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Chapter 14 - Learned Activation Patterns of Simple Connected Processing Units

Prediction Involves Connectionist Neural Networks

from Part III - Mathematical Theories

Published online by Cambridge University Press:  20 March 2025

Falk Huettig
Falk Huettig
Affiliation:
Max-Planck-Institut für Psycholinguistik, The Netherlands
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Summary

Connectionist networks consisting of large numbers of simple connected processing units implicitly or explicitly model aspects of human predictive behavior. Prediction in connectionist models can occur in different ways and with quite different connectionist architectures. Connectionist neural networks offer a useful playground and ‘hands-on way’ to explore prediction and to figure out what may be special about how the human mind predicts.

Keywords

connectionismpredictionstatistical learninglarge language modelsSRNTraceElmanbackpropagationdeep learning
Type
Chapter
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Looking Ahead
The New Science of the Predictive Mind
 , pp. 146 - 162
Publisher: Cambridge University Press
Print publication year: 2025

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References

Further Reading

Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14(2), 179–211.CrossRefGoogle Scholar
Fodor, J. A., & Pylyshyn, Z. W. (1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28(1–2), 3–71.CrossRefGoogle ScholarPubMed
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.CrossRefGoogle ScholarPubMed

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