PureNet: A modeling program for neurocognitive linguistics

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dc.contributor.advisorLamb, Sydney M.en_US
dc.creatorHarrison, Colin Jamesen_US
dc.date.accessioned2009-06-04T08:44:54Zen_US
dc.date.available2009-06-04T08:44:54Zen_US
dc.date.issued2000en_US
dc.description.abstractNeurocognitive Linguistic Theory (NCL, Lamb 1999) stands alone as the only well-developed linguistic theory with a serious commitment to neurological plausibility. It is also set apart from much of mainstream Cognitive Science by its strictly non-symbolic approach to understanding cognition. The theory has enjoyed a long a fruitful development, but has been hampered by the difficulty of verifying complex network analyses presented entirely on paper. The need has been clear for some manner of independent testbed for the theory, and a computational context was the obvious choice. To meet this need, the PureNet modeling program has been constructed. Written in Java 1.1, the program has been designed to function in such a way as to match as closely as possible the essential elements of that which it seeks to model---the functional elements of NCL. The design and construction of the fundamental structures of the program are explicated. To demonstrate the utility of the program, three variant network analyses of portmanteau morphemes are proposed and modeled. As all three can be shown to function correctly, learnability is proposed as a discriminator. To reach the goal of a meaningful learnability test, a major learning hypotheses of NCL---the bi-directional learning hypothesis (Lamb, 1999, Ch.12)---is modeled and shown to be valid. Having demonstrated the validity of the NCL conception of bidirectional learning, a procedure for generalizing NCL networks into neutral structures for learnability tests is outlined, and then generalized network structures based upon the three portmanteau network models are constructed and run to see if they will self-organize into the target structures (the original network analyses). The methodology tentatively disfavors the lateral inhibition hypothesis for portmanteau morpheme structure as a learnable network system, and thus demonstrates the utility of PureNet as a valuable tool for future development of NCL.en_US
dc.format.extent279 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS LING. 2000 HARRISONen_US
dc.identifier.citationHarrison, Colin James. "PureNet: A modeling program for neurocognitive linguistics." (2000) Diss., Rice University. <a href="https://hdl.handle.net/1911/19501">https://hdl.handle.net/1911/19501</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/19501en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectLinguisticsen_US
dc.subjectCognitive psychologyen_US
dc.subjectComputer scienceen_US
dc.titlePureNet: A modeling program for neurocognitive linguisticsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentLinguisticsen_US
thesis.degree.disciplineSocial Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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