Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-11T04:02:53.809Z Has data issue: false hasContentIssue false

Language enabled by Baldwinian evolution of memory capacity

Published online by Cambridge University Press:  01 October 2008

Thomas K. Landauer
Affiliation:
Department of Psychology, University of Colorado at Boulder and Pearson Knowledge Technologies, Boulder, CO 80301. Landauer@PearsonKT.com

Abstract

The claim that language is shaped by the brain is weakened by lack of clear specification of what necessary and sufficient properties the brain actually imposes. To account for human intellectual superiority, it is proposed that language did require special brain evolution (Deacon 1997), but that what evolved was a merely quantitative change – in representation space – rather than a radically new invention.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Deacon, T. W. (1997) The symbolic species: The co-evolution of language and the brain. W. W. Norton/Penguin.Google Scholar
Jones, M. N. & Mewhort, D. J. K. (2007) Representing word meaning and order information in a composite holographic lexicon. Psychological Review 114:137.CrossRefGoogle Scholar
Landauer, T. K. (1975) How much do people remember? Some estimates of the amount of learned information in long-term memory. Cognitive Science 10:477–93.Google Scholar
Landauer, T. K. (2002) On the computational basis of learning and cognition: Arguments from LSA. In: The psychology of learning and motivation, ed. Ross, B. H., pp. 4384. Academic Press.Google Scholar
Landauer, T. K. & Dumais, S. T. (1997) A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review 104:211–40.CrossRefGoogle Scholar
Landauer, T. K., McNamara, D. S., Dennis, S. & Kintsch, W., eds. (2007) Handbook of Latent Semantic Analysis. Erlbaum.CrossRefGoogle Scholar
Steyvers, M. & Griffiths, T. (2007) Probabilistic Topic models. In: Handbook of Latent Semantic Analysis, ed. Landauer, T. K., McNamara, S., Dennis, S. & Kintsch, W., pp. 427–48. Erlbaum.Google Scholar