title: The neural basis of cognitive development: a constructivist manifesto.
abstract: 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.
authors: Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA. steve@salk.edu www.cnl.salk.edu/cnl
authors: S R
authors: SR
authors: Quartz
authors: T J
authors: TJ
authors: Sejnowski
mesh_terms: D001369:Axons / Q000502:physiology; D001921:Brain / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D004777:Environment; D006801:Humans; D007858:Learning / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D013569:Synapses / Q000502:physiology