General fluid/inductive reasoning battery for a high-ability population

Measuring Process Factors of Fluid Reasoning Using Multidimensional Computerized Adaptive Testing

Although many fluid reasoning (Gf) tests have been developed, there is a lack of figural tests measuring its lower-order process factors simultaneously. The present article introduces the development of the Multidimensional Induction-Deduction Computerized Adaptive Test (MID-CAT) to measure two process factors of Gf. The MID-CAT is designed to provide an instrument that is flexible, efficient, and entirely free for non-commercial use. We created 530 items and administered them to a sample of N = 2,247. Items were fitted and calibrated using the Rasch model. The results indicate that the final item pool has a wide range of difficulties that could precisely measure a wide range of test-takers' abilities. A simulation study also indicates that MID-CAT provides greater measurement efficiency than separate-unidimensional CAT or fixed-item test. In the discussion, we provide perspectives on how the MID-CAT can be used for future research.

Improving the Reliability of Cognitive Task Measures: A Narrative Review

Cognitive tasks are capable of providing researchers with crucial insights into the relationship between cognitive processing and psychiatric phenomena. However, many recent studies have found that task measures exhibit poor reliability, which hampers their usefulness for individual differences research. Here, we provide a narrative review of approaches to improve the reliability of cognitive task measures. Specifically, we introduce a taxonomy of experiment design and analysis strategies for improving task reliability. Where appropriate, we highlight studies that are exemplary for improving the reliability of specific task measures. We hope that this article can serve as a helpful guide for experimenters who wish to design a new task, or improve an existing one, to achieve sufficient reliability for use in individual differences research.

Should Intelligence Tests Be Speeded or Unspeeded? A Brief Review of the Effects of Time Pressure on Response Processes and an Experimental Study with Raven's Matrices

Intelligence tests are often performed under time constraints for practical reasons, but the effects of time pressure on reasoning performance are poorly understood. The first part of this work provides a brief review of major expected effects of time pressure, which includes forcing participants to skip items, convoking a mental speed factor, constraining response times, qualitatively altering cognitive processing, affecting anxiety and motivation, and interacting with individual differences. The second part presents data collected with Raven's matrices under three conditions of speededness to provide further insight into the complex effects of time pressure, with three major findings. First, even mild time pressure (with enough time available for all participants to complete the task at a leisurely pace) induced speeding throughout the whole task, starting with the very first item, and participants sped up more than was actually required. Second, time pressure came with lower confidence and poorer strategy use and a substantial decrease of accuracy (d = 0.35), even when controlling for response time at the item level-indicating a detrimental effect on cognitive processing beyond speeding. Third, time pressure disproportionately reduced response times for difficult items and participants with high ability, working memory capacity, or need for cognition, although this did not differentially affect ability estimates. Overall, both the review and empirical sections show that the effects of time pressure go well beyond forcing participants to speed or skip the last few items and make even mild time constraints inadvisable when attempting to measure maximal performance, especially for high-performing samples.

Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach

Central to modern neuroscientific theories of human intelligence is the notion that general intelligence depends on a primary brain region or network, engaging spatially localized (rather than global) neural representations. Recent findings in network neuroscience, however, challenge this assumption, providing evidence that general intelligence may depend on system-wide network mechanisms, suggesting that local representations are necessary but not sufficient to account for the neural architecture of human intelligence. Despite the importance of this key theoretical distinction, prior research has not systematically investigated the role of local versus global neural representations in predicting general intelligence. We conducted a large-scale connectome-based predictive modeling study (N = 297), administering resting-state fMRI and a comprehensive cognitive battery to evaluate the efficacy of modern neuroscientific theories of human intelligence, including spatially localized theories (Lateral Prefrontal Cortex Theory, Parieto-Frontal Integration Theory, and Multiple Demand Theory) and recent global accounts (Process Overlap Theory and Network Neuroscience Theory). The results of our study demonstrate that general intelligence can be predicted by local functional connectivity profiles but is most robustly explained by global profiles of whole-brain connectivity. Our findings further suggest that the improved efficacy of global theories is not reducible to a greater strength or number of connections, but instead results from considering both strong and weak connections that provide the basis for intelligence (as predicted by the Network Neuroscience Theory). Our results highlight the importance of considering local neural representations in the context of a global information-processing architecture, suggesting future directions for theory-driven research on system-wide network mechanisms underlying general intelligence.

The Precipitous Decline in Reasoning and Other Key Abilities with Age and Its Implications for Federal Judges

U. S. Supreme Court justices and other federal judges are, effectively, appointed for life, with no built-in check on their cognitive functioning as they approach old age. There is about a century of research on aging and intelligence that shows the vulnerability of processing speed, fluid reasoning, visual-spatial processing, and working memory to normal aging for men and women at all levels of education; even the maintained ability of crystallized knowledge declines in old age. The vulnerable abilities impact a person's decision-making and problem solving; crystallized knowledge, by contrast, measures a person's general knowledge. The aging-IQ data provide a rationale for assessing the key cognitive abilities of anyone who is appointed to the federal judiciary. Theories of multiple cognitive abilities and processes, most notably the Cattell-Horn-Carroll (CHC) model, provide a well-researched blueprint for interpreting the plethora of findings from studies of IQ and aging. Sophisticated technical advances in test construction, especially in item-response theory and computerized-adaptive testing, allow for the development of reliable and valid theory-based tests of cognitive functioning. Such assessments promise to be a potentially useful tool for evaluating federal judges to assess the impact of aging on their ability to perform at a level their positions deserve, perhaps to measure their competency to serve the public intelligently. It is proposed that public funding be made available to appoint a panel of experts to develop and validate an array of computerized cognitive tests to identify those justices who are at risk of cognitive impairment.

The Effects of Selective Survival on Black Adults' Cognitive Development

OBJECTIVES

The theory of selective survival suggests that possibly around 70-75 years of age, Blacks may display substantive changes in their pattern of cognitive decline. This study examined the age-graded pattern of cognitive decline within older Blacks by describing a trend that characterizes differences in the change of cognitive decline from ages 51.5 to 95.5, and hypothesized that this age-graded pattern is nonlinear.

METHOD

Utilizing 2 waves of longitudinal data from the Baltimore Study of Black Aging, this study used multilevel modeling to test whether the interaction between age and the 3-year study period (time between waves) had a positive effect on changes in inductive reasoning, declarative memory, working memory, and perceptual speed.

RESULTS

A significant positive interaction between age and wave was found for inductive reasoning, demonstrating an age-grade pattern of change/decline in cognitive pattern for Blacks aged 51.5-95.4. Simple slope probing via the Johnson-Neyman Technique suggested that Black adults ~64 years and younger experienced significant decline in inductive reasoning across study time, whereas for those older than 63.71, the decline was nonsignificant. No significant age-wave interactions were found for declarative memory, working memory, or perceptual speed.

DISCUSSION

Findings suggest a selective survival effect for inductive reasoning ability among Blacks. With decline evident so early, common cognitive intervention programs targeting adults 65+ may come too late for Blacks, signifying the importance and urgency for early health interventions and public policy designed to promote cognitive reserve.

Divergent Research Methods Limit Understanding of Working Memory Training

Working memory training has been a hot topic over the last decade. Although studies show benefits in trained and untrained tasks as a function of training, there is an ongoing debate on the efficacy of working memory training. There have been numerous meta-analyses put forth to the field, some finding overall broad transfer effects while others do not. However, discussion of this research typically overlooks specific qualities of the training and transfer tasks. As such, there has been next to no discussion in the literature on what training and transfer tasks features are likely to mediate training outcomes. To address this gap, here, we characterized the broad diversity of features employed in N-back training tasks and outcome measures in published working memory training studies. Extant meta-analyses have not taken into account the diversity of methodology at this level, primarily because there are too few studies using common methods to allow for a robust meta-analysis. We suggest that these limitations preclude strong conclusions from published data. In order to advance research on working memory training, and in particular, N-back training, more studies are needed that systematically compare training features and use common outcome measures to assess transfer effects.