A tutorial for estimating mixture models for visual working memory tasks in brms: Introducing the Bayesian Measurement Modeling (bmm) package for R

Mixture models for visual working memory tasks using continuous report recall are highly popular measurement models in visual working memory research. Yet, efficient and easy-to-implement estimation procedures that flexibly enable group or condition comparisons are scarce. Specifically, most software packages implementing mixture models have used maximum likelihood estimation for single-subject data. Such estimation procedures require large trial numbers per participant to obtain robust and reliable estimates. This problem can be solved with hierarchical Bayesian estimation procedures that provide robust and reliable estimates with lower trial numbers. In this tutorial, we illustrate how mixture models for visual working memory tasks can be specified and fit in the R package brms. The benefit of this implementation over existing hierarchical Bayesian implementations is that brms integrates hierarchical Bayesian estimation of the mixture models with an efficient linear model syntax that enables us to adapt the mixture model to practically any experimental design. Specifically, this implementation allows varying model parameters over arbitrary groups or experimental conditions. Additionally, the hierarchical structure and the specification of informed priors can improve subject-level parameter estimation and solve estimation problems frequently. We will illustrate these benefits in different examples and provide R code for easy adaptation to other use cases. We also introduce a new R package called bmm, which simplifies the process of estimating these models with brms

Basic cognitive processes of intelligence

This thesis discusses important issues concerning the basic cognitive processes of intelligence. In recent empirical research on individual differences on cognitive abilities, several cognitive processes have been related to intelligence. Specifically, the capacity of working memory, processing speed or executive function (i.e. attention regulation mechanisms) have been identified as important cognitive correlates of intelligence. Within this thesis, I discuss how cognitive models as measurement tools for theoretically sound indicators of these cognitive processes may enrich research on the basic cognitive processes of intelligence. In addition, I provide an example how to establish that parameters from cognitive models poses trait like properties and thus qualify as adequate predictors of intelligence. Furthermore, I present a new methodological approach for analyzing the worst performance rule, an important phenomenon in intelligence research that has been linked to processing speed and attention regulation. And finally, I present results from an empirical study that aimed to bridge the gap between working memory capacity, processing speed, and executive functions as important predictors of intelligence. All in all, this work summarizes the core aspects of process oriented research on intelligence and outlines how future research may provide more comprehensive results identifying specific process parameters that underlie individual differences in our cognitive abilities

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

In Search of the Executive Cognitive Processes Proposed by Process-Overlap Theory

Process-Overlap Theory (POT) suggests that measures of cognitive abilities sample from sets of independent cognitive processes. These cognitive processes can be separated into domain-general executive processes, sampled by the majority of cognitive ability measures, and domain-specific processes, sampled only by measures within a certain domain. According to POT, fluid intelligence measures are related because different tests sample similar domain-general executive cognitive processes to some extent. Re-analyzing data from a study by De Simoni and von Bastian (2018), we assessed domain-general variance from executive processing tasks measuring inhibition, shifting, and efficiency of removal from working memory, as well as examined their relation to a domain-general factor extracted from fluid intelligence measures. The results showed that domain-general factors reflecting general processing speed were moderately and negatively correlated with the domain-general fluid intelligence factor (r = -.17--.36). However, domain-general factors isolating variance specific to inhibition, shifting, and removal showed only small and inconsistent correlations with the domain-general fluid intelligence factor (r = .02--.22). These findings suggest that (1) executive processing tasks sample only few domain-general executive processes also sampled by fluid intelligence measures, as well as (2) that domain-general speed of processing contributes more strongly to individual differences in fluid intelligence than do domain-general executive processes. Keywords: Process-Overlap Theory; executive processes; intelligence; processing speed; working memor

Process-oriented intelligence research: A review from the cognitive perspective

Despite over a century of research on intelligence, the cognitive processes underlying intelligent behavior are still unclear. In this review, we summarize empirical results investigating the contribution of cognitive processes associated with working memory capacity, processing speed, and executive processes to intelligence differences. Specifically, we (a) evaluate how cognitive processes associated with the three different cognitive domains have been measured, and (b) how these processes are related to individual differences in intelligence. Consistently, this review illustrates that isolating single cognitive processes using average performance in cognitive tasks is hardly possible. Instead, formal models that implement theories of cognitive processes underlying performance in different cognitive tasks may provide more adequate indicators of single cognitive processes. Therefore, we outlined which models for working memory capacity, processing speed, and executive processes may provide more specific insights into cognitive processes associated with individual differences in intelligence. Finally, we discuss implications of a process-oriented intelligence research using cognitive measurement models for psy- chometric theories of intelligence and argue that a model-based approach might overcome validity problems of traditional intelligence theories

When Load is Low, Working Memory is Shielded From Long-Term Memory’s Influence

Previous studies found that episodic long-term memory (eLTM) enhances working memory (WM) performance when both novel and previously learnt word pairs must be retained on a short-term basis. However, there is uncertainty regarding how and when WM draws on eLTM. Three possibilities are (a) that people draw on eLTM only if WM capacity is exceeded; (b) that there is always a contribution of eLTM to WM performance, irrespective of whether prior knowledge is helpful or not; or (c) benefits of prior knowledge are specific to comparisons between conditions which are similarly ambiguous concerning whether LTM may be useful. We built on the assumption that under conditions of a contribution from LTM, these LTM traces of memoranda could benefit or hamper performance in WM tasks depending on the match between the traces stored in LTM and the ones to-be stored in WM in the current trial, yielding proactive facilitation (PF) and proactive interference (PI), respectively. Across four experiments, we familiarized participants with some items before they completed a separate WM task. In accordance with possibility (a) we show that there are indeed conditions in which only WM contributes to performance. Performance deteriorated with the addition of stimuli from eLTM when WM load was low, but not when it was high; and an exchange of information between LTM and WM occurred only when WM capacity was exceeded, with PI and PF effects affecting immediate memory performance in verbal and visual tasks only at higher set sizes

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

Responsible Research Assessment Should Prioritize Theory Development and Testing Over Ticking Open Science Boxes

We appreciate the initiative to seek for ways to improve academic assessment by broadening the range of relevant research contributions and by considering a candidate’s scientific rigor. Evaluating a candidate's ability to contribute to science is a complex process that cannot be captured through one metric alone. While the proposed changes have some advantages, such as an increased focus on quality over quantity, the proposal's focus on adherence to open science practices is not sufficient, as it undervalues theory building and formal modelling: A narrow focus on open science conventions is neither a sufficient nor valid indicator for a “good scientist” and may even encourage researchers to choose easy, pre-registerable studies rather than engage in time-intensive theory building. Further, when in a first step only a minimum standard for following easily achievable open science goals is set, most applicants will soon pass this threshold. At this point, one may ask if the additional benefit of such a low bar outweighs the potential costs of such an endeavour. We conclude that a reformed assessment system should put at least equal emphasis on theory building and adherence to open science principles and should not completely disregard traditional performance metrices