A psycholinguistic model of natural language parsing implemented in simulated neurons

Article

Huyck, C. 2009. A psycholinguistic model of natural language parsing implemented in simulated neurons. Cognitive Neurodynamics. 3 (4), pp. 316-330. https://doi.org/10.1007/s11571-009-9080-6
TypeArticle
TitleA psycholinguistic model of natural language parsing implemented in simulated neurons
AuthorsHuyck, C.
Abstract

A natural language parser implemented entirely in simulated neurons is described. It produces a semantic representation based on frames. It parses solely using simulated fatiguing Leaky Integrate and Fire neurons, that are a relatively accurate biological model that is simulated efficiently. The model works on discrete cycles that simulate 10 ms. of biological time, so the parser has a simple mapping to psychological parsing time. Comparisons to human parsing studies show that the parser closely approximates this data. The parser makes use of Cell Assemblies and the semantics of lexical items is represented by overlapping hierarchical Cell Assemblies so that semantically related items share neurons. This semantic encoding is used to resolve prepositional phrase attachment ambiguities encountered during parsing. Consequently, the parser provides a neurally-based cognitive model of parsing.

Research GroupArtificial Intelligence group
PublisherSpringer
JournalCognitive Neurodynamics
ISSN1871-4080
Electronic1871-4099
Publication dates
Online20 Mar 2009
Print31 Dec 2009
Publication process dates
Deposited02 Mar 2010
Submitted26 Jan 2009
Accepted26 Feb 2009
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/s11571-009-9080-6
LanguageEnglish
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