|Networks: A network is a system of interconnected components that communicate with and influence each other. Networks can be found in both natural and artificial systems. E.g., the nervous system, or the internet. See also Neural networks, Artificial neural networks, Connectionism._____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. |
Ronald E. Smith on Networks - Dictionary of Arguments
Corr I 481
Networks/Shoda/Smith: One notable property of dynamic networks is the emergence of distinctive sets of activation patterns into which the network settles over time (Hopfield 1982)(1). Called attractor states, these stable patterns are analogous to the shapes that straw hats can snap into. These shapes represent ‘stable’ states because the hat takes on, and remains in, one of these shapes when it is let go after being distorted. Because component parts of the straw hat mutually support each other, the hat tends to remain in that shape (Shoda and Smith 2004)(2).
As originally proposed by Hebb (1949)(3), a basic neural network mechanism of learning is that the simultaneous activation of two units in a network strengthens the association between them. This principle has been used in a variety of neural network models, playing an important role in cognitive neuroscience (e.g., Rumelhart and McClelland 1986)(4).
Applied to the CAPS system (Cognitive-Affective Processing System, >Control processes/Shoda/Smith), it suggests that CAPS elements that become activated simultaneously may begin to form stronger associations with one other, eventually becoming a nodal cluster of mutually activating thoughts. Once any component of this cluster of thoughts becomes activated, it may in turn activate others in such a way that it becomes very difficult to break out of the cycle of mutual activation among the component cognitions that makeup the attractor state. In this manner, chronic accessibility of the network connections may increase over time.
1. Hopfield, J. J. 1982. Neural networks and physical systems with emergent collective computational abilities, Proceedings of the National Academy of Sciences 79:2554–8
2. Shoda, Y. and Smith, R. E. 2004. Conceptualizing personality as a cognitive-affective processing system: a framework for models of maladaptive behaviour patterns and change, Behaviour Therapy 35: 147–65
3. Hebb, D. O. 1949. The organization of behavior. New York: Wiley
4. Rumelhart, D.E. and McClelland, J.L. 1986.Parallel distributed processing: explorations in the microstructure of cognition, vols. I and II. Cambridge, MA: MIT Press
Ronald E. Smith and Yuichi Shoda, “Personality as a cognitive-affective processing system“, in: Corr, Ph. J. & Matthews, G. (eds.) 2009. The Cambridge Handbook of Personality Psychology. New York: Cambridge University Press_____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.
The Theory of Moral Sentiments London 2010
Vernon L. Smith
Rationality in Economics: Constructivist and Ecological Forms Cambridge 2009
Philip J. Corr
The Cambridge Handbook of Personality Psychology New York 2009
Philip J. Corr (Ed.)
Personality and Individual Differences - Revisiting the classical studies Singapore, Washington DC, Melbourne 2018