m), and use (play time in green spaces: hours/year), and the number of visits to green spaces (times/previous week). Cognition measured as fluid intelligence, inattention, and working memory was assessed by computerized tests. We performed multiple linear regression analyses on pooled and imputed data adjusted for individual and area-level confounders. Availability, accessibility, and uses of green spaces showed a social gradient that was unfavorable in more vulnerable socioeconomic groups. NDVI was associated with more playing time in green spaces, but proximity to a major green space was not. Associations between green space exposures and cognitive function outcomes were not statistically significant in our overall study population. Stratification by socioeconomic variables showed that living within 300 m of a major green space was associated with improved working memory only in children in less deprived residential areas (β = 0.30, CI: 0.09,0.51), and that more time playing in green spaces was associated with better working memory only in children of highly educated mothers (β per IQR increase in hour/year = 0.10; 95% CI: 0.01, 0.19). However, studying within 300 m of a major green space increased inattention scores in children in more deprived areas (β = 15.45, 95% CI: 3.50, 27.40).
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•Green space availability, accessibility and use are unequal across socioeconomic groups.•Availability more than accessibility seems to foster play time in green spaces.•Accessibility improved working memory in children of higher socioeconomic areas.•Play time in green spaces improved working memory in children of higher educated mothers.•Accessibility increased inattention in children studying in more deprived areas.
Media multitasking in adolescence Cain, Matthew S.; Leonard, Julia A.; Gabrieli, John D. E. ...
Psychonomic bulletin & review,
12/2016, Letnik:
23, Številka:
6
Journal Article
Recenzirano
Odprti dostop
Media use has been on the rise in adolescents overall, and in particular, the amount of media multitasking—multiple media consumed simultaneously, such as having a text message conversation while ...watching TV—has been increasing. In adults, heavy media multitasking has been linked with poorer performance on a number of laboratory measures of cognition, but no relationship has yet been established between media-multitasking behavior and real-world outcomes. Examining individual differences across a group of adolescents, we found that more frequent media multitasking in daily life was associated with poorer performance on statewide standardized achievement tests of math and English in the classroom, poorer performance on behavioral measures of executive function (working memory capacity) in the laboratory, and traits of greater impulsivity and lesser growth mindset. Greater media multitasking had a relatively circumscribed set of associations, and was not related to behavioral measures of cognitive processing speed, implicit learning, or manual dexterity, or to traits of grit and conscientiousness. Thus, individual differences in adolescent media multitasking were related to specific differences in executive function and in performance on real-world academic achievement measures: More media multitasking was associated with poorer executive function ability, worse academic achievement, and a reduced growth mindset.
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