Cognitive reserve, depressive symptoms, obesity, and change in employment status predict mental processing speed and executive function after COVID-19.

The risk factors for post-COVID-19 cognitive impairment have been poorly described. This study aimed to identify the sociodemographic, clinical, and lifestyle characteristics that characterize a group of post-COVID-19 condition (PCC) participants with neuropsychological impairment. The study sample included 426 participants with PCC who underwent a neurobehavioral evaluation. We selected seven mental speed processing and executive function variables to obtain a data-driven partition. Clustering algorithms were applied, including K-means, bisecting K-means, and Gaussian mixture models. Different machine learning algorithms were then used to obtain a classifier able to separate the two clusters according to the demographic, clinical, emotional, and lifestyle variables, including logistic regression with least absolute shrinkage and selection operator (LASSO) (L1) and Ridge (L2) regularization, support vector machines (linear/quadratic/radial basis function kernels), and decision tree ensembles (random forest/gradient boosting trees). All clustering quality measures were in agreement in detecting only two clusters in the data based solely on cognitive performance. A model with four variables (cognitive reserve, depressive symptoms, obesity, and change in work situation) obtained with logistic regression with LASSO regularization was able to classify between good and poor cognitive performers with an accuracy and a weighted averaged precision of 72%, a recall of 73%, and an area under the curve of 0.72. PCC individuals with a lower cognitive reserve, more depressive symptoms, obesity, and a change in employment status were at greater risk for poor performance on tasks requiring mental processing speed and executive function. Study registration: www.ClinicalTrials.gov , identifier NCT05307575.

Processing speed in temporal lobe epilepsy. A scoping review.

BACKGROUND: Impaired processing speed (PS) can affect patients with temporal lobe epilepsy (TLE). However, it is usually considered a nonspecific clinical feature and is not measured, but this raises lexical and methodological problems. This review aims to evaluate the existing terminology and assessment methods of PS in patients with TLE. METHODS: A scoping review was conducted based on the extended guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. The electronic literature search was conducted on Medline-PubMed, American Psychological Association-PsycINFO, Elton Bryson Stephens Company, and Google Scholar, using the keywords "temporal lobe epilepsy" and "speed" or "slowing" plus "processing," "cognitive," "psychomotor," or "mental." Peer-reviewed articles published before December 2022 were analyzed if they were in English, including patients older than 14 years and at least one neuropsychological measure, reported original research focused on PS and had the selected keywords in the title, keywords, and abstract. RESULTS: Seven articles published between December 2004 and September 2021 were selected. The terms "processing speed," "psychomotor speed," and "information processing speed," based on similar theoretical constructs, were the most frequently used. Assessment methods included non-computerized or paper-and-pencil tests (WAIS-III Digit Symbol and Symbol Search subtests, Purdue Pegboard and Grooved Pegboard Tests, Trail Making Test and Stroop Color-Word Test) and computerized tests (Sternberg Memory Scanning Test, Pattern Comparison Processing Speed, Computerized Visual Searching). In some studies, impairment was associated with white and gray matter damage in the brain, independent of clinical and treatment variables. CONCLUSION: Clinical research on TLE has focused inconsistently on PS. Different evaluation terms and methods have been used while referring to similar theoretical constructs. These findings highlight a gap between the clinical importance of PS and its assessment. Studies are needed to share terms and tools among clinical centers and clarify the position of PS in the TLE phenotype.

How Speededness of a Reasoning Test and the Complexity of Mental Speed Tasks Influence the Relation between Mental Speed and Reasoning Ability.

Although previous research has consistently reported a positive association between mental speed and reasoning ability, it remains unclear whether the magnitude of this association depends on whether the reasoning test is administered with or without a time limit. In addition, it is unknown how mental speed task complexity affects the mental speed-reasoning association when the effects of time limitations in the reasoning test (labeled "speededness") are controlled for. The present study examined these questions in a sample of 200 participants who completed the time-limited Culture Fair Test (CFT) and a Hick task with three levels of complexity to measure mental speed. Results showed that the latent correlation between mental speed and reasoning was slightly lower when the effect of speededness in reasoning was statistically controlled for. However, for both controlled and uncontrolled reasoning, the correlation with mental speed was of medium size and statistically significant. When reasoning was controlled for the effects of speededness, only complexity-related mental speed aspects were correlated with reasoning, whereas basic mental speed aspects were correlated with the speededness factor and unrelated to reasoning. These findings demonstrate that time limitations in reasoning tests and complexity in mental speed tasks affect the magnitude of the mental speed-reasoning association.

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.

Is Flexibility More than Fluency and Originality?

Flexibility (i.e., the number of categorically different ideas), fluency (i.e., the answer quantity), and originality (i.e., the quality of ideas) are essential aspects of the ability to think divergently. Theoretically, fluency and ideational flexibility tasks are akin to one another. However, flexibility was also considered to be uniquely related to working memory capacity due to the task requirements involved in generating diverse answers (e.g., self-monitoring, suppression, and category generation). Given that the role of working memory is strengthened in flexibility tasks relative to fluency and originality tasks, flexibility should be more strongly related with working memory. Additionally, mental speed should show a similar pattern of results because mental speed has been previously related to task complexity. Based on a sample of N = 409 adults (Mage = 24.01 years), we found in latent variable models that fluency/originality strongly predicts flexibility and accounts for 61% of its variance. Creative flexibility was unrelated to working memory and mental speed after controlling for fluency/originality. Additionally, the residual of a latent flexibility factor was unrelated to self-reported creative activities. We concluded that flexibility, as measured here, can be deemed primarily a method factor that did not show value over and above fluency/originality as assessed in traditional fluency and originality tasks. We discussed perspectives for disentangling trait and method variance in flexibility tasks.

Binding Costs in Processing Efficiency as Determinants of Cognitive Ability.

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person's ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall-1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the relation between reaction time tasks and working memory capacity hinges on the complexity of the reaction time tasks. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.

Piagetian Tasks and Psychometric Intelligence: Different or Similar Constructs?

Research on cognitive ability is done in different paradigms. In the Piagetian paradigm, cognitive ability focuses on cognitive development along qualitative stages. Interactive real scenarios, "Piagetian tasks", are constructed for measurement. According to age, tasks differing in complexity are applied in individual measurements. In the psychometric paradigm, the investigation of cognitive ability focuses on individual differences. Intelligence is seen as a quantitative construct with gradual differences between persons and ages. Paper-and-pencil tests with items differing in difficulty are used for IQ measurement of single persons or school classes. However, do those tasks measure two distinct cognitive abilities? Solving tasks in both approaches requires basic (speed, working memory) and complex cognitive abilities (reasoning, understanding). Regarding empirical relationships, we used three Austrian samples (in kindergarten four to six years old N = 40, in primary school six to eight years old N = 40, and nine to ten years old N = 41). They were tested with psychometric tests (Raven CPM or SPM) and Piagetian tasks. In addition, mental speed (ZVT) was measured in the two school samples. The average observed correlation between IQ and Piagetian tasks was r = .51. In factor analyses, the tests loaded on a common factor of general intelligence. Further analyses revealed that mental speed is correlated more strongly with psychometric (r = .50) than with Piagetian tasks (r = .39), while Piagetian tasks are more related to parental education indicators (speed: r = .11, Raven: r = .20, Piaget: r = .25).

An Investigation of the Slope Parameters of Reaction Times and P3 Latencies in the Sternberg Memory Scanning Task - A Fixed-Links Model Approach.

The speed of short-term memory scanning is thought to be captured in the slope of the linear function of mean reaction times (RTs) regressed on set size in the Sternberg memory scanning task (SMST). Individual differences in the slope parameter have been hypothesized to correlate with general intelligence (g). However, this correlation can usually not be found. This present study chose a fixed-links model (FLM) approach to re-evaluate the RT slope parameter on a latent level in a sample of 102 participants aged 18 to 61 years who completed the SMST with set sizes 1, 3, and 5. The same was tried for P3 latencies to investigate whether or not both parameters measure the same cognitive processes in the SMST, and to assess the usability of both slopes to predict g. For RTs, a linear increase with set size was found. The slope of mean RTs correlated with g on a manifest level already. The FLM approach could better reveal this relationship with the correlation between the slope and g being substantially higher. For P3 latencies, we found no evidence for a linear increase, but a general increase from the smallest set size to the two larger ones. This indicates that RTs and P3 latencies do not measure the same cognitive processes in the SMST. The FLM proved suitable to investigate the association between the speed of short-term memory scanning and intelligence.

Do Executive Attentional Processes Uniquely or Commonly Explain Psychometric g and Correlations in the Positive Manifold? A Structural Equation Modeling and Network-Analysis Approach to Investigate the Process Overlap Theory.

One of the best-established findings in intelligence research is the pattern of positive correlations among various intelligence tests. Although this so-called positive manifold became the conceptual foundation of many theoretical accounts of intelligence, the very nature of it has remained unclear. Only recently, Process Overlap Theory (POT) proposed that the positive manifold originated from overlapping domain-general, executive processes. To test this assumption, the functional relationship between different aspects of executive attention and the positive manifold was investigated by re-analyzing an existing dataset (N = 228). Psychometric reasoning, speed, and memory performance were assessed by a short form of the Berlin Intelligence Structure test. Two aspects of executive attention (sustained and selective attention) and speed of decision making were measured by a continuous performance test, a flanker task, and a Hick task, respectively. Traditional structural equation modeling, representing the positive manifold by a g factor, as well as network analyses, investigating the differential effects of the two aspects of executive attention and speed of decision making on the specific correlations of the positive manifold, suggested that selective attention, sustained attention, and speed of decision making explained the common but not the unique portions of the positive manifold. Thus, we failed to provide evidence for POT's assumption that the positive manifold is the result of overlapping domain-general processes. This does not mean that domain-general processes other than those investigated here will not be able to show the pattern of results predicted by POT.

Mene Mene Tekel Upharsin: Clerical Speed and Elementary Cognitive Speed are Different by Virtue of Test Mode Only.

Current taxonomies of intelligence comprise two factors of mental speed, clerical speed (Gs), and elementary cognitive speed (Gt). Both originated from different research traditions and are conceptualized as dissociable constructs in current taxonomies. However, previous research suggests that tasks of one category can be transferred into the other category by simply changing the mode of administration, i.e., in form of a paper-and-pencil test or in from of a computer-based elementary cognitive task. However, cross-mode correlations for specific tasks are usually only moderate. In the present study, mental speed was assessed as a broad construct across different tasks and stimulus materials. This allowed modeling mental speed as a hierarchical construct for paper-and-pencil as well as for computer-based tests. Cross-mode correlations of the respective general factors were moderate (r = 0.64), while the cross-mode correlations of task-specific components depended on task type (r = 0.12 to r = 0.71). Only the g factors of mental speed, but not the task-specific components, were found to be related with working memory capacity as a marker of cognitive ability. The speed general factor modeled across computer-based tests was more highly correlated with working memory capacity (r = 0.66) than the general factor modeled across paper-and-pencil tests (r = 0.46). These findings corroborate a crucial role of the assessment method and imply that validity of speed tests is affected by the choice of the test format.

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

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

On the Relationship between P3 Latency and Mental Ability as a Function of Increasing Demands in a Selective Attention Task.

The mental speed approach to individual differences in mental ability (MA) is based on the assumption of higher speed of information processing in individuals with higher than those with lower MA. Empirical support of this assumption has been inconsistent when speed was measured by means of the P3 latency in the event-related potential (ERP). The present study investigated the association between MA and P3 latency as a function of task demands on selective attention. For this purpose, 20 men and 90 women performed on a standard continuous performance test (CPT1 condition) as well as on two further task conditions with lower (CPT0) and higher demands (CPT2) on selective attention. MA and P3 latency negatively correlated in the standard CPT, and this negative relationship even increased systematically from the CPT1 to the CPT2 condition but was absent in the CPT0 condition. The present results indicate that task demands on selective attention are decisive to observe the expected shorter P3 latency in individuals with higher compared to those with lower MA.

Scoring Alternatives for Mental Speed Tests: Measurement Issues and Validity for Working Memory Capacity and the Attentional Blink Effect.

Research suggests that the relation of mental speed with working memory capacity (WMC) depends on complexity and scoring methods of speed tasks and the type of task used to assess capacity limits in working memory. In the present study, we included conventional binding/updating measures of WMC as well as rapid serial visual presentation paradigms. The latter allowed for a computation of the attentional blink (AB) effect that was argued to measure capacity limitations at the encoding stage of working memory. Mental speed was assessed with a set of tasks and scored by diverse methods, including response time (RT) based scores, as well as ex-Gaussian and diffusion model parameterization. Relations of latent factors were investigated using structure equation modeling techniques. RT-based scores of mental speed yielded substantial correlations with WMC but only weak relations with the AB effect, while WMC and the AB magnitude were independent. The strength of the speed-WMC relation was shown to depend on task type. Additionally, the increase in predictive validity across RT quantiles changed across task types, suggesting that the worst performance rule (WPR) depends on task characteristics. In contrast to the latter, relations of speed with the AB effect did not change across RT quantiles. Relations of the model parameters were consistently found for the ex-Gaussian tau parameter and the diffusion model drift rate. However, depending on task type, other parameters showed plausible relations as well. The finding that characteristics of mental speed tasks determined the overall strength of relations with WMC, the occurrence of a WPR effect, and the specific pattern of relations of model parameters, implies that mental speed tasks are not exchangeable measurement tools. In spite of reflecting a general factor of mental speed, different speed tasks possess different requirements, supporting the notion of mental speed as a hierarchical construct.

Elucidating the Functional Relationship Between Speed of Information Processing and Speed-, Capacity-, and Memory-Related Aspects of Psychometric Intelligence.

Numerous studies reported a positive relationship between speed of information processing (SIP) and the g factor of intelligence. Only very few studies, however, examined SI P's relationship to speed-, capacity-, and memory-related aspects of psychometric intelligence. In order to further elucidate this relationship, a Hick reaction time task and the Berlin Intelligence Structure (BIS) test were administered to 240 participants. From the BIS test, indicators of BIS -Capacity, BIS -Speed, and BIS -Memory were determined. By means of fixed-links modeling, we subdivided variance in reaction time from the Hick task into a component representing individual differences in speed directly related to the systematically increased number of possible responses and another component representing individual differences in speed associated with residual sources unrelated to the experimental variation of response alternatives. While the former speed component was primarily related to BIS -Capacity and, to a lesser extent, to BIS -Speed, the latter one was only weakly related to BIS -Speed but unrelated to BIS -Capacity. None of the two speed components from the Hick task showed an association with BIS -Memory. Our findings indicate that individual differences in SI P caused by experimentally increasing the number of possible responses were more strongly associated with capacity- than with speed-related aspects of psychometric intelligence. In addition, individual differences in SI P not associated with the experimental manipulation of response alternatives showed rather weak relationships to each of the three BIS operations and could be considered equally strong.

Response Time Reduction Due to Retesting in Mental Speed Tests: A Meta-Analysis.

As retest effects in cognitive ability tests have been investigated by various primary and meta-analytic studies, most studies from this area focus on score gains as a result of retesting. To the best of our knowledge, no meta-analytic study has been reported that provides sizable estimates of response time (RT) reductions due to retesting. This multilevel meta-analysis focuses on mental speed tasks, for which outcome measures often consist of RTs. The size of RT reduction due to retesting in mental speed tasks for up to four test administrations was analyzed based on 36 studies including 49 samples and 212 outcomes for a total sample size of 21,810. Significant RT reductions were found, which increased with the number of test administrations, without reaching a plateau. Larger RT reductions were observed in more complex mental speed tasks compared to simple ones, whereas age and test-retest interval mostly did not moderate the size of the effect. Although a high heterogeneity of effects exists, retest effects were shown to occur for mental speed tasks regarding RT outcomes and should thus be more thoroughly accounted for in applied and research settings.

A Differential-Developmental Model (DDM): Mental Speed, Attention Lapses, and General Intelligence (g).

The aim of this paper is to provide a parsimonious account of developmental and individual differences in intelligence (measured as g). The paper proposes a Differential-Developmental Model (DDM), which focuses on factors common to intelligence and cognitive development (e.g., mental speed and attention lapses). It also proposes a complementary method based on Jensen's box, a chronometric device. The device systematically varies task complexity, and separates two components of mental speed that differentially predict intelligence and cognitive development (reaction time and movement time). The paper reviews key assumptions of DDM, preliminary findings relevant to DDM, and future research on DDM.