Commentary on McCraw, A., Sullivan, J., Lowery, K., Eddings, R., Heim, H. R., & Buss, A. T. (2024). Dynamic Field Theory of Executive Function: Identifying Early Neurocognitive Markers. https://doi.org/10.1111/mono.12478

About the Author

Michael T. Willoughby

RTI International

Michael Willoughby, Ph.D., is a Senior Fellow in the Education Practice Area at RTI International. His program of research is focused on the developmental causes, course, and consequences of executive function (EF) skills, with specific interest in how these skills support children’s transition to school and their risk for disruptive behavior disorders. He is also involved in the development and evaluation of performance-based measures of EF, including for use in low-resource settings.


Moving Towards a Developmental Conceptualization of Executive Function Skills

I enjoyed reading McCraw and colleagues’ Monograph. My commentary is organized in three sections. First, I highlight what I consider to be key strengths and limitations of this work. Second, I elaborate and extend McCraw and colleagues’ concerns with the components view of EF. Third, I highlight Gottlieb’s model of probabilistic epigenesis as an under-utilized framework that can help address criticisms of EF research that arise from the widespread adoption of the components view. 

Strengths & Limitations of this Monograph

This Monograph is characterized by three interrelated strengths. The authors’ reliance on dynamic field (DF) theory is a distinguishing feature of this work. DF motivated a novel hypothesis that label learning in toddlerhood would contribute to children’s EF performance in early childhood. Relatively few studies in the contemporary developmental literature explicitly appeal to developmental theory to inform study design and hypotheses. Another strength of this study is the use of functional near infrared spectroscopy methods while children completed dimensional label comprehension and production tasks at the 30-month visit. Although many studies of EF skills in early childhood invoke brain development, far fewer obtain direct measures of neural structure or function. When studies do involve measures of neural activity, these data are typically collected in conjunction with EF task performance (e.g., Moriguchi & Shinohara, 2019). This study was unique in collecting neural data during the toddler assessment and relying on these neural data as predictors of subsequent EF performance. Finally, despite limitations in the number and racial diversity of participants (both of which are acknowledged), the authors made intentional decisions in the design and analysis of their study to more precisely test their motivating hypotheses (e.g., contrasting the influence of dimensional label vs. Simon task performance as predictors of DCCS). 

In my opinion, this monograph also suffers from two limitations. First, the DF model is focused on explaining children’s performance on the Dimensional Change Card Sort task. My concern is that this work conflates performance on the DCCS as EF. This is reminiscent of the problems in other areas of psychological research in which a specific task is conflated with the underlying construct (e.g., strange situation to measure attachment; false belief task to measure theory of mind). Although the DCCS is arguably the most popular and widely studied measure of EF in early childhood, children’s performance on the DCCS measures only one facet of their EF skills. To the extent that the DF is narrowly focused on DCCS performance, the resulting inferences are similarly limited. The authors’ proposal that label learning interventions in toddlerhood should be developed to promote EF skills is a case in point. We aspire to identify interventions that broadly benefit EF skill development, not that increase children’s performance on any specific task. Second, the authors advance the provocative idea that EF skills are an emergent property of neural systems. Despite the conceptual appeal of this idea, the ability to rigorously test this idea proves elusive. Ultimately, their work demonstrated that individual differences in neural activity during a dimensional label learning task in toddlerhood uniquely predicted performance on the DCCS in early childhood. Although documenting longitudinal associations that support study hypotheses is compelling, it falls short of an ‘emergent’ perspective of EF. This criticism is not unique to this work but rather reflects a fundamental tension in developmental science, where the complexity of our theory routinely outstrips our methods and data.

Discontent with Component View of Executive Function Skills

The authors present DF as an alternative to the ‘component view’ (also commonly known as the tripartite model) of EF. The component view is shorthand for the widespread characterization of EF skills as constituting three foundational cognitive processes—inhibitory control, working memory, and cognitive flexibility—that collectively support goal directed behaviors, including planning and reasoning (Diamond, 2013). Given the growing criticism of the component view (Doebel, 2020; Rosales et al., 2023), it is worth situating this view in a broader context. As I described elsewhere (Willoughby & Hudson, 2020), the components view of EF emerged from the use of factor analytic models to summarize EF task performance. The ascendance of factor analytic methods in the EF literature occurred at a time when researchers were increasingly critical of the value of EF as a scientific construct. Specifically, concerns were raised that the proliferation of individual tasks complicated the ability to integrate empirical results (Baggetta & Alexander, 2016). Moreover, the proliferation of conceptual models, which lacked a standard terminology, contributed to the idea that EF was an ill-defined construct that was not amenable to empirical inquiry (Barkley, 2012). Factor analytic studies unintentionally addressed these concerns. Specifically, the proliferation of individual tasks appears less problematic if tasks are considered interchangeable indicators of a smaller set of latent constructs. Moreover, the adoption of a common set of labels to both describe latent variables and EF skills more generally (i.e., inhibitory control, working memory, cognitive flexibility) addressed concerns about terminological confusion. Finally, the notion that the complexities of EF skills (including advanced forms of planning, monitoring, and reasoning) could be explained with reference to foundational cognitive processes helped to sidestep early criticisms of the invocation of a ‘central executive’ or related homuncular concepts for explaining EF performance. 

Although the component view helped to introduce a standardized terminology in the literature, I maintain that it has also engendered substantial confusion that is the source of recent criticisms. Notably, the component view is solely a descriptive account of the covariance structure of EF task performance. Whereas early prominent studies of adults indicated that EF tasks could be parsimoniously explained by three latent variables, subsequent studies suggested that the factor structure may change from being unidimensional in early childhood to multidimensional in adulthood (Karr et al., 2018). The application of advanced factor analytic models (i.e., bi-factor parameterization) ushered in a ‘unity and diversity’ model of EF, which implied that EF task performance depends on a combination of general (i.e., the common factor, ‘unity’) and specific (i.e., specific factors, ‘diversity’) cognitive processes (Friedman & Miyake, 2017; Miyake & Friedman, 2012). It is important to remember that the component view (including the unity and diversity model) of EF results from psychometric studies of EF (Silva et al., 2024). Psychometric models describe the covariance structure of indicators. They are not intended to provide insight into the developmental processes that give rise to or influence EF skills, nor do they necessarily provide specific insight into the neural processes that support the use of EF skills (but see Saylik et al., 2022 for some supporting evidence in adults). 

The mistaken belief that psychometric models can inform the development of EF is a source of confusion in the literature. For example, McCraw and colleagues criticize the component view as ignoring contextual influences on EF skills, which is an idea that has been raised by others (Munakata & Michaelson, 2021). McCraw and colleagues also maintain that the component view has promoted a perspective of EF in which training studies were expected to have broad benefits (i.e., training specific EF skills will result in collateral benefits for behavioral functioning and/or academic performance). They and others have pointed out that EF training studies have largely failed to do so (Kassai et al., 2019; Niebaum & Munakata, 2023). In my opinion, the growing discontent with the component view (and by extension unity and diversity model) of EF is misplaced. The component view is a psychometric model that serves a descriptive purpose; it is not a theoretical model that should acknowledge contextual influences on EF performance or inform EF interventions. The increasing discontent with the component view is symptomatic of a larger problem involving our limited understanding of how EF skills develop. Developmental systems theories, like the one promoted in this monograph, represent a path forward.

Embracing Developmental Accounts of EF 

Here, I provide a high-level account of Gottlieb’s theory of probabilistic epigenesis and consider how it informs the results of this monograph. I focus on probabilistic epigenesis because it is the developmental systems model with which I am most conversant (Gottlieb & Willoughby, 2006). Given space constraints, I highlight key ideas that were evident throughout Gottlieb’s writings (Gottlieb, 1976, 1991, 1992, 1998b, 2002). Interested readers may also enjoy Blair and Raver’s more extended consideration of how Gottlieb’s model informs the development of EF skills (Blair & Raver, 2012; Blair et al., 2016). 

Although Gottlieb’s program of research involved mallard ducks, his theory integrated ideas from ethology, psychobiology, and systems theory that spanned the 19th – 21st centuries. Gottlieb’s goal was to draw attention to converging ideas from across disciplines and historical time that revealed a universal set of principles that governed individual development. Much of his work occurred at a time in which genetic influences were assumed to play a privileged role in directing individual development, which included ‘maturational’ and ‘instinctual’ accounts of behavioral and cognitive development. As such, Gottlieb’s empirical and theoretical work often sought to highlight the inaccuracies of this perspective (Gottlieb, 1995, 1998a). To this end, he promoted a probabilistic epigenesis as a counterpoint to predetermined epigenesis and championed experiential canalization as a counterpoint to genetic canalization (Gottlieb, 1991). 

Consistent with other systems theories, Gottlieb conceptualized individual development as consisting of multiple levels of influence (genetic, neural, behavioral, environmental levels were often used for heuristic purposes). An essential idea was that experience was the primary catalyst of development. Experience was defined as any functional activity that occurred between levels, which was bidirectional in nature. Gottlieb proposed that experience served inductive (channeling development in a particular direction), facilitative (influencing thresholds or the rate at which development occurs), and maintenance (serving to sustain the integrity of existing development) functions (Gottlieb, 1976, 1992, 2002). The emphasis on experience as propelling individual development remains a novel idea that can help organize our thinking and research. Here, I briefly consider some of the key ideas in the monograph from the vantage of Gottlieb’s model. 

The authors offered a novel characterization of EF:  

Instead of viewing action as a consequence of a “central executive” or homuncular control system, the DF model demonstrates how cognitive control is an emergent property of interactions between neurocognitive systems and the environment… rather than EF being defined in terms of structural components such as inhibition or switching, EF is instead defined as a property of how label representations guide object-based attention. 

This characterization is consistent with the idea that EF skills result from interactions within and across neural and cognitive levels of influence (i.e., horizontal and vertical coactions in the parlance of probabilistic epigenesis). Regardless of whether EF is conceived of as an emergent property of an individual or as arising from the coaction between neural and cognitive levels of influence, both conceptualizations challenge the widespread tendency to conceive of EF skills as stable attributes of children (akin to a muscle). These conceptualizations have implications for theory development and the design of interventions. 

One of the main findings from this monograph was that children’s perceptual and language learning in toddlerhood, which was evident at behavioral and neural levels of analysis, predicted performance on the DCCS in early childhood. From the vantage of probabilistic epigenesis, children’s exposure to rich language environments in toddlerhood, which promotes early perceptual knowledge and language learning (shape knowledge, labels), may serve as an inductive experience that is necessary for subsequent EF skills. Children’s interactions with caregivers who model and scaffold strategy use (e.g., use of internalized rules and analogical reasoning) may serve as a facilitative experience for EF skills, especially when this strategy use is applied to perceptual or procedural knowledge (Starr et al., 2023; Zelazo, 2015). Growing expectations that children will take increasingly more responsibility for managing their own behavior and emotions, including adapting to situational variations in expectations (e.g., across home and preschool), may serve as maintenance experiences that promote quantitative and qualitative improvements in EF skill use (Chevalier, 2015). Although these examples are overly simplistic, they are intended to highlight the merits of considering how the cumulative impact of early learning experiences (which play inductive, facilitative, and maintenance functions) collectively support the emergence of increasingly sophisticated EF skills. This is consistent with the authors’ stated objective of considering “how children’s early neurocognitive development lays the foundation for later EF development” and their interest in looking “beyond traditional measures of EF to other aspects of perception/action development to understand the processes that give rise to EF.” This perspective also resonates with a recent construal of EF skills as ‘just-in-time’ processes that are initially needed to solve simple, concrete demands but that expand to more abstract demands in an incremental fashion (Ibbotson, 2023). 

McCraw and colleagues advocate for the creation of dimensional label learning interventions as a novel strategy for promoting EF skill development. In doing so, they also suggest that that many existing interventions suffer from ambiguity in the mechanisms that are targeted. Although the promotion of label learning may facilitate later performance on the DCCS, it is not clear to me how this would benefit EF skills more broadly. Nonetheless, their proposal is consistent with the broader idea that multiple aspects of children’s language experience in infancy and toddlerhood contribute to subsequent EF skill development (Kuhn et al., 2016; Kuhn et al., 2014). Elucidating the specific ways through which early language environments support later EF skills may inform novel intervention approaches. These ideas are reminiscent of Gottlieb’s (2002) interest in ‘nonobvious’ sources of influence on later development (in his classic work, this involved the discovery that ducklings only show a selective response to the maternal call of their species if they experienced exposure to their own calls during the embryonic period). 

Concerns about the ambiguity of mechanisms that are targeted in existing EF intervention studies can be reframed in terms of the theory of change. Many recent reviews of EF interventions have primarily focused on the efficacy of various approaches (e.g., physical activity, mindfulness, computerized training) and consideration of potential moderating variables, including child (e.g., typical vs. atypically developing) and intervention (e.g., dosage) characteristics (Sankalaite et al., 2021; Song et al., 2022; Takacs & Kassai, 2019). Comparatively less attention has been paid to the ways in which EF interventions differ with respect to their implicit theories of change (cf., yoga, physical activity, computerized training approaches), as well as the supporting evidence for the theory of change. It is notable that, following an exhaustive review of EF intervention studies, Diamond and Ling (2019) concluded that the most effective intervention approaches would continually challenge EF skills in new and different ways, be viewed as personally meaningful to participants, involve a mentor, and provide a sense of joy. Clearly, we need more detailed theoretical models of how EF skills develop. Moreover, we (as a field) should leverage interventions as a strategy for testing and refining our theoretical models. Adopting a developmental perspective can assist in accomplishing these objectives.


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Citation:
Willoughby, M. T. (2024). Moving Towards a Developmental Conceptualization of Executive Function Skills. [Peer commentary on the article “Dynamic Field Theory of Executive Function: Identifying Early Neurocognitive Markers” by A. McCraw, J. Sullivan, K. Lowery, R. Eddings, H. R. Heim, and A. T. Buss.]. Monograph Matters. Retrieved from https://monographmatters.srcd.org/2024/12/04/commentary-willoughby-89-3/