Special Issue Introduction: Bringing Theory to the Forefront of Developmental Cognitive Neuroscience

Developmental neuroscience is a general term related to the study of developmental processes of the brain. The present special issue includes some discussion of general brain development processes but relates most directly to a specific branch of this research, referred to commonly as developmental cognitive neuroscience (DCN). DCN examines the relation between the developing brain and the emergence of sensorimotor, cognitive, social, and emotional changes across the lifespan, as well as the environmental and biological influences that play a role in these processes. Research in this domain has expanded exponentially over the last 3 decades resulting in a rapid increase in published papers on the topic. As an illustration, we performed a Google Scholar search of the term “developmental cognitive neuroscience” for any time prior to 1990 which produced about 34 results (with none before 1972), while a search on that term from 1990 to the present produced about 17,000 results, with about 6,290 between 2023 and the present, alone. As with any emerging and expanding field, it has experienced some challenges along with this rapid growth.

Because the field of DCN has attempted to employ cutting-edge methodology to study difficult-to-recruit samples (children and adolescents), in some cases, developmental theory has gotten lost in the conversation. Often neuroscience techniques and study questions that have long been used with adults are adapted for use with children, often starting with asking the question of whether children’s brains show similar responses to those of adults. While this might be a logical place to start from a methodological perspective, i.e., making sure a paradigm and equipment will work with a study on children, it has led to some approaches that are less than informative from a developmental perspective. First, this type of approach has meant that there is a tendency to ask what brain areas are activated in children in response to specific tasks, without due consideration to the theoretical rationale behind the question. Second, any comparisons are often with adults rather than other-aged children. This type of comparison limits our understanding of how neural processes change over the course of development and instead contrasts neural activation in children versus adults (who are seen as the endpoint or mature point of comparison). Finally, a narrow focus on areas of brain activation can limit our understanding underlying processes or supporting networks and how they might change over time. In order for DCN to truly inform theory, and for theory to guide DCN, research needs to go beyond simply identifying areas of neural activation in response to specific tasks.

Fortunately, there are scholars whose program of research in DCN has been firmly grounded in theory, and the results of the studies have in turn informed theory. Thus, the aim of this special issue is to highlight research that has fruitfully integrated developmental theory and developmental neuroscience in ways that promise to advance developmental science. In this special issue of Human Development, we highlight research that addresses different domains and periods of development and uses different techniques, to present a broad sampling of how theory is informing work across various areas of developmental neuroscience.

When DCN (or any subdiscipline) is firmly grounded in theory, it has the potential to change the scope of that discipline. Neuroscientific techniques have the potential to answer questions that cannot be addressed behaviorally and to provide insight into underlying mechanisms and processes. One example comes from research on reading skills. A longitudinal study of typically developing children aged 9–15 years examined whether brain activity would be predictive of future reading skills (McNorgan et al., 2011). Critically, the researchers were interested in how correlations between brain and behavior might inform developmental models of reading. The children were initially assessed for reading skills and performed an fMRI rhyming judgment task. Patterns of brain activation during the task predicted the type of difficulties that children encountered in their reading 6 years later. Results revealed an age-dependent correlation between activity in brain areas associated with phonological and orthographic processing and future reading ability, consistent with models that had proposed a maturational timeline of these language processes: early reliance on phonological and later reliance on orthographic processing. Thus, brain imaging data were able to provide evidence for these models in a way that behavioral assessments of reading skills over time were not.

In contrast, developmental neuroscience research that focuses on children simply as a comparison to adults (exploring, for example, whether the same brain areas are activated during a given task) provides a limited contribution to the field. Such a comparison between patterns of brain activation at one age compared to another, without a firm grounding in developmental theory, can do little to advance our understanding of human development. This type of approach overlooks important developmental concepts such as equifinality (where the outcomes might be the same but the underlying developmental processes are very different) or multifinality (where the outcomes are different, but the underlying developmental processes are the same). While this was once a common (if not dominant) approach in developmental neuroscience, some scholars have been careful both to incorporate developmental theory into their research and to shift away from “localization of function” models toward ones which consider dynamic connectivity of brain systems and circuits. These approaches are ones that yield more comprehensive accounts of developmental changes in the brain, and that can complement and add value to behavioral studies.

Why is it important for developmental scientists to understand how brain structure and function changes with development? First, if we assume that cognitive development is subserved by underlying neurological changes, tracking neural change has the potential to shed light on developmental processes in a way that observing behavior, alone, cannot. For instance, Steinberg proposed a dual-systems model of adolescent risk taking (Steinberg, 2010; Steinberg et al., 2008) that has become one of the dominant models in the field. This model describes two processes: a curvilinear pattern of reward seeking that peaks in mid-adolescence and a relatively linear age-related decrease in impulsivity across the adolescent years (indexing increasing self-control). Taken together, these two systems contribute to especially heightened vulnerability to risk taking in middle adolescence when reward seeking is high, while self-control is not yet fully mature. Pfiefer and Allen argued that the dual-systems models should be reconsidered in light of neuroimaging evidence that is inconsistent with the account and suggest building new models to account for greater complexity (Pfeifer & Allen, 2012). For instance, they describe neuroimaging evidence that shows inconsistent patterns of greater ventral affective activity as conferring risk and greater prefrontal cortical activity as conferring protection as the dual-systems model might predict. Shulman and colleagues published a review that incorporated neuroimaging literature since 2008 and suggested that neuroscientific findings are largely in line with the predictions of the dual-systems model (Shulman et al., 2016). Thus, it is clear that (despite disagreements between researchers) neuroimaging evidence can inform theory and drive the development of new theories when evidence does not line up with existing theories.

In addition, understanding how the brain develops can lead to a better comprehension of the timing of sensitive or critical periods and may inform educational practices or, in the case of atypical development, the implementation of supports and services. Thus, DCN has the potential to make critical contributions to theory, as long as it goes beyond the “localization of function” approach.

This special issue will examine how DCN can address theories of development. Contributors will be invited to discuss their work from multiple domains of developmental science and focus on how it informs developmental theory. Specifically, it will highlight cutting-edge neuroscience work in socioemotional and cognitive development that represents a shift of focus away from examining what areas of the brain are associated with certain processes toward rigorous inquiry into how neuroscience can inform and test theoretical predictions. Thus, the special issue will include contributors who use neuroscience methods to examine dynamic developmental processes that drive how sensorimotor, social, and cognitive development unfold and who have a strong theoretical orientation in their research.

We asked our contributing authors to consider the following questions in their paper: (1) How can neuroscience findings inform and be informed by developmental theory? What are some concrete examples of this in your own work or within the domain of research in which your work is situated? (2) How do you conceptualize development and developmental processes within your own research? (3) How has developmental theory driven your own research questions, shaped the kinds of questions you have asked, and informed interpretations of your findings? and (4) What are several key guiding principles that should inform developmental neuroscience work so that theory stays at the forefront of our scientific inquiries?

The first paper, authored by Marshall (2024), describes a biologically coherent account of the brain and how it develops. In this paper, Marshall argues that brain function must be considered in the context of individual goal-directed activity rather than as a passive process that receives external input. By this view, the brain is seen as being part of a “reafferent loop that begins and ends with the activity of the organism.” Thus, Marshall focuses on embodiment as key to understanding the relation between brain development and individual level activity.

The second paper, authored by Arsalidou (2024), focuses on neurocognitive assessments and translates links between neuroscience and constructivist developmental theory. This paper describes the developmental theory of constructive operators and provides four guiding principles (using developmentally appropriate age groups, ensuring assessments are child-friendly and culturally appropriate, and using meta-subjective task analyses) to help steer the field of DCN. These principles highlight the benefits of employing theory-based measures and have applications for behavioral and neuroimaging research. Arsalidou also describes the historical figures that have shaped the field of neuroscience and psychology to show the interplay between developmental theory and neuroscientific methodologies.

The third paper, authored by Rueda (2024), examines the contributions of the cognitive neuroscience approach to a theory of attentional development. In this paper, Rueda describes how three components of attention –sustained attention, selective attention, and executive control – have been associated with specific brain networks. Further, the paper presents a theory of attentional development and how this has been informed by both brain and behavioral evidence. This paper illustrates how neuroscience work has informed the three components of attention and how converging evidence from behavioral and brain research has helped inform theory on the development of attention. Rueda argues for the integration of data from multiple levels of analysis to develop more comprehensive and robust developmental theories.

The fourth and final paper, authored by Eveline Crone and van Drunen (2024), focuses on the development of self-concept in childhood and adolescence, and how DCN and theory are mutually informative. In this paper, Crone and van Drunen outline how Harter’s original theory of self-concept (Harter, 2012) guides but can also benefit from findings on structural brain development, insights from developmental neuroscience studies that have used self-concept appraisal paradigms, the genetic and environmental influences on correlates of self-concept development, and finally youth’s perspectives on self-concept development within current global challenges.

In addition to these four papers, we invited commentaries from two imminent developmental psychologists. Usha Goswami is a Professor of Cognitive Developmental Neuroscience at the University of Cambridge and has pioneered the application of neuroscience to education. Her research investigates the sensory/neural basis of childhood disorders of language and literacy, which are heritable and found across languages. John P. Spencer is a Professor of Psychology at the University of East Anglia in Norwich, UK. His research examines the development of visuospatial cognition, word learning, working memory, attention, and executive function with an emphasis on dynamical systems and dynamic field models of cognition and action. His commentary is co-authored by a senior graduate student, Eleanor Johns.

Taken together, the field of DCN has made progress from the once-common approaches of examining the localization of function or direct comparisons between children’s and adult’s brain activation on the same task. DCN research is becoming more integrated with developmental theory, theory is used to make novel predictions, and findings are interpreted within theoretical frameworks and used to form new theories. The four papers in this special issue highlight how developmental theory can be fruitfully integrated with neuroscientific methods as well as promising future directions for DCN research. The commentaries provided by Goswami and Spencer and Johns provide excellent reading companions to the four submissions, offering further context and interpretation and reminding us where there is still much work to be done. As the body of DCN work expands and grows with the emergence of new neuroscientific data collection and analysis techniques, we hope that this special issue will serve as a call to colleagues in the field to keep developmental theory at the forefront in both guiding research questions and interpreting results.

The authors have no conflict of interest to report.

No funding supported this work.

C.E.V.M. and S.M.R. both were involved in conceptualization, writing – original draft, and writing – review and editing.