Conceptual Hierarchies in a Flat Attractor Network: Dynamics of Learning and Computations

The structure of people's conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory.

[1]  Mark H. Johnson,et al.  Global-Before-Basic Object Categorization in Connectionist Networks and 2-Month-Old Infants. , 2000, Infancy : the official journal of the International Society on Infant Studies.

[2]  K. McRae,et al.  Automatic semantic similarity priming. , 1998 .

[3]  W. Nelson Francis,et al.  FREQUENCY ANALYSIS OF ENGLISH USAGE: LEXICON AND GRAMMAR , 1983 .

[4]  Stephen M. Kosslyn,et al.  Pictures and names: Making the connection , 1984, Cognitive Psychology.

[5]  Randi C. Martin,et al.  How semantic is automatic semantic priming , 1992 .

[6]  Jeffrey L. Elman,et al.  Exercises in Rethinking Innateness: A Handbook for Connectionist Simulations , 1997 .

[7]  Mark S. Seidenberg,et al.  Semantic feature production norms for a large set of living and nonliving things , 2005, Behavior research methods.

[8]  Barak A. Pearlmutter Gradient calculations for dynamic recurrent neural networks: a survey , 1995, IEEE Trans. Neural Networks.

[9]  Ken McRae,et al.  Semantic Memory: Some Insights from Feature-Based Connectionist Attractor Networks , 2004 .

[10]  T. Shallice,et al.  Connectionist Modelling in Cognitive Neuropsychology: A Case Study , 1994 .

[11]  Anne L. Fulkerson,et al.  The Influence of Labels, Non-Labeling Sounds, and Source of Auditory Input on 9- and 15-Month-Olds' Object Categorization , 2003 .

[12]  James L. McClelland,et al.  Distributed memory and the representation of general and specific information. , 1985, Journal of experimental psychology. General.

[13]  R. Gelman First Principles Organize Attention to and Learning About Relevant Data: Number and the Animate‐Inanimate Distinction as Examples , 1990 .

[14]  T. Rogers,et al.  Where do you know what you know? The representation of semantic knowledge in the human brain , 2007, Nature Reviews Neuroscience.

[15]  Ken McRae,et al.  Further evidence for feature correlations in semantic memory. , 1999, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.

[16]  S. Lupker Semantic Priming without Association: A Second Look. , 1984 .

[17]  L. Barsalou,et al.  Perceptual simulation in conceptual combination: evidence from property generation. , 2009, Acta psychologica.

[18]  Robert A. Randal how tall is a taxonomic tree? some evidence for dwarfism1 , 1976 .

[19]  B. Mesquita,et al.  Adjustment to Chronic Diseases and Terminal Illness Health Psychology : Psychological Adjustment to Chronic Disease , 2006 .

[20]  C. Frenck-Mestre,et al.  Semantic Features and Semantic Categories: Differences in Rapid Activation of the Lexicon , 1999, Brain and Language.

[21]  James L. McClelland,et al.  Semantic Cognition: A Parallel Distributed Processing Approach , 2004 .

[22]  J. H. Neely,et al.  Semantic priming in the pronunciation task: The role of prospective prime-generated expectancies , 1990, Memory & cognition.

[23]  J. F. Macario,et al.  Young children's use of color in classification: Foods and canonically colored objects , 1991 .

[24]  George S. Cree,et al.  Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of semantic memory. , 2006, Journal of experimental psychology. Learning, memory, and cognition.

[25]  David E. Rumelhart,et al.  Brain style computation: learning and generalization , 1990 .

[26]  K. Nelson,et al.  Context effects on lexical specificity in maternal and child discourse , 1986, Journal of Child Language.

[27]  Geoffrey E. Hinton,et al.  Learning distributed representations of concepts. , 1989 .

[28]  J. H. Neely,et al.  Semantic priming in the lexical decision task: roles of prospective prime-generated expectancies and retrospective semantic matching. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[29]  J. H. Neely Semantic priming effects in visual word recognition: A selective review of current findings and theories. , 1991 .

[30]  Paula J. Schwanenflugel,et al.  Interlingual semantic facilitation: Evidence for a common representational system in the bilingual lexicon , 1986 .

[31]  J. Mandler,et al.  Separating the sheep from the goats: Differentiating global categories , 1991, Cognitive Psychology.

[32]  Gregory L. Murphy,et al.  Hierarchical structure in concepts and the basic level of categorization. , 1997 .

[33]  Sandra R. Waxman,et al.  Mapping Words to the World in Infancy: Infants' Expectations for Count Nouns and Adjectives , 2003 .

[34]  A. Giovagnoli Connectionist modelling in cognitive neuropsychology: A case study , 1995, The Italian Journal of Neurological Sciences.

[35]  Ken McRae,et al.  Category - Specific semantic deficits , 2008 .

[36]  W. Marslen-Wilson,et al.  Accessing Different Types of Lexical Semantic Information: Evidence From Priming , 1995 .

[37]  Wayne D. Gray,et al.  Basic objects in natural categories , 1976, Cognitive Psychology.

[38]  Arthur B. Markman,et al.  Role-governed categories , 2001, J. Exp. Theor. Artif. Intell..

[39]  R. Brown How shall a thing be called. , 1958, Psychological review.

[40]  M. McCloskey,et al.  Natural categories: Well defined or fuzzy sets? , 1978 .

[41]  Lance J. Rips,et al.  Structure and process in semantic memory: A featural model for semantic decisions. , 1974 .

[42]  M. Garrett,et al.  Representing the meanings of object and action words: The featural and unitary semantic space hypothesis , 2004, Cognitive Psychology.

[43]  L. Barsalou,et al.  Verifying Different-Modality Properties for Concepts Produces Switching Costs , 2003, Psychological science.

[44]  L. Barsalou,et al.  Perceptual simulation in property verification , 2004, Memory & cognition.

[45]  J. Deese The structure of associations in language and thought , 1966 .

[46]  Allan Collins,et al.  A spreading-activation theory of semantic processing , 1975 .

[47]  Lance J. Rips,et al.  Semantic distance and the verification of semantic relations , 1973 .

[48]  Matthew Flatt,et al.  PsyScope: An interactive graphic system for designing and controlling experiments in the psychology laboratory using Macintosh computers , 1993 .

[49]  M. Masson A distributed memory model of semantic priming. , 1995 .

[50]  Lawrence W Barsalou,et al.  Abstraction in perceptual symbol systems. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[51]  Rochel Gelman,et al.  First Principles Organize Attention to and Learning About Relevant Data: Number and the Animate-Inanimate Distinction as Examples , 1990, Cogn. Sci..

[52]  Chris McNorgan,et al.  An attractor model of lexical conceptual processing: simulating semantic priming , 1999, Cogn. Sci..

[53]  D. E. Breedlove,et al.  General Principles of Classification and Nomenclature in Folk Biology , 1973 .

[54]  Mark S. Seidenberg,et al.  On the nature and scope of featural representations of word meaning. , 1997, Journal of experimental psychology. General.

[55]  W. Schneider,et al.  Perceptual Knowledge Retrieval Activates Sensory Brain Regions , 2006, The Journal of Neuroscience.

[56]  Geoffrey E. Hinton,et al.  Lesioning an attractor network: investigations of acquired dyslexia , 1991 .

[57]  E. Rosch,et al.  Family resemblances: Studies in the internal structure of categories , 1975, Cognitive Psychology.

[58]  L. Cohen,et al.  Labels can override perceptual categories in early infancy , 2008, Cognition.

[59]  A Pollatsek,et al.  On the use of counterbalanced designs in cognitive research: a suggestion for a better and more powerful analysis. , 1995, Journal of experimental psychology. Learning, memory, and cognition.

[60]  James L. McClelland,et al.  Understanding normal and impaired word reading: computational principles in quasi-regular domains. , 1996, Psychological review.

[61]  D. Plaut Graded modality-specific specialisation in semantics: A computational account of optic aphasia , 2002, Cognitive neuropsychology.

[62]  J. Hodges,et al.  Charting the progression in semantic dementia: implications for the organisation of semantic memory. , 1995 .

[63]  Edward J. Wisniewski,et al.  Superordinate and basic category names in discourse: A textual analysis , 1989 .

[64]  John R. Anderson A Spreading Activation Theory of Memory , 1988 .

[65]  Peter M. Todd,et al.  Learning and connectionist representations , 1993 .

[66]  E. Warrington Quarterly Journal of Experimental Psychology the Selective Impairment of Semantic Memory the Selective Impairment of Semantic Memory , 2022 .

[67]  J. L. Myers Fundamentals of Experimental Design , 1972 .

[68]  Diane Pecher,et al.  Verifying Properties from Different Modalities for Concepts Produces Switching Costs , 2002 .

[69]  G. Miller,et al.  Cognitive science. , 1981, Science.

[70]  Sandra R. Waxman,et al.  Words as Invitations to Form Categories: Evidence from 12- to 13-Month-Old Infants , 1995, Cognitive Psychology.

[71]  Edward E. Smith,et al.  Basic-level superiority in picture categorization , 1982 .

[72]  M. Ross Quillian,et al.  Retrieval time from semantic memory , 1969 .