Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures ...of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.
•We draw a distinction between several popular measures of working memory capacity.•We relate working memory to primary and secondary memory, and attention control.•We examine the relationship of ...working memory to reasoning ability.•Many working memory tasks strongly reflect attention control.•The best predictors of fluid intelligence have strong relationships to primary memory.
Working memory capacity is traditionally treated as a unitary construct that can be explained using one cognitive mechanism (e.g., storage, attention control). Several recent studies have, however, demonstrated that multiple mechanisms are needed to explain individual differences in working memory capacity. The present study focuses on three such mechanisms: Maintenance/disengagement in primary memory, retrieval from secondary memory, and attention control. Structural equation modeling reveals that each of these mechanisms is important to explaining individual differences in working memory capacity. Further analyses reveal that the degree to which these mechanisms are apparent may be driven by the type of task used to operationalize working memory capacity. Specifically, complex span (processing and storage) and visual arrays (change detection) performance is strongly related to a person’s attention control, while running memory span (memory for last n items on a list) performance has a relationship to primary memory that is apparent above-and-beyond other working memory tasks. Finally, regardless of the working memory task that is used, it is found that primary and secondary memory fully explain the relationship of working memory capacity to general fluid intelligence.
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.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
•AWPs performance is affected by consistency of relational term and operation.•Regardless from consistency reading comprehension has a mediating role in AWPs.•Inhibition, updating and fluid ...intelligence predicted consistent-inconsistent AWPs.•Consistency effect is related to the efficiency of updating and inhibitory processes.
Children’s performance in arithmetic word problems (AWPs) predicts their academic success and their future employment and earnings in adulthood. Understanding the nature and difficulties of interpreting and solving AWPs is important for theoretical, educational, and social reasons. We investigated the relation between primary school children’s performance in different types of AWPs and their basic cognitive abilities (reading comprehension, fluid intelligence, inhibition, and updating processes). The study involved 182 fourth- and fifth-graders. Participants were administered an AWP-solving task and other tasks assessing fluid intelligence, reading comprehension, inhibition, and updating. The AWP-solving task included comparison problems incorporating either the adverb more than or the adverb less than, which demand consistent or inconsistent operations of addition or subtraction. The results showed that consistent problems were easier than inconsistent problems. Efficiency in solving inconsistent problems is related to inhibition and updating. Moreover, our results seem to indicate that the consistency effect is related to updating processes’ efficiency. Path analyses showed that reading comprehension was the most important predictor of AWP-solving accuracy. Moreover, both executive functions—updating and inhibition—had a distinct and significant effect on AWP accuracy. Fluid intelligence had both direct and indirect effects, mediated by reading comprehension, on the overall measure of AWP performance. These domain-general factors are important factors in explaining children’s performance in solving consistent and inconsistent AWPs.
Nature and Measurement of Attention Control Burgoyne, Alexander P.; Tsukahara, Jason S.; Mashburn, Cody A. ...
Journal of experimental psychology. General,
08/2023, Letnik:
152, Številka:
8
Journal Article
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Individual differences in the ability to control attention are correlated with a wide range of important outcomes, from academic achievement and job performance to health behaviors and emotion ...regulation. Nevertheless, the theoretical nature of attention control as a cognitive construct has been the subject of heated debate, spurred on by psychometric issues that have stymied efforts to reliably measure differences in the ability to control attention. For theory to advance, our measures must improve. We introduce three efficient, reliable, and valid tests of attention control that each take less than 3 min to administer: Stroop Squared, Flanker Squared, and Simon Squared. Two studies (online and in-lab) comprising more than 600 participants demonstrate that the three "Squared" tasks have great internal consistency (avg. = .95) and test-retest reliability across sessions (avg. r = .67). Latent variable analyses revealed that the Squared tasks loaded highly on a common factor (avg. loading = .70), which was strongly correlated with an attention control factor based on established measures (avg. r = .81). Moreover, attention control correlated strongly with fluid intelligence, working memory capacity, and processing speed and helped explain their covariation. We found that the Squared attention control tasks accounted for 75% of the variance in multitasking ability at the latent level, and that fluid intelligence, attention control, and processing speed fully accounted for individual differences in multitasking ability. Our results suggest that Stroop Squared, Flanker Squared, and Simon Squared are reliable and valid measures of attention control. The tasks are freely available online: https://osf.io/7q598/.
Public Significance Statement
Reliably measuring individual differences in attention control has posed a challenge for the field. This paper reports the development and validation of three 90-s tests of attention control, dubbed the "Squared" tasks: Stroop Squared, Flanker Squared, and Simon Squared. The three Squared tasks demonstrated great internal consistency reliability and test-retest reliability, strong evidence for convergent validity with other measures of attention control, and explained a majority of the positive manifold and variance in multitasking ability. The three Squared tasks can be administered online via web browser, E-Prime, or as standalone programs for Mac and Windows (https://osf.io/7q598/). The three Squared tasks demonstrate that it is possible to reliably measure attention control at the observed and latent level by avoiding the use of response time difference scores. Furthermore, the measures reveal that individual differences in attention control can be represented as a unitary latent factor that is highly correlated with complex cognitive task performance.
Background. Paired exercise and cognitive training have the potential to enhance cognition by “priming” the brain and upregulating neurotrophins. Methods. Two-site randomized controlled trial. ...Fifty-two patients >6 months poststroke with concerns about cognitive impairment trained 50 to 70 minutes, 3× week for 10 weeks with 12-week follow-up. Participants were randomized to 1 of 2 physical interventions: Aerobic (>60% VO2peak using <10% body weight–supported treadmill) or Activity (range of movement and functional tasks). Exercise was paired with 1 of 2 cognitive interventions (computerized dual working memory training COG or control computer games Games). The primary outcome for the 4 groups (Aerobic + COG, Aerobic + Games, Activity + COG, and Activity + Games) was fluid intelligence measured using Raven’s Progressive Matrices Test administered at baseline, posttraining, and 3-month follow-up. Serum neurotrophins collected at one site (N = 30) included brain-derived neurotrophic factor (BDNF) at rest (BDNFresting) and after a graded exercise test (BDNFresponse) and insulin-like growth factor–1 at the same timepoints (IGF-1rest, IGF-1response). Results. At follow-up, fluid intelligence scores significantly improved compared to baseline in the Aerobic + COG and Activity + COG groups; however, only the Aerobic + COG group was significantly different (+47.8%) from control (Activity + Games −8.5%). Greater IGF-1response at baseline predicted 40% of the variance in cognitive improvement. There was no effect of the interventions on BDNFresting or BDNFresponse; nor was BDNF predictive of the outcome. Conclusions. Aerobic exercise combined with cognitive training improved fluid intelligence by almost 50% in patients >6 months poststroke. Participants with more robust improvements in cognition were able to upregulate higher levels of serum IGF-1 suggesting that this neurotrophin may be involved in behaviorally induced plasticity.
How to play 20 questions with nature and lose Katz, Benjamin; Shah, Priti; Meyer, David E.
Proceedings of the National Academy of Sciences,
10/2018, Letnik:
115, Številka:
40
Journal Article
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Despite dozens of empirical studies and a growing body of meta-analytic work, there is little consensus regarding the efficacy of cognitive training. In this review, we examine why this substantial ...corpus has failed to answer the often-asked question, “Does cognitive training work?” We first define cognitive training and discuss the general principles underlying training interventions. Next, we review historical interventions and discuss how findings from this early work remain highly relevant for current cognitive-training research. We highlight a variety of issues preventing real progress in understanding the underlying mechanisms of training, including the lack of a coherent theoretical framework to guide training research and methodological issues across studies and meta-analyses. Finally, suggestions for correcting these issues are offered in the hope that we might make greater progress in the next 100 y of cognitive-training research.
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.
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