Advancing the Understanding of the Factor Structure of Executive Functioning

Himi, Samsad Afrin; Bühner, Markus; Hilbert, Sven

doi:10.3390/jintelligence9010016

Cited by 15 publications

(12 citation statements)

References 32 publications

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“…Typical updating and shifting tasks are created following the same logic of selective additivity, allowing to analyze individual differences in the performance decrement from the low to the high process saturated condition. Because researchers have the choice between using RTs or accuracy rates as performance measures, there is much heterogeneity how individual differences in executive functions are assessed (von Bastian et al, 2020), even within single studies (Friedman et al, 2006(Friedman et al, , 2008Himi et al, 2019Himi et al, , 2021Ito et al, 2015;Krumm et al, 2009;Miyake et al, 2000;Schnitzspahn et al, 2013;Vaughan & Giovanello, 2010;Wongupparaj et al, 2015).…”

Section: The Common Factor Of Executive Function Tasks Measures Nothi...mentioning

confidence: 99%

“…The three executive functions by Miyake et al (2000) represent distinct but interrelated factors (Friedman et al, 2006(Friedman et al, , 2008Himi et al, 2019Himi et al, , 2021Ito et al, 2015;Miyake et al, 2000;Schnitzspahn et al, 2013;Vaughan & Giovanello, 2010). Substantial correlations between the three latent factors raised the question of a higher-order factor of executive functions, often labeled as common executive functions.…”

Section: Empirical Findings On the Three-factor Model Of Executive Fu...mentioning

confidence: 99%

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The common factor of executive functions measures nothing but speed of information uptake

Löffler¹,

Frischkorn²,

Hagemann³

et al. 2022

Preprint

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There is an ongoing debate about the unity and diversity of executive functions and their relationship with other cognitive abilities such as processing speed, working memory capacity, and intelligence. Specifically, the initially proposed unity and diversity of executive functions is challenged by discussions about (1) the factorial structure of executive functions and (2) unfavorable psychometric properties of measures of executive functions. The present study addressed two methodological limitations of previous work that may explain conflicting results: the inconsistent use of (a) accuracy-based vs. reaction time-based indicators and (b) average performance vs. difference scores. In a sample of 148 participants who completed a battery of executive function tasks, we tried to replicate the three-factor model of the three commonly distinguished executive functions shifting, updating, and inhibition by adopting data-analytical choices of previous work. After addressing the identified methodological limitations using drift-diffusion modeling, we only found one common factor of executive functions that was fully accounted for by individual differences in the speed of information uptake. No variance specific to executive functions remained. Our results suggest that individual differences common to all executive function tasks measure nothing more than individual differences in the speed of information uptake. We therefore suggest to refrain from using typical executive function tasks in applied research, because these tasks are no valid measures of executive functions.

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Section: The Common Factor Of Executive Function Tasks Measures Nothi...mentioning

confidence: 99%

Section: Empirical Findings On the Three-factor Model Of Executive Fu...mentioning

confidence: 99%

The common factor of executive functions measures nothing but speed of information uptake

Löffler¹,

Frischkorn²,

Hagemann³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Such a battery could tap, for example, the most common taxonomy of executive attention that is based on the work by Friedman and Miyake ( Friedman et al 2006 ; Friedman et al 2008 ) with the three basic functions referred to as “working-memory updating”, “pre-potent response inhibition”, and “task-set shifting” ( Friedman and Miyake 2017 ). However, extensions of this framework by relational integration ( Himi et al 2021 ) or more fine-grained investigations of different aspects of inhibition ( Rey-Mermet et al 2018 ) might also be promising to examine whether other aspects of executive attention—primarily when based on error rates rather than RT measures—differentially account for correlations in the positive manifold.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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“…The equivalent of the p factor was termed emotional intelligence 13 and general factor of personality (GFP) 14 . In neuropsychology and neurology, the equivalent of the g factor was termed global cognition 18 , global cognitive function or ability 19 , and global neurocognition 20,21 . The equivalent of the p factor was conceptualized by a global score of neuropsychiatric symptoms 22 .…”

Section: Different Disciplines Measure G and P Using Different Method...mentioning

confidence: 99%

The link between mitochondria, psychopathology, and intelligence: A bioenergetic model of cerebral function

Fissler¹,

Mavioğlu²,

Wenzel³

et al. 2022

Preprint

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Decomposing the structure of human cerebral function in its domains, such as affect regulation or cognition, forms the backbone of psychiatric diagnosis and treatment. Research continues to decipher the domains and hierarchical structure of cerebral function. So far, the findings strongly suggest two higher-order latent factors of general psychopathology (p factor) and general intelligence (g factor). Both general factors are functions of the same organ, covary, share risk factors as well as biomarkers, and benefit from the same treatments. However, to our knowledge, a model that connects both components of cerebral function within a higher-order latent factor and describes its potential biological underpinning is lacking. First, we suggest the general factor of cerebral function (c factor) as the shared variance of the measures of g and p in a bi-factor model. Second, we propose and provide evidence that mitochondrial bioenergetics (MB) is one core biological underpinning of c. Third, we describe how this c factor mito-bioenergetics (CMB) model may transform research and clinical practice by advancing knowledge of treatment effects, risk factors, biomarkers and clinical outcomes. Finally, we present a CMB model-based hypothesis stating that fatigue—as a phenotypical correlate of MB—directly loads on c.

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Advancing the Understanding of the Factor Structure of Executive Functioning

Cited by 15 publications

References 32 publications

The common factor of executive functions measures nothing but speed of information uptake

The common factor of executive functions measures nothing but speed of information uptake

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

The link between mitochondria, psychopathology, and intelligence: A bioenergetic model of cerebral function

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