Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

Association of domain-general speed of information processing with spoken language outcomes in prelingually-deaf children with cochlear implants

Spoken language development after pediatric cochlear implantation requires rapid and efficient processing of novel, degraded auditory signals and linguistic information. These demands for rapid adaptation tax the information processing speed ability of children who receive cochlear implants. This study investigated the association of speed of information processing ability with spoken language outcomes after cochlear implantation in prelingually deaf children aged 4-6 years. Two domain-general (visual, non-linguistic) speed of information processing measures were administered to 21 preschool-aged children with cochlear implants and 23 normal-hearing peers. Measures of speech recognition, language (vocabulary and comprehension), nonverbal intelligence, and executive functioning skills were also obtained from each participant. Speed of information processing was positively associated with speech recognition and language skills in preschool-aged children with cochlear implants but not in normal-hearing peers. This association remained significant after controlling for hearing group, age, nonverbal intelligence, and executive functioning skills. These findings are consistent with models suggesting that domain-general, fast-efficient information processing speed underlies adaptation to speech perception and language learning following implantation. Assessment and intervention strategies targeting speed of information processing may provide better understanding and development of speech-language skills after cochlear implantation.

Word or pseudoword? The lexicality effect in naming and lexical decision tasks during advanced aging

Although there is evidence that recognizing pseudowords is more difficult than recognizing words during childhood, adulthood, and early old age (60-75 years), it is not yet clear what happens during advanced aging or the fourth age, a stage when the decline of fluid intelligence strongly affects processing speed, but a good performance of crystallized intelligence is described through an increase in vocabulary and knowledge. The objective of this study was to determine the lexicality effect in advanced aging, specifically exploring how the ability to recognize words and pseudowords (ortho-phonologically plausible for Spanish) is affected during the third and fourth-ages. The lexicality effect was measured using naming and lexical decision tasks. Response time and accuracy were compared between a fourth-age group (80+ years) and two third-age groups (60-69 and 70-79 years) through linear regression models. The results showed that, in general, the fourth-age group had longer response times and reduced accuracy when recognizing words and pseudowords. Moreover, they showed a significant lexicality effect (which increases from the third- age onwards), reflected in higher costs during pseudoword recognition, especially when the task required more cognitive effort (lexical decision task). These results were consistent with the impact of the deterioration of fluid intelligence on the speed of lexical recognition and with the better performance that crystallized intelligence can generate on accuracy, especially in the early stages of old age. Additionally, this study supports the fact that pseudoword recognition resists cognitive decline, as accentuated deterioration is visualized only after 80 years.

How robust is the relationship between neural processing speed and cognitive abilities?

Individual differences in processing speed are consistently related to individual differences in cognitive abilities, but the mechanisms through which a higher processing speed facilitates reasoning remain largely unknown. To identify these mechanisms, researchers have been using latencies of the event-related potential (ERP) to study how the speed of cognitive processes associated with specific ERP components is related to cognitive abilities. Although there is some evidence that latencies of ERP components associated with higher-order cognitive processes are related to intelligence, results are overall quite inconsistent. These inconsistencies likely result from variations in analytic procedures and little consideration of the psychometric properties of ERP latencies in relatively small sample studies. Here we used a multiverse approach to evaluate how different analytical choices regarding references, low-pass filter cutoffs, and latency measures affect the psychometric properties of P2, N2, and P3 latencies and their relations with cognitive abilities in a sample of 148 participants. Latent correlations between neural processing speed and cognitive abilities ranged from -.49 to -.78. ERP latency measures contained about equal parts of measurement error variance and systematic variance, and only about half of the systematic variance was related to cognitive abilities, whereas the other half reflected nuisance factors. We recommend addressing these problematic psychometric properties by recording EEG data from multiple tasks and modeling relations between ERP latencies and covariates in latent variable models. All in all, our results indicate that there is a substantial and robust relationship between neural processing speed and cognitive abilities when those issues are addressed.

The block design subtest of the Wechsler adult intelligence scale as a possible non-verbal proxy of cognitive reserve

Objectives

To investigate the potential of the Block design subtest of the Wechsler Adults Intelligence Scale as a non-verbal proxy of cognitive reserve.

Method

A total of 391 cognitively unimpaired participants were included in this study. The association between the Block design subtest and the Information subtest (an established verbal proxy of cognitive reserve) from the WAIS, as well as the association of the two subtests with a Cognitive Reserve Questionnaire (CRQ) were tested. In addition, multiple linear regression models were conducted to investigate the association of the Block design and Information subtests with cognitive performance. The capacity of the Block design subtest to minimize the negative effect of an older age over cognitive performance was also assessed and this effect was compared with that of the Information subtest. The four cognitive domains included were: verbal memory, visual-visuospatial memory, executive-premotor functions and processing speed.

Results

The Block design subtest correlated positively with both the Information subtest and the CRQ. A statistically significant association was observed between the Block design subtest and all four cognitive domains. Higher scores in the Block design subtest minimized the negative effect of aging on the cognitive domains of visual-visuospatial memory and executive-premotor functions, in a similar way to the results obtained for the Information subtest.

Conclusion

The Block design subtest is significantly correlated with two established proxies of cognitive reserve: it correlates with cognitive performance and high scores in Block design have the capacity to minimize the negative effect of an older age on cognitive performance. Therefore, the results suggest that the corrected Block design subtest could be considered as a non-verbal proxy of cognitive reserve.

Visual word recognition among oldest old people: The effect of age and cognitive load

During the fourth age, a marked physiological deterioration and critical points of dysfunction are observed, during which cognitive performance exhibits a marked decline in certain skills (fluid intelligence) but good performance of others (crystallized intelligence). Experimental evidence describes important constraints on word production during old age, accompanied by a relative stabilization of speech comprehension. However, cognitive changes associated with advanced aging could also affect comprehension, particularly word recognition. The present study examines how the visual recognition of words is affected during the fourth age when tasks involving different cognitive loads are applied. Through linear regression models, performance was compared between two third-age groups and a fourth-age group on reaction time (RT) and accuracy in naming, priming and lexical decision experiments. The fourth-age group showed a significant RT increase in all experiments. In contrast, accuracy was good when the task involved a low cognitive demand (Experiments 1 and 2); however, when a decisional cognitive factor was included (Experiment 3), the fourth-age group performed significantly worse than the younger third-age group. We argue that the behavior observed among fourth-age individuals is consistent with an unbalanced cognitive configuration, in which the fluid intelligence deficit significantly reduces the speed necessary to recognize words, independent of the cognitive load associated with the test. In contrast, the maintenance in crystallized intelligence improves the accuracy of the process, strengthening linguistic functionality in the advanced stages of old age.

University students with attention deficit hyperactivity disorder (ADHD): a consensus statement from the UK Adult ADHD Network (UKAAN)

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is associated with poor educational outcomes that can have long-term negative effects on the mental health, wellbeing, and socio-economic outcomes of university students. Mental health provision for university students with ADHD is often inadequate due to long waiting times for access to diagnosis and treatment in specialist National Health Service (NHS) clinics. ADHD is a hidden and marginalised disability, and within higher education in the UK, the categorisation of ADHD as a specific learning difference (or difficulty) may be contributing to this.

AIMS

This consensus aims to provide an informed understanding of the impact of ADHD on the educational (or academic) outcomes of university students and highlight an urgent need for timely access to treatment and management.

METHODS

The UK Adult ADHD Network (UKAAN) convened a meeting of practitioners and experts from England, Wales, and Scotland, to discuss issues that university students with ADHD can experience or present with during their programme of studies and how best to address them. A report on the collective analysis, evaluation, and opinions of the expert panel and published literature about the impact of ADHD on the educational outcomes of university students is presented.

RESULTS

A consensus was reached that offers expert advice, practical guidance, and recommendations to support the medical, education, and disability practitioners working with university students with ADHD.

CONCLUSIONS

Practical advice, guidance, and recommendations based on expert consensus can inform the identification of ADHD in university students, personalised interventions, and educational support, as well as contribute to existing research in this topic area. There is a need to move away from prevailing notions within higher education about ADHD being a specific learning difference (or difficulty) and attend to the urgent need for university students with ADHD to have timely access to treatment and support. A multimodal approach can be adapted to support university students with ADHD. This approach would view timely access to treatment, including reasonable adjustments and educational support, as having a positive impact on the academic performance and achievement of university students with ADHD.

Mental speed is high until age 60 as revealed by analysis of over a million participants

Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion model to extract interpretable cognitive components from raw response time data. We apply our model to cross-sectional data from 1.2 million participants to examine age differences in cognitive parameters. To efficiently parse this large dataset, we apply a Bayesian inference method for efficient parameter estimation using specialized neural networks. Our results indicate that response time slowing begins as early as age 20, but this slowing was attributable to increases in decision caution and to slower non-decisional processes, rather than to differences in mental speed. Slowing of mental speed was observed only after approximately age 60. Our research thus challenges widespread beliefs about the relationship between age and mental speed.

STATE OF THE MAIN PSYCHOPHYSIOLOGICAL FUNCTIONS IN MILITARY SERVANTS OF DIFFERENT AGE GROUPS

To discover age-related changes in the simple sensorimotor reaction (SSMR), choice reaction (CR), functional mobility of nervous processes (FMNP) and brain productivity (BP), as well as to determine the stress index (SI) of regulatory systems during performance of these tests. Forty-seven healthy volunteers, representatives of military professions, aged 18–54 were divided into three groups (first group – 18–23 years, n=16; second group – 24– 34 years, n=19; third group – 35–54 years, n=12) and performed original computer tests to determine SSMR, CR, FMNP and BP. An electrocardiogram (ECG) was recorded in parallel. Although the rate of SSMR and CR did not differ for participants of three groups, the SI was significantly higher in the third group, compared with the first group (p<0.01) during SSMR. During CR performance it was significantly higher for the third and second groups compared with the first one (p<0.01). The FMNP index was significantly higher in the third group compared to the first one (p<0.05), and BP had the highest values for the second group compared to the first one (p<0.01). During performance of BP test, the SI did not differ in three groups, and during the test for FMNP it was significantly higher in the third group compared to the first one (p<0.01). The effectiveness of simple tasks (SSMR and CR) does not change with age, but their level is maintained due to increase of the SI of regulatory systems, i.e. increasing sympathetic tone. The FMNP value mainly depends on the individual CNS characteristics than on age. The highest level of FMNP was in the elderly. They also had elevated levels of the SI of regulatory systems. The reason of this could be associated with the high activity of cortical neurons, which leads to intensification of metabolic processes and changes in the level of autonomic supply. The lowest level of relative error, i.e. the highest level of BP was found in the middle age group. At the same time, no differences were found in the SI of regulatory systems between servicemen of different age groups during BP test performance.

Educational and economic returns to cognitive ability in low- and middle-income countries: A systematic review

There is growing interest to use early cognitive ability to predict schooling and employment outcomes in low- and middle-income countries (LMICs). Rather than using educational attainment and school enrollment as predictors of future economic growth or of improving an individual's earning potential, mounting evidence suggests that cognitive ability may be a better predictor. The relationship between cognitive ability, education, and employment are essential to predict future development in LMICs. We performed a systematic literature review and meta-analysis of the evidence regarding the relationship between cognitive ability and educational outcomes, and between cognitive ability and economic outcomes across LMICs. We searched peer-reviewed studies since 2000 that quantitatively measured these relationships. Based on an initial search of 3,766 records, we identified 14 studies, including 8 studies that examined the cognition-education link and 8 studies that assessed cognition-employment returns in LMICs. Identified studies showed that higher cognitive ability increased the probability of school enrollment, academic achievement, and educational attainment across LMICs. A meta-analysis of returns to wages from cognitive ability suggested that a standard deviation increase in cognitive test scores was associated with a 4.5% (95% CI 2.6%-9.6%) increase in wages. Investments into early cognitive development could play a critical role in improving educational and economic outcomes in LMICs. Further research should focus particularly in low-income countries with the least evidence, and examine the impact on education and economic outcomes by cognitive domains to provide more robust evidence for policy makers to take action.

Two Sides of the Same Coin: Fluid Intelligence and Crystallized Intelligence as Cognitive Reserve Predictors of Social Cognition and Executive Functions Among Vulnerable Elderly People

The concept of cognitive reserve -CR- postulates two forms that prevent cognitive impairment: neural reserve and neural compensation. Both have been primarily linked to the protective role played by genetic factors, educational level, occupation or socioeconomic status. Though it is true that it has been related to executive functions, so far very little attention has been paid to its predictive capacity with other variables more related to social cognition and psychosocial adaptation. Considering socially vulnerable contexts with reduced cultural capital and educational levels, the neural reserve function would be the most relevant and best predictor of aspects related to social cognition and executive functions. We suggest that variables such as fluid and crystallized intelligence influence social cognition and executive functions. This study included a sample of 27 participants over 60 years old from varied contexts of social vulnerability. The procedure included data collection using various cognitive measures. Results show that elderly people with high intelligence-mainly fluid intelligence-have better executive functions, emotional recognition and theory of mind. These results focus on cognitive reserve and its importance because they show that elderly people in vulnerable contexts who strengthen these aspects protect themselves against the deterioration of cognitive skills. This study is the first preliminary research to present a relationship between cognitive reserve and social cognition factors in elderly subjects. Fluid intelligence functions as a highly related factor to protect the performance of executive functions, along with other social-cognitive factors relevant to facilitating the conditions of social adaptation.

Stability and Change in Diffusion Model Parameters over Two Years

In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research.

A diffusion model analysis of belief bias: Different cognitive mechanisms explain how cognitive abilities and thinking styles contribute to conflict resolution in reasoning

Recent results have challenged the widespread assumption of dual process models of belief bias that sound reasoning relies on slow, careful reflection, whereas biased reasoning is based on fast intuition. Instead, parallel process models of reasoning suggest that rule- and belief-based problem features are processed in parallel and that reasoning problems that elicit a conflict between rule- and belief-based problem features may also elicit more than one Type 1 response. This has important implications for individual-differences research on reasoning, because rule-based responses by certain individuals may reflect that these individuals were either more likely to give a rule-based default response or that they successfully inhibited and overrode a belief-based default response. In two studies, we used the diffusion model to describe decision making in a transitive reasoning task. In Study 1, 41 participants were asked to evaluate conclusions based on their validity. In Study 2, 133 participants evaluated conclusions based on their validity or believability. We tested which diffusion model parameters reflected conflict resolution and related those model parameters to individual differences in cognitive abilities and thinking styles. Individual differences in need for cognition predicted successful conflict resolution under logic instruction, which suggests that a disposition to engage in reflective thinking facilitates the inhibition and override of Type 1 responses. Intelligence, however, was negatively related to successful conflict resolution under belief instruction, which suggests that individuals with high cognitive abilities quickly generated a higher-level logical response that interfered with their ability to evaluate lower-level intrinsic problem features. Taken together, this double dissociation indicates that cognitive abilities and thinking styles affect the processing of conflict information through different mechanisms and at different stages: Greater cognitive abilities facilitate the efficient creation of decoupled problem representations, whereas a greater disposition to engage in critical thinking facilitates the detection and override of Type 1 responses.

Comparing Eight Parameter Estimation Methods for the Ratcliff Diffusion Model Using Free Software

The Ratcliff Diffusion Model has become an important and widely used tool for the evaluation of psychological experiments. Concurrently, numerous programs and routines have appeared to estimate the model's parameters. The present study aims at comparing some of the most widely used tools with special focus on freely available routines (i.e., open source). Our simulations show that (1) starting point and non-decision time were recovered better than drift rate, (2) the Bayesian approach outperformed all other approaches when the number of trials was low, (3) the Kolmogorov-Smirnov and χ² approaches revealed more bias than Bayesian or Maximum Likelihood based routines, and (4) EZ produced substantially biased estimates of threshold separation, non-decision time and drift rate when starting point z ≠ a/2. We discuss the implications for the choice of parameter estimation approaches for real data and suggest that if biased starting point cannot be excluded, EZ will produce deviant estimates and should be used with great care.

Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains?

In comparison to young adults, middle-aged and old people show lower scores in intelligence tests and slower response times in elementary cognitive tasks. Whether these well-documented findings can both be attributed to a general cognitive slow-down across the life-span has become subject to debate in the last years. The drift diffusion model can disentangle three main process components of binary decisions, namely the speed of information processing, the conservatism of the decision criterion and the non-decision time (i.e., time needed for processes such as encoding and motor response execution). All three components provide possible explanations for the association between response times and age. We present data from a broad study using 18 different response time tasks from three different content domains (figural, numeric, verbal). Our sample included people between 18 to 62 years of age, thus allowing us to study age differences across young-adulthood and mid-adulthood. Older adults generally showed longer non-decision times and more conservative decision criteria. For speed of information processing, we found a more complex pattern that differed between tasks. We estimated mediation models to investigate whether age differences in diffusion model parameters account for the negative relation between age and intelligence, across different intelligence process domains (processing capacity, memory, psychometric speed) and different intelligence content domains (figural, numeric, verbal). In most cases, age differences in intelligence were accounted for by age differences in non-decision time. Content domain-general, but not content domain-specific aspects of non-decision time were related to age. We discuss the implications of these findings on how cognitive decline and age differences in mental speed might be related.

Neurocognitive Psychometrics of Intelligence: How Measurement Advancements Unveiled the Role of Mental Speed in Intelligence Differences

More intelligent individuals typically show faster reaction times. However, individual differences in reaction times do not represent individual differences in a single cognitive process but in multiple cognitive processes. Thus, it is unclear whether the association between mental speed and intelligence reflects advantages in a specific cognitive process or in general processing speed. In this article, we present a neurocognitive-psychometrics account of mental speed that decomposes the relationship between mental speed and intelligence. We summarize research employing mathematical models of cognition and chronometric analyses of neural processing to identify distinct stages of information processing strongly related to intelligence differences. Evidence from both approaches suggests that the speed of higher-order processing is greater in smarter individuals, which may reflect advantages in the structural and functional organization of brain networks. Adopting a similar neurocognitive-psychometrics approach for other cognitive processes associated with intelligence (e.g., working memory or executive control) may refine our understanding of the basic cognitive processes of intelligence.