How do the representations underlying cognitive skills emerge? It is becoming increasingly apparent that answering this question requires integration of neural, cognitive and computational perspectives. Results from this integrative approach resonate with Piaget’s central constructivist themes, thus converging on a ‘neural constructivist’ approach to development, which itself rests on two major research developments. First, accumulating neural evidence for developmental plasticity makes nativist proposals increasingly untenable. Instead, the evidence suggests that cortical development involves the progressive elaboration of neural circuits in which experience-dependent neural growth mechanisms act alongside intrinsic developmental processes to construct the representations underlying mature skills. Second, new research involving constructivist neural networks is elucidating the dynamic interaction between environmentally derived neural activity and developmental mechanisms. Recent neurodevelopmental studies further accord with Piaget’s themes, supporting the view of human cortical development as a protracted period of hierarchical-representation construction. Combining constructive growth algorithms with the hierarchical construction of cortical regions suggests that cortical development involves a cascade of increasingly complex representations. Thus, protracted cortical development, while occurring at the expense of increased vulnerability and parental investment, appears to be a powerful and flexible strategy for constructing the representations underlying cognition.

Key words: developmental cognitive neuroscience, constructivism, hierarchial development, activity-dependent neural development, prefrontal cortex

How do minds emerge from developing brains? According to “neural constructivism,” the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: “constructive learning” minimizes the need for prespecification in accordance with recent neurobiological evidence that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning.

Key words: cognitive development, constructivism, evolution, learnability, mathematical learning theory, neural development, selectionism