Literature DB >> 10097006

The neural basis of cognitive development: a constructivist manifesto.

S R Quartz1, T J Sejnowski.   

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.

Entities:  

Mesh:

Year:  1997        PMID: 10097006     DOI: 10.1017/s0140525x97001581

Source DB:  PubMed          Journal:  Behav Brain Sci        ISSN: 0140-525X            Impact factor:   12.579


  68 in total

1.  Cortical representations of symbols, objects, and faces are pruned back during early childhood.

Authors:  Jessica F Cantlon; Philippe Pinel; Stanislas Dehaene; Kevin A Pelphrey
Journal:  Cereb Cortex       Date:  2010-05-10       Impact factor: 5.357

Review 2.  A hierarchical model of the evolution of human brain specializations.

Authors:  H Clark Barrett
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-20       Impact factor: 11.205

Review 3.  Neural plasticity of development and learning.

Authors:  Adriana Galván
Journal:  Hum Brain Mapp       Date:  2010-06       Impact factor: 5.038

Review 4.  Postoperative cerebellar mutism and autistic spectrum disorder.

Authors:  Erol Tasdemiroğlu; Miktat Kaya; Can Hakan Yildirim; Levent Firat
Journal:  Childs Nerv Syst       Date:  2010-10-30       Impact factor: 1.475

5.  A longitudinal functional magnetic resonance imaging study of language development in children 5 to 11 years old.

Authors:  Jerzy P Szaflarski; Vincent J Schmithorst; Mekibib Altaye; Anna W Byars; Jennifer Ret; Elena Plante; Scott K Holland
Journal:  Ann Neurol       Date:  2006-05       Impact factor: 10.422

Review 6.  Constructivisms from a genetic point of view: a critical classification of current tendencies.

Authors:  José Carlos Sánchez; José Carlos Loredo
Journal:  Integr Psychol Behav Sci       Date:  2009-12

Review 7.  The concept of allosteric interaction and its consequences for the chemistry of the brain.

Authors:  Jean-Pierre Changeux
Journal:  J Biol Chem       Date:  2013-07-22       Impact factor: 5.157

8.  Neural tuning of human face processing.

Authors:  Jeremy I Borjon; Asif A Ghazanfar
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-04       Impact factor: 11.205

9.  Changes in the interaction of resting-state neural networks from adolescence to adulthood.

Authors:  Michael C Stevens; Godfrey D Pearlson; Vince D Calhoun
Journal:  Hum Brain Mapp       Date:  2009-08       Impact factor: 5.038

Review 10.  Early experience and multisensory perceptual narrowing.

Authors:  David J Lewkowicz
Journal:  Dev Psychobiol       Date:  2014-01-16       Impact factor: 3.038

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