Quartz, S. & Sejnowski, T.J. (1997). The neural basis of cognitive development: A constructivist manifesto.

We present a theoretical framework for understanding the roles of the hippocampus and neocortex in learning and memory. This framework incorporates a theme found in many theories of hippocampal function, that the hippocampus is responsible for developing conjunctive representations binding together stimulus elements into a unitary rep- resentation that can later be recalled from partial input cues. This idea appears problematic, however, because it is contradicted by the fact that hippocampally lesioned rats can learn nonlinear discrimination problems that require conjunctive representations. Our framework accommodates this finding by establishing a principled division of labor between the cortex and hippocampus, where the cortex is responsible for slow learning that integrates over multiple experiences to extract generalities, while the hippocampus performs rapid learning of the arbitrary contents of individual experiences. This framework shows that nonlinear discrimination problems are not good tests of hippocampal function, and suggests that tasks involving rapid, incidental conjunctive learning are better. We implement this framework in a computational neural network model, and show that it can account for a wide range of data in animal learning, thus validating our theoretical ideas, and providing a number of insights and predictions about these learning phenomena.

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“Origins of communicative disorders ” to Elizabeth Bates, and by a grant from the John D. and Catherine T. MacArthur Foundation. We are grateful to Larry Juarez and Meiti Opie The effects of focal brain injury are investigated in the first stages of language development, during the passage from first words to grammar. Parent report and/or free speech data are reported for 53 infants and preschool children between 10- 44 months of age. All children had suffered a single, unilateral brain injury to the left or right hemisphere, incurred before six months of age (usually in the pre- or perinatal period). This is the period in which we should expect to see maximal plasticity, but it is also the period in which the initial specializations of particular cortical regions ought to be most evident. In direct contradiction of hypotheses based on the adult aphasia literature, results from 10- 17 months suggest that children with righthemisphere injuries are at greater risk for delays in word comprehension, and in the gestures that normally precede and accompany language onset. Although there were no differences between left- vs. right-hemisphere injury per se on expressive language, children whose lesions include the left temporal lobe did show significantly greater delays in expressive vocabulary and

Supervised learning procedures for neural networks have recently met with considerable success in learning difficult mappings. So far, however, they have been limited by their poor scaling behaviour, particularly for networks with many hidden layers. A promising alternative is to develop unsupervised learning algorithms by defining objective functions that characterize the quality of an internal representation without requiring knowledge of the desired outputs of the system. Our major goal is to build self-organizing network modules which capture important regularities in the environment in a simple form. A layered hierarchy of such modules should be able to learn in a time roughly linear in the number of layers. We propose that a good objective for perceptual learning is to extract higher-order features that exhibit simple coherence across time or space. This can be done by transforming the input representation into an underlying representation in which the mutual information between ...

Introduction Language is puzzling. On the one hand, there are compelling reasons to believe that the possession of language by humans has deep biological roots. We are the only species that has a communication system with the complexity and richness of language. There are cases of non-human primates who can be taught (sometimes only with heroic effort) some aspects of human language, but their performance comes nowhere close to those of a six-year old child. Second, although languages differ, but there are also striking similarities across widely divergent cultures. Finally, there are significant similarities in the patterns of language acquisition across very different linguistic communities. These (and other considerations as well) all suggest that species-specific biological factors play a critical role in human's ability to acquire and process language. So what is puzzling? First, it is not at all clear what the biological foundations are. What precisely do we mean when w

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An intelligent system has to be capable of adapting to a constantly changing environment. It therefore, ought to be capable of learning from its perceptual interactions with its surroundings. This requires a certain amount of plasticity in its structure. Any attempt to model the perceptual capabilities of a living system or, for that matter, to construct a synthetic system of comparable abilities, must therefore, account for such plasticity through a variety of developmental and learning mechanisms. This paper examines some results from neuroanatomical, morphological, as well as behavioral studies of the development of visual perception; integrates them into a computational framework; and suggests several interesting experiments with computational models that can yield insights into the development of visual perception. Role of Environmental Experience in Development and Learning In order to understand the development of information processing structures in the brain, one needs knowl...

In this paper a biologically plausible and efficient object recognition system (called ORASSYLL) is introduced which is based on a set of a priori constraints motivated by findings of developmental psychology and neurophysiology. These constraints are concerned with the organisation of the input in local and corresponding entities, the interpretation of the input by its transformation in a highly structured feature space and the evaluation of features extracted from an image sequence by statistical evaluation criteria. In the context of the bias/variance dilemma the functional role of a priori knowledge within ORASSYLL is discussed. In contrast to systems in which object representations are defined manually the introduced constraints allow an autonomous learning from complex scenes. 1

Contents 1 Introduction 9 2 The a priori Constraints 13 2.1 The Bias/Variance Dilemma . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2 The Argument between Rationalism and Empiricism and its Resolution in Kant's Metaphysic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3 The Development of the Visual System . . . . . . . . . . . . . . . . . . . . 18 2.3.1 Developmental Psychology of Visual and Gripping Abilities . . . . 19 2.3.2 Development of the Visual System: Neurobiology . . . . . . . . . . 20 2.4 The a priori Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.4.1 Locality and the Correspondence Problem . . . . . . . . . . . . . . 24 2.4.2 Feature Selection and Feature Organization . . . . . . . . . . . . . 25 2.4.3 Evaluation of Features . . . . . . . . . . . . . . . . . . . . . . . . . 28 3 An Algorithm for the Learning of Weights 29 3.1 Weighted Average as Discrimination Function . . . . . . . . . . . . . . . . 29 3.2 Problem