Skip to main content Accessibility help

Semantic cognition or data mining?

  • Denny Borsboom (a1) and Ingmar Visser (a1)


We argue that neural networks for semantic cognition, as proposed by Rogers & McClelland (R&M), do not acquire semantics and therefore cannot be the basis for a theory of semantic cognition. The reason is that the neural networks simply perform statistical categorization procedures, and these do not require any semantics for their successful operation. We conclude that this has severe consequences for the semantic cognition views of R&M.



Hide All
Brentano, F. C. (1874/1995) Psychology from an empirical standpoint. Routledge.
Collins, A. M. & Quillian, M. R. (1969) Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behavior 8:240–47.
Hadley, R. F. (2000) Cognition and the computational power of connectionist networks. Connection Science 12:95110.
Ripley, B. D. (1996) Pattern recognition and neural networks. Cambridge University Press.
Rogers, T. T. & McClelland, J. L. (2004) Semantic cognition: A parallel distributed processing approach. MIT Press.
Sarle, W. S. (1994) Neural networks and statistical models. In: Proceedings of the Nineteenth Annual SAS Users Group International Conference. pp. 1538–50. SAS Institute.
Schmittmann, V. D., Visser, I. & Raijmakers, M. E. J. (2006) Multiple learning modes in the development of rule-based category-learning task performance. Neuropsychologia 44:2079–91.


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed