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Time phases, pointers, rules and embedding

Published online by Cambridge University Press:  04 February 2010

John A. Barnden
John A. Barnden
Affiliation:
Computing Research Laboratory & Computer Science Department, New Mexico State University, Las Cruces, NM 88003-0001 Electronic mail: [email protected]
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Behavioral and Brain Sciences , Volume 16 , Issue 3 , September 1993 , pp. 451 - 452
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Copyright © Cambridge University Press 1993

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References

Aaronson, J. (1991) Dynamic fact communication mechanism: A connectionist interface. Proceedings of the Thirteenth Conference of the Cognitive Science Society. Erlbaum. [aLS]Google Scholar
Abeles, M. (1982) Local cortical circuits: Studies of brain function, vol. 6. Springer. [arLS]CrossRefGoogle Scholar
Abeles, M. (1991) Corticonics: Neural circuits of the cerebral cortex. Cambridge University Press. [aLS, WJF]CrossRefGoogle Scholar
Ajjanagadde, V. G. (1990) Reasoning with function symbols in a connectionist system. Proceedings of the Twelfth Conference of the Cognitive Science Society. Erlbaum. [aLS]Google Scholar
Ajjanagadde, V. G. (1991) Abductive reasoning in connectionist networks: Incorporating variables, background knowledge, and structured explananda. Technical Report WS1-91-7. Wilhelm-Schickard-Institute, University of Tubingen, Germany. [arLS, GH, DST]Google Scholar
Ajjanagadde, V. G. & Shastri, L. (1989) Efficient inference with multiplace predicates and variables in a connectionist system. Proceedings of the Eleventh Conference of the Cognitive Science Society.Erlbaum. [aLS]Google Scholar
Allen, J. F. (1987) Natural language understanding. Benjamin Cummings. [aLS]Google Scholar
Allen, J. F. & Perrault, C. R. (1980) Analyzing intention in utterances. Artificial Intelligence 15:143–78. [GH]CrossRefGoogle Scholar
Anderson, J. R. (1983) The architecture of cognition. Harvard University Press. [aLS]Google Scholar
Baddeley, A. (1986) Working memory. Clarendon Press. [arLS, SS]Google ScholarPubMed
Bair, W., Koch, C., Newsome, W., Britten, K. & Niebur, E. (1992) Power spectrum analysis of MT neurons from awake monkey. Society for Neuroscience Abstracts 18(1):11 12. [MPY]Google Scholar
Barnden, J. A. (1992) Connectionism, generalization and propositional attitudes: A catalogue of challenging issues. In: The symbolic and connectionist paradigms: Closing the gap, ed. Dinsmore, J.. Erlbaum. [JAB]Google Scholar
Barnden, J. A. & Srinivas, K. (1991) Encoding techniques for complex information structures in connectionist systems. Connection Science 3(3):263–309. [aLS, JAB]CrossRefGoogle Scholar
Barnes, D. & Hampson, P. J. (1992) Stimulus equivalence, relational frame theory and connectionism: Implications for behaviour analysis and cognitive science. Proceedings of the Fifteenth Symposium on Quantitative Analyses of Behavior. Harvard University Press. [PJH]Google Scholar
Bartlett, F. C. (1934) Remembering (2nd. ed. 1967). Cambridge University Press. [WJF]Google Scholar
Bibel, W. (1988) Advanced topics in automated deduction. In: Fundamentals of artificial intelligence II. ed. Nossum, R.. Springer. [SH]Google Scholar
Bienenstock, E. (1991) Notes on the growth of a “composition machine.” Presented at the Interdisciplinary Workshop on Compositionality in Cognition and Neural Networks, Abbaye de Royaumont, May. [aLS]Google Scholar
Bobrow, D. & Collins, A., eds. (1975) Representation and understanding. Academic Press. [aLS]Google Scholar
Bradski, G., Carpenter, G. A. & Grossberg, S. (1992a) Working memory networks for learning temporal order with application to 3-D visual object recognition. Neural Computation 4:270–86. [SG]CrossRefGoogle Scholar
Bradski, G., Carpenter, G. A. & Grossberg, S. (1992b) Working memories for storage and recall of arbitrary temporal sequences. Proceedings of the International joint Conferences on Neural Networks,Piscataway, NJ. [SG]Google Scholar
Braine, M. D. S. (1978) On the relationship between the natural logic of reasoning and standard logic. Psychological Review 85:1–21. [MO]CrossRefGoogle Scholar
Broadbent, D. E. (1958) Perception and communication. Pergamon. [MPY]CrossRefGoogle Scholar
Buchanan, B. C. & Shortliffe, E. F. (1984) Rule-based expert systems: The MYCIN experiments of the Stanford Heuristic Programming Project. Addison-Wesley. [aLS]Google Scholar
Bylander, T., Allemang, D., Tanner, M. C. & Josephson, J. R. (1991) The computational complexity of abduction. Artificial Intelligence 47(1–3):25–60. [aLS]CrossRefGoogle Scholar
Cahill, A. & Mitchell, D. C. (1987) Plans and goals in story comprehension. In: Communication failure in dialogue and discourse, ed. Reilly, R.. Elsevier. [GH]Google Scholar
Carpenter, G. A. & Grossberg, S., eds. (1991) Pattern recognition by self-organizing neural networks. MIT Press. [SG]CrossRefGoogle Scholar
Carpenter, G. A. & Grossberg, S., eds. (1992) A self-organizing neural network for supervised learning, recognition, and prediction. IEEE Communications 30:38–49. [SG]CrossRefGoogle Scholar
Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H. & Rosen, D. B. (1992) Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks 3:698–713. [SG]CrossRefGoogle ScholarPubMed
Carpenter, G. A., Grossberg, S. & Reynolds, J. H. (1991) ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks 4:565–88. [SG]CrossRefGoogle Scholar
Carpenter, P. A. & Just, M. A. (1977) Reading comprehension as eyes see it. In: Cognitive processes in comprehension, ed. Just, M. A. & Carpenter, P. A.. Erlbaum. [aLS]Google Scholar
Celebrini, S., Thorpe, S., Trotter, Y. & Imbert, M. (1993) Dynamics of orientation coding in area VI of the awake primate. Visual Neuroscience (in press). [SJT]CrossRefGoogle Scholar
Chalmers, D. J. (1990) Syntactic transformations on distributed representations. Connection Science 1&2(2):53–62. [GD, JWG]CrossRefGoogle Scholar
Charniak, E. (1976) Inference and knowledge (I and II). In: Computational semantics, ed. Charniak, E. & Wilks, Y.. North-Holland. [aLS]Google Scholar
Charniak, E. (1983) Passing markers: A theory of contextual influence in language comprehension. Cognitive Science 7:171–90. [aLS, GH]Google Scholar
Chater, N. & Oaksford, M. (1993) Logicism, mental models and everyday reasoning: Reply to Garnham. Mind & Language 8 (in press). [MO]CrossRefGoogle Scholar
Churchland, P. S., Koch, C. & Sejnowski, T. J. (1989) What is computational neuroscience? In: Computational neuroscience, ed. Schwartz, E.. MIT Press. [MO]Google Scholar
Clossman, G. (1988) A model of categorization and learning in a connectionist broadcast system. Ph.D. dissertation, Department of Computer Science, Indiana University. [aLS]Google Scholar
Cohen, P. R., Morgan, J. & Pollack, M. E., eds. (1990) Intentions in communication. MIT Press. [GH]CrossRefGoogle Scholar
Collins, A. & Michalski, R. (1989). The logic of plausible reasoning: A core theory. Cognitive Science 13(1):1–50. [rLS, DST]CrossRefGoogle Scholar
Cooke, N. J. (1992) Modeling human expertise in expert systems. In: The psychology of expertise: Cognitive research and empirical artificial intelligence, ed. Hoffman, R. R.. Springer. [GH]Google Scholar
Cooper, P. R. (1992) Structure recognition by connectionist relaxation: Formal analysis. Computational Intelligence 8(1):25–44. [PRC]CrossRefGoogle Scholar
Cooper, P. R. & Swain, M. J. (1992) Arc consistency: Parallelism and domain dependence. Artificial Intelligence 58:207–35. [PRC]CrossRefGoogle Scholar
Corriveau, J. (1991) Time-constrained memory for reader-based text comprehension. Technical Report CSRI-246. Ph.D. dissertation, Computer Science Research Institute, University of Toronto. [aLS]Google Scholar
Cottrell, G. (1985) Parallelism in inheritance hierarchies with exceptions. Proceedings of the Eighth International Joint Conference on Artificial Intelligence,Los Angeles, CA. [GWC]Google Scholar
Cottrell, G. (1989) A connectionist approach to word sense disambiguation. Pitman. [GWC]Google Scholar
Creutzfeldt, O., Ojemann, G. & Lettich, E. (1989) Neuronal activity in the human lateral temporal lobe. 1. Responses to speech. Experimental Brain Research 77:451–75. [SJT]Google Scholar
Crick, F. (1984) Function of the thalamic reticular complex: The searchlight hypothesis. Proceedings of the National Academy of Sciences 81:4586–90. [aLS]CrossRefGoogle ScholarPubMed
Crick, F. & Koch, C. (1990a) Towards a neurobiological theory of consciousness Seminars in Neurosciences 2:263–75. [aLS]Google Scholar
Crick, F. & Koch, C. (1990b) Some reflections on visual awareness Cold Spring Harbor Symposium on Quantitative Biology 55:953–62. [SG]CrossRefGoogle ScholarPubMed
Damasio, A. R. (1989) Time-locked multiregional retroactivation: A systems-level proposal for the neural substrates of recall and recognition. Cognition 33:25–62. [aLS]Google ScholarPubMed
Davis, P. (1990) Application of optical chaos to temporal pattern search in a nonlinear optical resonator. Japanese Journal of Applied Physics 29:L1238-40. [IT]CrossRefGoogle Scholar
Dawson, M. R. W. & Schopflocher, D. P. (1992) Autonomous processing in parallel distributed processing networks. Philosophical Psychology 5:199–219. [MRWD]Google Scholar
Dehaene, S. & Changeux, J-P. (1991) The Wisconsin card sorting test: Theoretical analysis and modeling in a neuronal network. Cerebral Cortex 1:62–79. [MO]CrossRefGoogle Scholar
Diederich, J. (1992) Inkrementelles Konnektionistisches Lernen. Forthcoming habilitation thesis, Department of Computer Science, University of Hamburg. [JD]Google Scholar
Dietz, P., Krizanc, D., Rajasekaran, S. & Shastri, L. (1993) A lower bound result for the common element problem and its implication for reflexive reasoning. Technical Report, Department of Computer and Information Science, University of Pennsylvania (forthcoming). [rLS]Google Scholar
Dolan, C. P. & Smolensky, P. (1989) Tensor product production system: A modular architecture and representation. Connection Science 1:53–68. [aLS, GSH, RR]CrossRefGoogle Scholar
Dorffner, G. & Rotter, M. (1992) On the virtues of functional connectionist compositionality. Proceedings of the Tenth European Conference on Artificial Intelligence, ed. Neumann, B.. Wiley. [GD]Google Scholar
Dosher, B. A. & Corbett, A. T. (1982) Instrument inferences and verb schemata. Memory and Cognition 10(6):531–39. [GH]CrossRefGoogle Scholar
Douglas, R. J., Martin, K .A. C. & Whitteridge, D. (1991) An intracellular analysis of the visual responses of neurons in cat visual cortex. Journal of Physiology 440:659–96. [RE]CrossRefGoogle ScholarPubMed
Downing, P. (1977) On the creation and use of English compound nouns. Language 53(4):810–42. [GH]CrossRefGoogle Scholar
Dwork, C., Kannelakis, P. C. & Mitchell, J. C. (1984) On the sequential nature of unification. Journal of Logic Programming 1:35–50. [SH]CrossRefGoogle Scholar
Dyer, M. (1983) In-depth understanding: A computer model of integrated processing for narrative comprehension. MIT Press. [aLS]CrossRefGoogle Scholar
Eckhorn, R. (1991) Stimulus-specific synchronizations in the visual cortex: Linking of local features into global figures? In: Neuronal cooperativity, ed. Kruger, J.. Springer. [SJT]Google Scholar
Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M. & Reitboeck, H. J. (1988) Coherent oscillations: A mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biological Cybernetics 60:121–30. [aLS, RE, WJF, IT, SJT]CrossRefGoogle ScholarPubMed
Eckhorn, R., Gruesser, O.-J., Kroeller, J., Pellnitz, K. & Poepel, B. (1976) Efficiency of different neural codes: Information transfer calculations for three different neural systems. Biological Cybernetics 22:49–60. [RE]CrossRefGoogle Scholar
Eckhorn, R. & Poepel, B. (1975) Rigorous and extended application of information theory to the afferent visual system of the cat. Biological Cybernetics 17:7–17. [RE]CrossRefGoogle Scholar
Eckhorn, R., Reitboeck, H. J., Arndt, M. & Dicke, P. (1990) Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex. Neural Computation 2:293–307. [aLS, RE]CrossRefGoogle Scholar
Eichenbaum, H., Wiener, S. I., Shapiro, M. L. & Cohen, N. J. (1989) The organization of spatial coding in the hippocampus: A study of neural ensemble activity. Journal of Neuroscience 9:2764–75. [GWS]Google ScholarPubMed
Elman, J. (1991) Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning 7:195–225. [JWG]CrossRefGoogle Scholar
Engel, A. K., Koenig, P., Gray, C. M. & Singer, W. (1990) Stimulus-dependent neuronal oscillations in cat visual cortex: Intercolumnar interactions as determined by cross-correlation analysis. European Journal of Neuroscience 2:588–606. [WJF, MPY]CrossRefGoogle ScholarPubMed
Engel, A. K., Koenig, P., Kreiter, A. K., Gray, C. M. & Singer, W. (1991) Temporal coding by coherent oscillations as a potential solution to the binding problem: Physiological evidence. In: Nonlinear dynamics and neural networks, ed. Schuster, H. G. & Singer, W.. Weinheim. [aLS]Google Scholar
Engel, A. K., Kroiter, A. K. & Singer, W. (1992) Oscillatory responses in the superior temporal sulcus of anesthetized macaque monkeys. Society for Neuroscience Abstracts 18:11.10. [rLS]Google Scholar
Etherington, D. & Reiter, R. (1983) On inheritance hierarchies with exceptions. Proceedings of the National Conference on Artificial Intelligence, Washington, D. C. [GWC]Google Scholar
Evans, J. St. B. T. (1972) Interpretation and matching bias in a reasoning task. Quarterly Journal of Experimental Psychology 24:193–99. [MO]CrossRefGoogle Scholar
Evans, J. St. B. T. (1982) The psychology of deductive reasoning. Routledge & Kegan Paul. [MO]Google Scholar
Evans, J. St. B. T. (1983) Linguistic determinants of bias in conditional reasoning. Quarterly Journal of Experimental Psychology 35A:635–44. [MO]CrossRefGoogle Scholar
Evans, J. St. B. T. (1989) Bias in human reasoning: Causes and consequences. Erlbaum. [MO]Google Scholar
Fahlman, S. E. (1979) NETL: A system for representing real-world knowledge. MIT Press. [aLS, GH, MO]CrossRefGoogle Scholar
Fahlman, S. E. (1981) Representing implicit knowledge. In: Parallel models of associative memory, ed. Hinton, G. E. & Anderson, J. A.. Erlbaum. [aLS, MO]Google Scholar
Fahlman, S. E., Hinton, G. E. & Sejnowski, T. J. (1983) Massively parallel architectures for AI: NETL, thistle, and Boltzmann machines. Proceedings of the National Conference on Artificial Intelligence. Morgan Kaufmann. [DST]Google Scholar
Fahlman, S. E., Touretzky, D. S. & van Roggen, W. (1981) Cancellation in a parallel semantic network. Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Morgan Kaufmann. [aLS]Google Scholar
Feldman, J. A. (1982) Dynamic connections in neural networks. Biological Cybernetics 46:27–39. [aLS, PRC]CrossRefGoogle ScholarPubMed
Feldman, J. A. (1985) Four frames suffice: A provisional model of vision and space. Behavioral and Brain Sciences 8:265–89. [PRC]CrossRefGoogle Scholar
Feldman, J. A. (1989) Neural representation of conceptual knowledge. In: Neural connections, mental computation, ed. Nadel, L., Cooper, L. A., Culicover, P. & Harnish, R. M.. MIT Press. [aLS]Google Scholar
Feldman, J. A. & Ballard, D. H. (1982) Connectionist models and their properties. Cognitive Science 6(3):205–54. [aLS, PRC]CrossRefGoogle Scholar
Fodor, J. A. (1983) Modularity of mind. MIT Press. [MO]CrossRefGoogle Scholar
Fodor, J. A. & Pylyshyn, Z. W. (1988a) Connectionism and cognitive architecture: A critical analysis. In: Connections and symbols, ed. Pinker, S. & Mehler, J., MIT Press. [aLS, DLM]Google Scholar
Fodor, J. A. & Pylyshyn, Z. W. (1988b) Connectionism and cognitive architecture: A critical analysis Cognition 28:3–71. [GD, MO]CrossRefGoogle ScholarPubMed
Freeman, M. J. (1975) Mass action in the nervous system. Academic Press. [WJF]Google Scholar
Freeman, M. J. (1981) A physiological hypothesis of perception. Perspectives in Biology and Medicine 24(4):561–92. [aLS]CrossRefGoogle ScholarPubMed
Freeman, M. J. (1987) Simulation of chaotic EEC patterns with a dynamic model of olfactory system. Biological Cybernetics 56:139–50. [IT]CrossRefGoogle Scholar
Freeman, M. J. (1991) The physiology of perception. Scientific American 264:78–85. [WJF, IT]CrossRefGoogle ScholarPubMed
Freeman, W. J. & van Dijk, B. (1987) Spatial patterns of visual cortical fast EEC during conditioned reflex in a rhesus monkey. Brain Research 422:267–76. [WJF]CrossRefGoogle Scholar
Frisch, A. M. & Allen, J. F. (1982) Knowledge retrieval as limited inference. In: Notes in computer science: Sixth conference on automated deduction, ed. Loveland, D. W.. Springer. [aLS]Google Scholar
Garnham, A. (1993) Is logicist cognitive science possible? Mind & Language 8 (in press). [MO]CrossRefGoogle Scholar
Gawne, T. J., Eskandar, E. N., Richmond, B. J. & Optican, L. M. (1991) Oscillations in the responses of neurons in inferior temporal cortex are not driven by stationary visual stimuli. Society for Neuroscience Abstracts 17(1):180.18. [MPY]Google Scholar
Geib, C. (1990) A connectionist model of medium-term memory. Term report, Department of Computer and Information Science, University of Pennsylvania. [aLS]Google Scholar
Geller, J. & Du, C. (1991) Parallel implementation of a class reasoner. Journal of Theoretical Artificial Intelligence 3:109–27. [aLS]CrossRefGoogle Scholar
Genesereth, M. R. & Nilsson, N. J. (1987) Logical foundations of artificial intelligence. Morgan Kaufmann. [aLS]Google Scholar
Gerstein, G. L. (1970) Functional association of neurons: Detection and interpretation. In: The neurosciences: Second study program, ed. Schmitt, F. O.. Rockefeller University Press. [aLS]Google Scholar
Gibbs, R. W. Jr. (1983) Do people always process the literal meanings of indirect requests? Journal of Experimental Psychology: Learning, Memory, and Cognition 9:524–33. [GH]Google Scholar
Gilbert, C. D. & Wiesel, T. (1992) Receptive field dynamics in adult primary visual cortex. Nature 356:150–52. [JD]CrossRefGoogle ScholarPubMed
Gray, C. M., Engel, A. K., Koenig, P. & Singer, W. (1991) Properties of synchronous oscillatory neuronal interactions in cat striate cortex. In: Nonlinear dynamics and neural networks, ed. Schuster, H. G. & Singer, W.. Weinheim: VCH Publishers. [aLS, RE]Google Scholar
Gray, C. M., Koenig, P., Engel, A. K. & Singer, W. (1989) Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338:334–37. [aLS, IT, SJT]CrossRefGoogle ScholarPubMed
Gray, C. & Singer, W. (1989) Stimulus-specific neural oscillations in orientation specific columns of the visual cortex. Proceedings of the National Academy of Science 86:1698–1702. [aLS, RE]CrossRefGoogle Scholar
Gross, H., Koerner, E., Boehme, H. & Pomierski, T. (1992) A neural network hierarchy for data and knowledge controlled selective visual attention. In: Artificial neural networks, 2, ed. Aleksander, I. & Taylor, J.. North-Holland. [EK]Google Scholar
Grossberg, S. (1976) Adaptive pattern classification and universal recoding, II: Feedback, expectation, olfaction, and illusions. Biological Cybernetics 23:187–202. [SC]CrossRefGoogle ScholarPubMed
Grossberg, S. (1978) A theory of visual coding, memory, and development. In: Formal theories of visual perception, ed. Leeuwenberg, E. & Buffart, H.. Wiley. [SG]Google Scholar
Grossberg, S. ed. (1987a) The adaptive brain, vols. 1 & 2. Elsevier/North-Holland. [SG]Google Scholar
Grossberg, S. ed. (1987b) Competitive learning: From interactive activation to adaptive resonance. Cognitive Science 11:23–63. [MRWD]CrossRefGoogle Scholar
Grossberg, S. ed. (1988) Neural networks and natural intelligence. MIT Press. [SG]Google Scholar
Grossberg, S. & Mingolla, E. (1985a) Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading Psychological Review 92:173–211. [SG]CrossRefGoogle ScholarPubMed
Grossberg, S. & Mingolla, E. (1985b) Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations Perception & Psychophysics 38:141–71. [SG]Google ScholarPubMed
Grossberg, S. & Somers, D. (1991) Synchronized oscillations during cooperative feature linking in a cortical model of visual perception. Neural Networks 4:453–66. [SG]CrossRefGoogle Scholar
Grossberg, S. & Somers, D. (1992) Synchronized oscillations for binding spatially distributed feature codes into coherent spatial patterns. In: Neural networks for vision and image processing, ed. Carpenter, G. A. & Grossberg, S.. MIT Press. [SG]Google Scholar
Guha, R. V. & Lenat, D. B. (1990) Cyc: A mid-term report. Artificial Intelligence Magazine 11(3):32–59. [aLS]Google Scholar
Halford, G. S., Wilson, W. H., Guo, J., Gayler, R. W., Wiles, J. & Stewart, J. E. M. (1993) Connectionist implications for processing capacity limitations in analogies. In: Advances in connectionist and neural computational theory, vol. 2, ed. Holyoak, K. J. & Barnden, J. A.. Ablex. [GSH]Google Scholar
Hanson, S. J. & Kegl, J. (1987) PARSNIP: A connectionist network that learns natural language grammar from exposure to natural language sentences. Proceedings of the Ninth Annual Cognitive Science Society Conference, Seattle, Wa. [GWC]Google Scholar
Harnad, S. (1990) The symbol grounding problem. Physica D 42:335–46. [rLS]CrossRefGoogle Scholar
Hatfield, H. (1991) Representation and rule-instantiation in connectionist networks. In: Connectionism and the philosophy of mind, ed. Horgan, T. & Tienson, J.. Kluwer Academic. [arLS]Google Scholar
Hayes, P. J. (1977) In defense of logic. Proceedings of the Fifth Annual International Joint Conference on Artificial Intelligence, Cambridge, MA. [GWC]Google Scholar
Hayes, S. C. (1991) A relational control theory of stimulus equivalence. In: Rule-governed behavior: Cognition, contingencies and instructional control, ed. Hayes, L. J. & Chase, P. N.. Plenum. [PJH]Google Scholar
Hebb, D. O. (1949) The organization of behavior. Wiley. [aLS, CWC, GP]Google Scholar
Henderson, J. (1992) A connectionist parser for structure unification grammar. Proceedings of the Thirtieth Annual Meeting of the Association of Computational Linguistics. Association of Computational Linguistics. [arLS]Google Scholar
Handler, J. (1987) Integrating marker-passing and problem solving: A spreading activation approach to improved choice in planning. Erlbaum. [aLS, GH, MO]Google Scholar
Hinton, G. E. (1981) Implementing semantic networks in parallel hardware. In: Parallel models of associative memory, ed. Hinton, G. E. & Anderson, J. A.. Erlbaum. [aLS]Google Scholar
Hinton, G. E. (1986) Learning distributed representations of concepts. Proceedings of the Eighth Annual Conference of the Cognitive Science Society. Erlbaum. [CD]Google Scholar
Hirst, G. (1987) Semantic interpretation and the resolution of ambiguity. Cambridge University Press. [aLS, GH]CrossRefGoogle Scholar
Hirst, G. (1988) Resolving lexical ambiguity computationally with spreading activation and polaroid words. In: Lexical ambiguity resolution, ed. Small, S., Cottrell, G. & Tanenhaus, M. K.. Morgan Kaufmann. [GH]Google Scholar
Hirst, G. & Charniak, E. (1982) Word sense and case slot disambiguation. Proceedings of the Second National Conference on Artificial Intelligence, Pittsburgh. [GH]Google Scholar
Holden, A. V. & Kryukov, V. I., eds. (1991) Neurocomputers and attention I & II. Proceedings in nonlinear science. Manchester University Press. [IT]Google Scholar
Hölldobler, S. (1990) CHCL: A connectionist inference system for Horn logic based on the connection method and using limited resources. Technical Report 90–042. International Computer Science Institute, Berkeley, CA. [aLS, SH]Google Scholar
Horn, D., Sagi, D. & Usher, M. (1991) Segmentation, binding, and illusory conjunctions. Neural computation 3(4):510–25. [aLS]CrossRefGoogle ScholarPubMed
Hubel, D. H. & Wiesel, T. N. (1962) Receptive fields, binocular interaction and functional architectures of the cat's visual cortex. Journal of Physiology 160:106–54. [WJF]CrossRefGoogle ScholarPubMed
Hummel, J. E. & Biederman, I. (1992) Dynamic binding in a neural network for shape recognition. Psychological Review 99:480–517. [aLS, SJT]CrossRefGoogle Scholar
Hummel, J. E., Burns, B. & Holyoak, K. J. (in press) Analogical mapping by dynamic binding: Preliminary investigations. In: Advances in conneetionist and neural computation theory, vol. 2: Analogical connections, ed. K. J. Holyoak & J. A. Barnden. Ablex. [GSH, JEH]Google Scholar
Hummel, J. E. & Holyoak, K. J. (1992) Indirect analogical mapping. Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society. Erlbaum. [JEH]Google Scholar
Humphreys, M. S., Bain, J. D. & Pike, R. (1989) Different ways to cue a coherent memory system: A theory for episodic, semantic and procedural tasks. Psychological Review 96(2):208–33. [GSH]CrossRefGoogle Scholar
Ikeda, K., Otsuka, K. & Matsumoto, K. (1989) Maxwell-Bloch turbulence. Progress of Theoretical Physics (suppl.)99:295–324. [IT]CrossRefGoogle Scholar
James, W. (1890) Psychology (Briefer course). Holt. [GWC]Google Scholar
Johannesma, P., Aertsen, A., Vanden Boogaard, H., Eggermont, J. & Epping, W. (1986) From synchrony to harmony: Ideas on the function of neural assemblies and on the interpretation of neural synchrony. In: Brain theory, ed. Palm, G. & Aertsen, A.. Springer. [GP]Google Scholar
Johnson-Laird, P. N. (1983) Mental models. Cambridge University Press. [MIB, MO]Google Scholar
Johnson-Laird, P. N. (1988) The computer and the mind. Harvard University Press. [MIB]Google Scholar
Johnson-Laird, P. N. & Byrne, R. M. J. (1991) Deduction. Erlbaum. [MO]Google Scholar
Just, M. A. & Carpenter, P. A., eds. (1977) Cognitive processes in comprehension. Erlbaum. [aLS]Google Scholar
Kaneko, K. (1989) Pattern dynamics in spatio-temporal chaos. Physica 34D:1–41. [IT]Google Scholar
Kaneko, K. (1990) Clustering, switching, hierarchical ordering and control in a network of chaotic elements. Physica 41 D: 137–72. [IT]Google Scholar
Kautz, H. A. & Selman, B. (1991) Hard problems for simple default logics. Artificial Intelligence 47 (1–3):243–79. [aLS]CrossRefGoogle Scholar
Keenan, J. M., Baillet, S. D. & Brown, P. (1984) The effects of causal cohesion on comprehension and memory. Journal of Verbal Learning and Verbal Behavior 23:115–26. [aLS]CrossRefGoogle Scholar
Kintsch, W., ed. (1974) The representation of meaning in memory. Erlbaum. [aLS]Google Scholar
Kintsch, W., ed. (1988) The role of knowledge discourse comprehension: A construction-integration model. Psychological Review 95:163–82. [aLS]CrossRefGoogle ScholarPubMed
Kiper, D. C., Cegenfurtner, K. R. & Movshon, J. A. (1991) The effect of 40Hz flicker on the perception of global stimulus properties. Society for Neuroscicnce Abstracts 17(2):479.4. [MPY]Google Scholar
Klayman, J. & Ha, Y. (1987) Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review 94:211–28. [SS]CrossRefGoogle Scholar
Koerner, E. & Boehme, H. (1991) Organization of an episodic knowledge base in a neural network architecture with parallel-sequential processing modes for autonomous recognition and learning. In: Artificial neural networks, ed. Kohonen, T., Mackisara, K., Simula, O. & Kangas, J.. Elsevier/North-Holland. [EK]Google Scholar
Koerner, E., Gross, H. & Boehme, H. (1991) Elementary cognitive mechanisms for knowledge based image interpretation. In: Proceedings of the International Workshop on Adaptive Learning and Neural Networks, ed. Bock, P., Loew, M., Radermacher, F. J. & Richter, M. M.. Ulm: Forschungsinstitut für Anwendungs orientierte Wissensrerarbeitung. [EK]Google Scholar
Koerner, E., Gross, H. & Tsuda, I. (1990) Holonic processing in a model system of cortical processors. In: Biological complexity and information, ed. Shimizu, H.. World Scientific. [EK]Google Scholar
Koerner, E., Salevski, H., Shimizu, H., Koerner, U. & Seifert, S. (submitted) A structured neural network model of hippocampus and its function as a nonspecific controller of cortical decision making and nontrivial learning. [EK]Google Scholar
Koerner, E., Shimizu, H. & Tsuda, I. (1987) Parallel in sequence: Towards the architecture of an elementary cortical processor. In: Parallel algorithms and architectures, ed. Albrecht, A., Hung, H. & Mehlhorn, G.. Akademie-Verlag. [EK]Google Scholar
Koerner, E., Tsuda, I. & Shimizu, H. (1987) Take-grant control, variable byte formation and processing parallel in sequence: Characteristics of a new type of holonic processor. In: Parallel algorithms and architecture, ed. Albrecht, A., Jung, H. & Mehlhorn, G.. Springer. [IT]Google Scholar
Kosslyn, S. M., Murphy, G. L., Bemesderfer, M. E. & Feinstein, K. J. (1977) Category and continuum in mental comparisons. Journal of Experimental Psychology: General 106:341–75. [PJH]CrossRefGoogle Scholar
Kreiter, A. K., Engel, A. K. & Singer, W. (1992) Stimulus dependent synchronization in the caudal superior temporal sulcus of macaque monkeys. Society for Neuroscience Abstracts 18:11.11. [rLS]Google Scholar
Kreiter, A. K. & Singer, W. (1992) Oscillatory neuronal responses in the visual cortex of the awake macaque monkey. European Journal of Neuroscience 4:369–75. [aLS, IT]CrossRefGoogle ScholarPubMed
Kruse, W., Eckhorn, R., Schanze, T. & Reitboeck, H. J. (1992) Stimulus-induced oscillatory synchronization is inhibited by stimulus-locked non-oscillatory synchronization in cat visual cortex: Two modes that might support feature linking. Society for Neuroscicnce Abstracts 18:131.3. [RE]Google Scholar
Kuramoto, Y. (1991) Collective synchronization of pulse-coupled oscillators and excitable units. Physica 50D: 15–30. [IT]Google Scholar
Lado, F., Ribary, U., loannides, A., Volkman, J., Joliot, M., Mogilner, A. & Llinás, R. (1992) Coherent oscillations in motor and sensory cortices detected using MEG and MFT. Society for Neuroscience Abstracts 18:355.15. [rLS]Google Scholar
Lakoff, G. (1987) Women, fire, and dangerous things: What categories reveal about the mind. University of Chicago Press. [aLS, SS, DST]Google Scholar
Lakoff, G. & Johnson, M. (1980) Metaphors we live by. University of Chicago Press. [DST]Google Scholar
Lange, T. E. & Dyer, M. G. (1989) High-level inferencing in a conneetionist network. Connection Science 1(2):181–217. [aLS, JAB, GWC]CrossRefGoogle Scholar
Lehnert, W. G. & Ringle, M. H., eds. (1982) Strategies for natural language processing. Erlbaum. [aLS]Google Scholar
Lettvin, J. Y., Maturana, H. R., McCulloch, W. S. & Pitts, W. H. (1959) What the frog's eye tells the frog's brain. Proceedings of the Institute of Radio Engineering 47:1940–51. [WJF]Google Scholar
Levesque, H. J. (1988) Logic and the complexity of reasoning. Journal of Philosophical Logic 17:335–89. [aLS]CrossRefGoogle Scholar
Levesque, H. J. & Brachman, R. J. (1985) A fundamental tradeoff in knowledge representation and reasoning. In: Readings in knowledge representation, ed. Brachman, R. J. & Levesque, H. J.. Morgan Kaufmann. [aLS, GWC]Google Scholar
Levi, J. N. (1978) The syntax and semantics of complex nominals. Academic Press. [GH]Google Scholar
Livingstone, M. S. (1991) Visually evoked oscillations in monkey striate cortex. Society for Neuroscience Abstracts 17:73.3. [rLS]Google Scholar
Lucas, M. M., Tanenhaus, M. K. & Carlson, G. N. (1990) Levels of representation in the interpretation of anaphoric reference and instrument inference. Memory and Cognition 18(6):611–31. [GH]CrossRefGoogle ScholarPubMed
Lynch, G. (1986) Synapses, circuits, and the beginnings of memory. MIT Press. [aLS]Google Scholar
MacVicar, B. & Dudek, F. E. (1980) Dye-coupling between CA3 pyramidal cells in slices of rat hippocampus. Brain Research 196:494–97. [aLS]CrossRefGoogle ScholarPubMed
Malloch, M. I., Oaksford, M. & Iddon, J. (1992) Impairments of reasoning, memory and planning in early stage Parkinsonism. Technical Report No. UWBCNU-TR-13, Cognitive Neurocomputation Unit, University of Wales, Bangor. [MO]Google Scholar
Mandelbaum, R. (1991) A robust model for temporal synchronization of distant nodes: Description and simulation. Term Report, Department of Computer and Information Science, University of Pennsylvania. [aLS]Google Scholar
Mandelbaum, R. & Shastri, L. (1990) A robust model for temporal synchronisation of distant nodes. (Unpublished report.) [aLS]Google Scholar
Mani, D. R. & Shastri, L. (1991) Combining a connectionist type hierarchy with a connectionist rule-based reasoner. Proceedings of the Thirteenth Conference of the Cognitive Science Society. Erlbaum. [aLS]Google Scholar
Mani, D. R. & Shastri, L. (1992) A connectionist solution to the multiple instantiation problem using temporal synchrony. Proceedings of the Fourteenth Conference of the Cognitive Science Society. Erlbaum. [aLS]Google Scholar
Marr, D. (1971) Simple memory: A theory for archicortex. Philosophical Transactions of the Royal Society B 262:23–81. [aLS]Google ScholarPubMed
Martin, C. E. & Riesbeck, C. K. (1986) Uniform parsing and inferencing for learning. Proceedings of the Fifth National Conference on Artificial Intelligence. Philadelphia. [GH]Google Scholar
Matsumoto, K. & Tsuda, I. (1987) Extended information in one-dimensional maps. Physica 26D:347–57. [IT]Google Scholar
McAllester, D. A. (1990) Automatic recognition of tractability in inference relations. Memo 1215, MIT Artificial Intelligence Laboratory. [aLS]Google Scholar
McCarthy, J. (1988) Epistemological challenges for connectionism [Commentary on Smolensky]. Behavioral and Brain Sciences 11(1):44. [aLS]CrossRefGoogle Scholar
McDermott, D. (1981) Artificial intelligence meets natural stupidity. In: Mind design, ed. Haugland, J.. MIT Press/Bradford Books. [DLM]Google Scholar
McDermott, D. (1986) A critique of pure reason. Technical Report, Department of Computer Science, Yale University. [MO]Google Scholar
McKendall, T. (1991) A design for an answer extraction and display scheme for a connectionist rule-based reasoner. Unpublished report on work done for National Science Foundation, Research Experience for Undergraduates grant IRI 88–05465. [aLS]Google Scholar
McKoon, G. & Ratcliff, R. (1980) The comprehension processes and memory structures involved in anaphoric reference. Journal of Verbal Learning and Verbal Behavior 19:668–82. [aLS]CrossRefGoogle Scholar
McKoon, G. & Ratcliff, R. (1981) The comprehension processes and memory structures involved in instrumental inference. Journal of Verbal Learning and Verbal Behavior 20:671–82. [aLS]CrossRefGoogle Scholar
McKoon, G. & Ratcliff, R. (1986) Inferences about predictable events. Journal of Experimental Psychology: Learning, Memory, and Cognition 12:82–91. [aLS]Google ScholarPubMed
McMillan, C., Mozer, M. & Smolensky, P. (1991): The connectionist scientist game. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society. Erlbaum. [GD]Google Scholar
McRoy, S. W. (1993) Abductive interpretation and re-interpretation of natural language utterances. Ph.D. dissertation, Department of Computer Science, University of Toronto. [GH]Google Scholar
McRoy, S. W. & Hirst, G. (1993) Abductive explanations of dialogue misunderstanding. Proceedings, Sixth Conference of the European Chapter of the Association for Computational Linguistics, Utrecht. [GH]Google Scholar
Merzenich, M. M., Recanzone, G., Jenkins, W. M., Allard, T. T. & Nudo, R. J. (1988) Cortical representational plasticity. In: Neurobiology of neocortex, ed. Rakie, P. & Singer, W.. Wiley. [JD]Google Scholar
Miller, G. A. (1956) The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review 63(2):81–97 [aLS, GSH, EK]CrossRefGoogle ScholarPubMed
Milner, B. (1963) Effects of different brain lesions on card sorting. Archives of Neurology 9:90–100. [MO]Google Scholar
Minsky, M. (1975) A framework for representing knowledge. In: The psychology of computer vision, ed. Winston, P. M.. McGraw-Hill. [aLS]Google Scholar
Minsky, M. (1985) The society of mind. Simon & Schuster. [EK]Google Scholar
Mountcastle, V. B. (1957) Modality and topographic properties of single neurons of cat's somatic cortex. Journal of Neurophysiology 20:408–34. [WJF]CrossRefGoogle Scholar
Mozer, M. C., Zemel, R. S. & Behrman, M. (1991) Learning to segment images using dynamic feature binding. Technical Report CU-CS-540-91, University of Colorado at Boulder. [aLS]Google Scholar
Newell, A. (1980) Harpy, production systems and human cognition. In: Perception and production of fluent speech, ed. Cole, R.. Erlbaum. [aLS]Google Scholar
Newell, A. (1990) Unified theories of cognition. Harvard University Press. [arLS]Google Scholar
Newell, A. & Simon, H. A. (1972) Human problem solving. Prentice-Hall. [aLS]Google Scholar
Norman, D. A. & Shallice, T. (1985) Attention to action: Willed and automatic control of behaviour. In: Consciousness and self-regulation, vol. 4, ed. Davidson, R. J., Schwartz, G. E. & Shapiro, D.. Plenum. [MO]Google Scholar
Norvig, P. (1989) Marker passing as a weak method for text inferencing. Cognitive Science 113:569–620. [aLS, GH]CrossRefGoogle Scholar
Oaksford, M. (1993) Mental models and the tractability of everyday reasoning. Behavioral and Brain Sciences 16(2):360–61. [MO]CrossRefGoogle Scholar
Oaksford, M. & Chater, N. (1991) Against logicist cognitive science. Mind & Language 6:1–38. [MO]CrossRefGoogle Scholar
Oaksford, M. & Chater, N. (1992a) Reasoning theories and bounded rationality. In: Rationality, ed. Manktelow, K. & Over, D.. Routledge. [MO]Google Scholar
Oaksford, M. & Chater, N. (1992b) Bounded rationality in taking risks and drawing inferences. Theory & Psychology 2:225–30. [MO]CrossRefGoogle Scholar
Oaksford, M. & Chater, N. (in press) Cognition and inquiry. Academic Press. [MO]Google Scholar
Oaksford, M., Malloch, M. I. & Swain, S. (1992a) Transitive inference in closed head injury: A single case study. Technical Report No. UWBCNU-TR-12, Cognitive Neuroeomputation Unit, University of Wales, Bangor. [MO]Google Scholar
Oaksford, M., Malloch, M. I., Watson, F. & Hargreaves, I. (1992b) Impairments of reasoning, memory and attention in frontal lobe damage: A single case study. Technical Report No. UWBCNU-TR-11, Cognitive Neuroeomputation Unit, University of Wales, Bangor. [MO]Google Scholar
Oaksford, M. & Stenning, K. (1992) Reasoning with conditionals containing negated constituents. Journal of Experimental Psychology: Learning, Memory & Cognition 18:835–54. [MO]Google ScholarPubMed
Oram, M. W. & Perrett, D. I. (1992) Time course of neural responses discriminating different views of the face and head. Journal of Neurophysiology 69:70–84. [SJT]CrossRefGoogle Scholar
Pabst, M., Reitboeck, H. J. & Eckhorn, R. (1989) A model of preattentive region definition based on texture analysis. In: Models of brain function, ed. Cotterill, R. M. J.. Cambridge University Press. [RE]Google Scholar
Palm, G. (1982) Neural assemblies: An alternative approach to artificial intelligence. Springer. [GP]CrossRefGoogle Scholar
Palm, G. (1986) Associative networks and cell assemblies. In: Brain theory, ed. Palm, G. & Aertsen, A.. Springer. [GP]CrossRefGoogle Scholar
Palm, G. (1990) Cell assemblies as a guideline for brain research. Concepts in Neuroscience 1:133–14. [GP]Google Scholar
Pelletier, F. J. (1982) Completely non-causal, completely heuristic-ally driven, automated theorem proving. Technical Report 82–7, Department of Computing Science, University of Alberta. [MRWD]Google Scholar
Pfeifer, R. & Verschure, P. (1992) Beyond rationalism: Symbols, patterns and behavior. Connection Science 4:313–25. [JD]Google Scholar
Pollack, J. B. (1988) Recursive auto-associative memory: Devising compositional distributed representations. Technical report MCCS-88-124, Computing Research Laboratory, New Mexico State University. [GH]Google Scholar
Pollack, J. B. (1990) Recursive distributed representations. Artificial Intelligence 46:77–105. [GD, GH]CrossRefGoogle Scholar
Posner, M. I. & Snyder, C. R. R. (1975) Attention and cognitive control. In: Information processing and cognition: The Loyola Symposium, ed. Solso, R. L.. Erlbaum. [aLS]Google Scholar
Potts, G. R., Keenan, J. M. & Golding, J. M. (1988) Assessing the occurrence of elaborative inferences: Lexical decision versus naming. Journal of Memory and Language 27:399–415. [aLS]CrossRefGoogle Scholar
Quillian, M. R. (1968) Semantic memory. In: Semantic information processing, ed. Minsky, M.. MIT Press. [aLS]Google Scholar
Ramesh, R., Verma, R. M., Krishnaprasad, T. & Ramakrishnan, I. V. (1989) Term matching on parallel computers. Journal of Logic Programming 6:213–28. [SH]CrossRefGoogle Scholar
Reder, L. M. & Ross, B. H. (1983) Integrated knowledge in different tasks: The role of retrieval strategy on fan effects. Journal of Experimental Psychology: Learning, Memory, and Cognition 9:55–72. [aLS]Google Scholar
Reitboeck, H. J., Eckhorn, R., Arndt, M. & Dicke, P. (1990) A model for feature linking via correlated neural activity. In: Synergetics of cognition. Springer series in synergetics, vol. 45, ed. Haken, H. & Stadler, M.. Springer. [IT]CrossRefGoogle Scholar
Reiter, R. (1980) A logic for default reasoning. Artificial Intelligence 13:81–132. [rLS]CrossRefGoogle Scholar
Riesbeck, C. R. & Schank, R. C. (1989) Inside case-based reasoning. Erlbaum. [PRC]Google Scholar
Rips, L. J. (1983) Cognitive processes in propositional reasoning. Psychological Review 90:38–71. [MO]CrossRefGoogle Scholar
Rohwer, R. A. (1993) A representation of representation applied to a discussion of variable binding. In: Neurodynamics and psychology, ed. Oaksford, M. & Brown, G.. Academic Press. [RR]Google Scholar
Rolls, E. T. (1991) Neural organisation of higher visual functions. Current Opinion in Neurobiology 1:274–78. [aLS, MPY]CrossRefGoogle ScholarPubMed
Rotter, M. & Dorffner, G. (1990) Struktur und Konzeptrelationen in verteilten Netzwerken. In: Konnektionismus in Artificial Intelligence und Kognitionsforschung, ed. Dorffner, G.. Springer. [GD]Google Scholar
Rumelhart, D. E. (1989) Toward a microstructural account of human reasoning. In: Similarity and analogical reasoning, ed. Vosnaidou, S. & Ortony, A.. Cambridge Universtiy Press. [MO]Google Scholar
Rumelhart, D. E. & McClellan, J. L., eds. (1986) Parallel distributed processing: Explorations in the microstructure of cognition, vol 1. Bradford Books/MIT Press. [aLS]CrossRefGoogle Scholar
Rumelhart, D. E., Smolensky, P., McClelland, J. L. & Hinton, G. E. (1986) Schemata and sequential thought processes in PDF models. In: Parallel distributed processing: Explorations in the microstructure of cognition, vol. 2: Psychological and biological processes, ed. McClelland, J. L. & Rumelhart, D. E.. MIT Press. [MO]Google Scholar
Schank, R. C. & Abelson, R. P. (1977) Scripts, plans, goals and understanding. Erlbaum. [aLS]Google Scholar
Schauze, T. & Eckhorn, R. (1991) Synchronization statistics of stimulusspecific oscillatory events in cat visual cortex. In: Synapse, transmission, modulation, ed. Eisner, N. & Penzlin, H.. Thieme Verlag. [RE]Google Scholar
Schneider, W. & Shiffrin, R. M. (1977) Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review 84:1–66. [aLS]Google Scholar
Schubert, L. K. (1989) An episodic knowledge representation for narrative texts. Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning. Morgan Kaufmann. [aLS]Google Scholar
Sejnowski, T. J. (1981) Skeleton filters in the brain. In: Parallel models of associative memory, ed. Hinton, G. E. & Anderson, J. A.. Erlbaum. [aLS]Google Scholar
Servan-Schreiber, D., Cleeremans, A. & McClelland, J. (1989) Encoding semantical structure in simple recurrent nets. In: Advances in neural information processing systems 1, ed. Touretzsky, D.. Morgan Kaufmann. [JWG]Google Scholar
Shallice, T. (1982) Specific impairments of planning. Philosophical Transactions of the Royal Society of London B 298:199–209. [MO]Google ScholarPubMed
Sharkey, N. E. (1992) The causal role of the constituents of superpositional representations. In: Cybernetics and systems 92, ed. Trappl, R.. World Scientific. [CD]Google Scholar
Shastri, L. (1988a) Semantic networks: An evidential formulation and its connectionist realization. Pitman/Morgan Kaufmann. [arLS, PRC]Google Scholar
Shastri, L. (1988b) A connectionist approach to knowledge representation and limited inference. Cognitive Science 12(3):331–92. [arLS, GWC]CrossRefGoogle Scholar
Shastri, L. (1990) Connectionism and the computational effectiveness of reasoning. Theoretical Linguistics 16(1):65–87. [aLS]CrossRefGoogle Scholar
Shastri, L. (1991) Relevance of connectionism to AI: A representation and reasoning perspective. In: Advances in connectionist and neural computation theory, vol. 1, ed. Barnden, J. & Pollack, J.. Ablex. [aLS]Google Scholar
Shastri, L. (1992) Encoding higher-order bindings in LCS structures. Working notes for the NLQ-Project. National Science Foundation. [rLS]Google Scholar
Shastri, L. (1993a) A realization of preference rules using temporal synchrony (in preparation). [aLS]Google Scholar
Shastri, L. (1993b) Learning evidential rules in SHRUTI (in preparation). [rLS]Google Scholar
Shastri, L. & Ajjanagadde, V. G. (1990) A connectionist representation of rules, variables and dynamic binding. Technical Report MS-CIS-90-05, Department of Computer and Information Science, University of Pennsylvania. [aLS]Google Scholar
Shastri, L. & Feldman, J. A. (1986) Semantic nets, neural nets, and routines. In: Advances in cognitive science, ed. Sharkey, N.. Ellis Harwood/Wiley. [arLS]Google Scholar
Shiffrin, R. M. & Schneider, W. (1977) Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review 84:127–90. [aLS]Google Scholar
Shimizu, H. & Yamaguchi, Y. (1987) Synergetic computers and holoniesinfonnation dynamics of semantic computers. Physica Scripta 36:970–85. [IT]CrossRefGoogle Scholar
Shimizu, H., Yamaguchi, Y., Tsuda, I. & Yano, M. (1985) Pattern recognition based on holonic information dynamics. In: Complex systems-operational approaches, ed. Haken, H.. Springer Series in Synergetics, vol. 31. [EK]Google Scholar
Singer, M. & Ferreira, F. (1983) Inferring consequences in story comprehension. Journal of Verbal Learning and Verbal Behavior 22:437–48. [aLS]Google Scholar
Singer, W. (1987) Activity-dependent self-organization of synaptic connections as a substrate of learning. In: The neural and molecular bases of learning, ed. Changeux, J.-P. & Konishi, M.. Wiley. [JD]Google Scholar
Skarda, C. A. & Freeman, W. J. (1987) How brains make chaos in order to make sense of the world. Behavioral and Brain Sciences 10:161–95. [WJF, IT]CrossRefGoogle Scholar
Sloman, S. A. (1993) Feature-based induction. Cognitive Psychology 25 (in press). [SS]CrossRefGoogle Scholar
Smolensky, P. (1988) On the proper treatment of connectionism. Behavioral and Brain Sciences 11:1–74. [GD, EK]CrossRefGoogle Scholar
Smolensky, P. (1990) Tensor product variable binding and the representation of symbolic structure in connectionist systems. Artificial Intelligence 46(1–2):159–216. [aLS, CSH]CrossRefGoogle Scholar
Squire, L. R. (1987) Memory and brain. Oxford University Press. [aLS]Google Scholar
Squire, L. R. & Zola-Morgan, S. (1991) The medial temporal lobe memory system. Science 253:1380–86. [aLS]CrossRefGoogle ScholarPubMed
Stenning, K., Shepard, M. & Levy, J. (1988) On the construction of representations for individuals from descriptions in text. Language and Cognitive Processes 3(2): 129–64. [aLS]CrossRefGoogle Scholar
Stevens, C. F. (1989) How cortical interconnectedness varies with network size. Neural Computation 1:473–79. [JD]CrossRefGoogle Scholar
Stolcke, A. K. & Wu, D. (1992) Tree matching with recursive distributed representations. AAAI-92 Workshop on Integrating Neural and Symbolic Processes, San Jose, CA. (Also available as Technical Report 92–025, International Computer Science Institute, Berkeley.) [GH]Google Scholar
Strehler, B. L. & Lestienne, R. (1986) Evidence on precise time-coded symbols and memory of patterns in monkey cortical neuronal spike trains. Proceedings of the National Academy of Science 83:9812–16. [aLS]CrossRefGoogle ScholarPubMed
Strong, G. W. & Whitehead, B. A. (1989) A solution to the tag-assignment problem for neural nets. Behavioral and Brain Sciences 12:381–433. [aLS, GWS]CrossRefGoogle Scholar
Sumida, R. A. & Dyer, M. G. (1989) Storing and generalizing multiple instances while maintaining knowledge-level parallelism. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Morgan Kaufmann. [aLS]Google Scholar
Thorpe, S. J., Celebrini, S., Trotter, Y. & Imbert, M. (1991) Dynamics of stereo processing in area VI of the awake primate. European Journal of Neuroscience (Suppl.)4:83. [SJT]Google Scholar
Thorpe, S. J., Celebrini, S., Trotter, Y., Pouget, A. & Imbert, M. (1989) Dynamic aspects of orientation coding in area VI of the awake primate. European Journal of Neuroscience (Suppl.) 2:322. [SJT]Google Scholar
Thorpe, S. J. & Imbert, M. (1989) Biological constraints on connectionist models. In: Connectionism in perspective, ed. Pfeiffer, R., Schreter, Z., Fogelman-Souile, F. & Steels, L.. Elsevier. [arLS, SJT]Google Scholar
Tomabechi, H. & Kitano, H. (1989) Beyond PDF: The frequency modulation neural network approach. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Morgan Kaufmann. [aLS]Google Scholar
Touretzky, D. S. (1986) The mathematics of inheritance systems. Morgan Kaufmann/Pitman. [aLS]Google Scholar
Touretzky, D. S. (1990) BoltzCONS: Dynamic symbol structures in a connectionist network. Artificial Intelligence 46:1–2, 5–46. [rLS, JAB]CrossRefGoogle Scholar
Touretzky, D. S. & Hinton, G. E. (1988) A distributed connectionist production system. Cognitive Science 12(3):423–66. [aLS, GWC]CrossRefGoogle Scholar
Tovee, M. J. & Rolls, E. T. (1992) Oscillatory activity is not evident in the primate temporal visual cortex with static stimuli. Neuroreport 3:369–71. [aLS, SJT, MPY]CrossRefGoogle Scholar
Toyama, K., Kimura, M. & Tanaka, T. (1981) Cross correlation analysis of interneuronal connectivity in cat visual cortex. Journal of Neurophysiology 46(2):191–201. [aLS]CrossRefGoogle ScholarPubMed
Treisman, A. & Gelade, G. (1980) A feature integration theory of attention. Cognitive Psychology 12:97–136. [aLS]CrossRefGoogle ScholarPubMed
Tsuda, I. (1991) Chaotic itinerancy as a dynamical basis of hermeneutics in brain and mind. World Futures 32:167–84. [WJF, IT]CrossRefGoogle Scholar
Tsuda, I. (1992) Dynamic link of memory-chaotic memory map in nonequilibrium neural networks. Neural Networks 5:313–26. [IT]Google Scholar
Tulving, E. (1983) Elements of episodic memory. Oxford University Press. [aLS]Google Scholar
Tversky, A. & Kahneman, D. (1983) Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review 90:293–315. [SS]CrossRefGoogle Scholar
Ullman, J. D. & van Gelder, A. (1988) Parallel complexity of logical query programs. Algorithmica 3:5–42. [aLS]CrossRefGoogle Scholar
Valiant, L. G. (1988) Functionality in neural nets. Proceedings of the National Conference on Artificial Intelligence, Saint Paul, MN. [GWC]Google Scholar
van Gelder, T. (1990) Compositionality: A connectionist variation on a classical theme. Cognitive Science 14:208–12. [GD]Google Scholar
van Gelder, T. (1991) Classical questions, radical answers: Connectionism and the structure of mental representations. In: Connectionism and the philosophy of mind, ed. Horgan, T. & Tienson, J.. Kluwer. [JWG]Google Scholar
Velmans, M. (1991) Is human information processing conscious? [and Commentary thereon]. Behavioral and Brain Sciences 14(4):651–726. [GH]CrossRefGoogle Scholar
Vogels, R. & Orban, G. A. (1991) Quantitative study of striate single unit responses in monkeys performing an orientation discrimination task. Experimental Brain Research 84:1–11. [SJT]Google ScholarPubMed
von der Malsburg, C. (1981) The correlation theory of brain function. Internal Report 81–2. Department of Neurobiology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany. [aLS, WJF]Google Scholar
von der Malsburg, C. (1986) Am I thinking assemblies? In: Brain theory, ed. Palm, G. & Aertsen, A.. Springer. [aLS, GP]Google Scholar
von der Malsburg, C. & Schneider, W. (1986) A neural cocktail-party processor. Biological Cybernetics 54:29–40. [aLS, WJF, EK, IT]CrossRefGoogle ScholarPubMed
Wason, P. C. (1960) On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology 12:129–40. [SS]CrossRefGoogle Scholar
Wason, P. C. (1966) Reasoning. In: New horizons in psychology, ed. Foss, B.. Penguin. [MO]Google Scholar
Whitney, P. & Williams-Whitney, D. (1990) Toward a contextualist view of elaborative inferences. In: The psychology of learning and motivation, vol. 25, ed. Graesser, A. C. & Bower, G. H.. Academic Press. [GH]Google Scholar
Wickelgren, W. A. (1979) Chunking and consolidation: A theoretical synthesis of semantic networks, configuring in conditioning, S-R versus cognitive learning, normal forgetting, the amnesic syndrome, and the hippocampal arousal system. Psychological Review 86(1):44–60. [aLS]Google ScholarPubMed
Wilensky, R. (1983) Planning and understanding: A computational approach to human reasoning. Addison-Wesley. [aLS]Google Scholar
Wu, D. (1989) A probabilistic approach to marker propagation. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Morgan Kaufmann. [GH]Google Scholar
Wu, D. (1992a) Automatic inference: A probabilistic basis for natural language interpretation. Ph.D. dissertation (Technical Report UCB/CSD 92/692), Division of Computer Science, University of California at Berkeley. [GH]Google Scholar
Wu, D. (1992b) Approximate maximum-entropy integration of syntactic and semantic constraints. AAAI-92 Workshop on Statistically-Based NLP Techniques, San Jose, CA. [GH]Google Scholar
Yao, Y., Freeman, W. J., Burke, B. & Yang, Q. (1991) Pattern recognition by a distributed neural network: An industrial application. Neural Networks 4:103–12. [WJF]CrossRefGoogle Scholar
Young, M. P., Tanaka, K. & Yamane, S. (1991) On oscillating neuronal responses in monkey visual cortex. Society for Neuroscience Abstracts 17(1):73.9. [MPY]Google Scholar