Summary
The Structural Memory, a network model for human perception of serial objects, such as series, is presented. Our theoretical assumptions originate from the Structural Information (Theory (SIT) (Buffart & Leeuwenberg, 1983; Leeuwenberg, 1969), a theory concerning the perceptible structures in an object and the human preference for one of these structures. A symbolic notation of such a perceptible structure in an object is called a representation. For a given maximum number of symbols we can generate all representations automatically. From this procedure we define G(eneration)-relations between the representations. We also define S(tructure)-relations based upon the structures described by the representations. The representations and relations can be seen as respectively the nodes and links in a network. This network is the basis for the Structural Memory. We therefore assign an activation value to each representation in the network, expressing the strength of the preference for the described structure at a certain moment. By means of a process model we are able to make predictions for the strength of the preference for a perceptible structure in an object. The process is only based upon the network structure, because of a relation found between the preference measure, used in SIT, for a perceptible structure in an object and the number of G- and S-relations of the corresponding representation in the network. It is shown that with two of these process models some experiments by Van Leeuwen and Buffart can be simulated.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anderson, J. A., Silverstein, J. W., Ritz, S. A., & Jones, R. S. (1977). Distinctive features, categorical perception and probability learning: Some applications of a neural model. Psychological Review, 84, 413–451.
Buffart, H. (1986). Gestalt qualities, memory structure and minimum principles. In F. Klix, & H. Hagendorf (Eds.), Human memory and cognitive capabilities. Amsterdam, NL: North-Holland.
Buffart, H. (1987). Seven minus two and structural operations. In E. Roskam, & J. Suck (Eds.), Progress in mathematical psychology, I. Amsterdam, NL: North-Holland.
Buffart, H., & Leeuwenberg, E. (1983). Structural Information Theory. In H.-G. Geissler, H. F. J. M. Buffart, E. L. J. Leeuwenberg, & V. Sarris (Eds.), Modern issues in perception. Amsterdam, NL: North-Holland.
Geissler, H.-G., & Puffe, M. (1983). The inferential basis of classification: from perceptual to memory code systems. In H.-G. Geissler, H. F. J. M. Buffart, E. L. J. Leeuwenberg, & V. Sarris (Eds.), Modern issues in perception. Amsterdam, NL: North-Holland.
Hatfield, G. C., & Epstein, W. (1985). The status of the minimum principle in the theoretical analysis of visual perception. Psychological Bulletin, 97, 155–186.
Kerlinger, F. N., & Pedhazur, E. J. (1973). Multiple regression in behavioral research. New York: Holt, Rinehart, & Winston.
Koffka, K. (1935). Principles of Gestalt psychology. London: Routledge, & Kegan Paul.
Kohonen, T., Oja, E., Lehtiö, P. (1981). Storage and processing of information in Distributed Associative Memory Systems. In G. E. Hinton, & J. A. Anderson (Eds.), Parallel models of associative memory. Hillsdale, NJ: Lawrence Erlbaum Associates.
Kohonen, T. (1984). Self-organization and associative memory. Berlin: Springer-Verlag.
Laird, J. E., Newell, A., & Rosenbloom, P. S. (1987). SOAR: An architecture for general intelligence. Artificial Intelligence, 33, 1–64.
Leeuwen, C. van (1989). PDP and Gestalt. An Integration? Psychological Research, 50 (this issue).
Leeuwen, C. van, & Buffart, H. (1989). Facilitation of retrieval by perceptual structure. Psychological Research, 50 (this issue).
Leeuwen, C. van, Buffart, H., & Vegt, J. van der (1988). Sequence Influence on the organization of meaningless serial stimuli: Economy after all. Journal of Experimental Psychology: Human Perception and Performance, 14, 481–502.
Leeuwenberg, E. (1969). Quantitative specification of information in sequential patterns. Psychological Review, 76, 216–220.
Marr, D. (1982). Vision. San Francisco: W. H. Freeman, & Company.
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review, 88, 375–407.
McClelland, J. L., & Rumelhart, D. E. (1985). Distributed memory and the representation of general and specific information. Journal of Experimental Psychology: General, 114, 159–188.
Mellink, H., & Buffart, H. (1987). Abstract code network as a model of perceptual memory. Pattern Recognition, 20, 143–151.
Ratcliff, R. (1987). A theory of memory retrieval. Psychological Review, 85, 59–108.
Restle, F. (1970). Theory of serial pattern learning: Structural trees. Psychological Review, 77, 481–495.
Roediger, H. L., & Neely, J. H. (1982). Retrieval blocks in episodic and semantic memory. Canadian Journal of Psychology, 36, 213–242.
Rumelhart, D. E., McClelland, J. L., & the PDP Research Group (1986). Parallel Distributed Processing: Explorations in the microstructure of cognition. Cambridge, Mass.: MIT Press.
Skarda, C. A., & Freeman, W. J. (1987). How brains make chaos in order to make sense of the world. Behavioral and Brain Sciences, 10, 161–195.
Winograd, T. (1972). Understanding natural language. New York: Academic Press.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
van der Vegt, J., Buffart, H. & van Leeuwen, C. The Structural Memory: A network model for human perception of serial objects. Psychol. Res 50, 211–222 (1989). https://doi.org/10.1007/BF00309255
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF00309255