Nature, nurture, and the development of functional specializations: A computational approach

The roles assigned to nature and nurture in the acquisition of functional specializations have been modified in recent years due to increasing evidence that experience-dependent processes are more influential in determining a brain region’s functional properties than was previously supposed. Consequently, one may study the developmental principles that play a role in the acquisition of functional specializations. This article studies the hypothesis that a combination of structure-function correspondences plus the use of competition between modules leads to functional specializations. This principle has been instantiated in a family of neural network architectures referred to as “mixtures-ofexperts” architectures. These architectures are sensitive to structure-function relationships in the sense that they often learn to allocate to each task a network whose structure is well matched to that task. The viewpoint advocated here represents a middle ground between nativist and constructivist views of modularity.

[1]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[2]  G. Ojemann,et al.  Cortical language localization in left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. , 1989, Journal of neurosurgery.

[3]  Michael I. Jordan,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.

[4]  P. Milner A model for visual shape recognition. , 1974, Psychological review.

[5]  Fengchun Peng,et al.  Bayesian Inference in Mixtures-of-Experts and Hierarchical Mixtures-of-Experts Models With an Applic , 1996 .

[6]  Leslie G. Ungerleider,et al.  Object vision and spatial vision: two cortical pathways , 1983, Trends in Neurosciences.

[7]  H. Neville Developmental specificity in neurocognitive development in humans. , 1995 .

[8]  D. O'Leary,et al.  Do cortical areas emerge from a protocortex? , 1989, Trends in Neurosciences.

[9]  M. Sur,et al.  Cross-modal plasticity in cortical development: differentiation and specification of sensory neocortex , 1990, Trends in Neurosciences.

[10]  J. Fodor Modularity of mind , 1983 .

[11]  J. Kruschke,et al.  ALCOVE: an exemplar-based connectionist model of category learning. , 1992, Psychological review.

[12]  M. Dennis,et al.  Language acquisition following hemidecortication: Linguistic superiority of the left over the right hemisphere , 1976, Brain and Language.

[13]  S. Kosslyn,et al.  Categorical versus coordinate spatial relations: computational analyses and computer simulations. , 1992, Journal of experimental psychology. Human perception and performance.

[14]  J. Beaumont Cerebral Lateralization: Biological Mechanisms, Associations, and Pathology , 1987 .

[15]  Steven Pinker,et al.  On language and connectionism , 1988 .

[16]  G. E. Peterson,et al.  Control Methods Used in a Study of the Vowels , 1951 .

[17]  Geoffrey E. Hinton,et al.  The Bootstrap Widrow-Hoff Rule as a Cluster-Formation Algorithm , 1990, Neural Computation.

[18]  M. Moscovitch LANGUAGE AND THE CEREBRAL HEMISPHERES: REACTION-TIME STUDIES AND THEIR IMPLICATIONS FOR MODELS OF CEREBRAL DOMINANCE , 1973 .

[19]  Steven J. Nowlan,et al.  Maximum Likelihood Competitive Learning , 1989, NIPS.

[20]  M. Gazzaniga CONSISTENCY AND DIVERSITY IN BRAIN ORGANIZATION * , 1977, Annals of the New York Academy of Sciences.

[21]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[22]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[23]  S. Kosslyn Seeing and imagining in the cerebral hemispheres: a computational approach. , 1987, Psychological review.

[24]  Geoffrey E. Hinton,et al.  Distributed Representations , 1986, The Philosophy of Artificial Intelligence.

[25]  Robert A. Jacobs,et al.  Encoding Shape and Spatial Relations: The Role of -Receptive Field Size in Coordinating Complementary Representations , 1994 .

[26]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[27]  Michael I. Jordan,et al.  Learning piecewise control strategies in a modular neural network architecture , 1993, IEEE Trans. Syst. Man Cybern..

[28]  Dana H. Ballard,et al.  Cortical connections and parallel processing: Structure and function , 1986, Behavioral and Brain Sciences.

[29]  J. Piaget The child's construction of reality , 1954 .

[30]  Geoffrey E. Hinton Shape Representation in Parallel Systems , 1981, IJCAI.

[31]  A. Karmiloff-Smith Précis of Beyond modularity: A developmental perspective on cognitive science , 1994, Behavioral and Brain Sciences.

[32]  J. Hellige,et al.  Categorical versus Coordinate Spatial Processing: Effects of Blurring and Hemispheric Asymmetry , 1994, Journal of Cognitive Neuroscience.

[33]  John K. Kruschke,et al.  Learning of rules that have high-frequency exceptions: New empirical data and a hybrid connectionist model , 2019, Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society.

[34]  S. Kosslyn,et al.  Why are What and Where Processed by Separate Cortical Visual Systems? A Computational Investigation , 1989, Journal of Cognitive Neuroscience.

[35]  Geoffrey E. Hinton,et al.  A general framework for parallel distributed processing , 1986 .

[36]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[37]  B. Laeng Lateralization of Categorical and Coordinate Spatial Functions: A Study of Unilateral Stroke Patients , 1994, Journal of Cognitive Neuroscience.

[38]  Michael I. Jordan,et al.  Hierarchies of Adaptive Experts , 1991, NIPS.

[39]  S. Pinker,et al.  On language and connectionism: Analysis of a parallel distributed processing model of language acquisition , 1988, Cognition.

[40]  M. Dennis,et al.  Comprehension of syntax in infantile hemiplegics after cerebral hemidecortication: Left-hemisphere superiority , 1975, Brain and Language.