Abstract

BackgroundTo produce and understand words, humans access the mental lexicon. From a functional perspective, the long-term memory component of the mental lexicon is comprised of three levels: the concept level, the lemma level, and the phonological level. At each level, different kinds of word information are stored. Semantic as well as phonological cues can help to facilitate word access during a naming task, especially when neural dysfunctions are present. The processing corresponding to word access occurs in specific parts of working memory. Neural models for simulating speech processing help to uncover the complex relationships that exist between neural dysfunctions and corresponding behavioral patterns.MethodsThe Neural Engineering Framework (NEF) and the Semantic Pointer Architecture (SPA) are used to develop a quantitative neural model of the mental lexicon and its access during speech processing. By simulating a picture-naming task (WWT 6-10), the influence of cues is investigated by introducing neural dysfunctions within the neural model at different levels of the mental lexicon.ResultsFirst, the neural model is able to simulate the test behavior for normal children that exhibit no lexical dysfunction. Second, the model shows worse results in test performance as larger degrees of dysfunction are introduced. Third, if the severity of dysfunction is not too high, phonological and semantic cues are observed to lead to an increase in the number of correctly named words. Phonological cues are observed to be more effective than semantic cues.ConclusionOur simulation results are in line with human experimental data. Specifically, phonological cues seem not only to activate phonologically similar items within the phonological level. Moreover, phonological cues support higher-level processing during access of the mental lexicon. Thus, the neural model introduced in this paper offers a promising approach to modeling the mental lexicon, and to incorporating the mental lexicon into a complex model of language processing.

Highlights

  • Normal and Disordered SpeechSpeech processing involves complex cognitive, motor, and sensory processes

  • The model is comprised of seven modules: (1) a visual perception pathway module, (2) an auditory perception pathway module, (3) an overall perception module, (4) a production and articulation pathway module, (5) a cognitive processing module, (6) a task control module and (7) a knowledge repository module consisting of the mental lexicon and mental syllabary (Figure 1)

  • The neural realization of the speech processing model is based on a model of spiking neurons incorporated into neuron ensembles, which are organized into neuron buffers

Read more

Summary

Introduction

Normal and Disordered SpeechSpeech processing involves complex cognitive, motor, and sensory processes. The cognitive system involved in speech processing includes pragmatic, semantic, syntactic and phonological components, and is linked with sensory and motor systems. Within this cognitive system, the mental lexicon serves as a basic knowledge repository for word forms and their meanings (long-term memory; Dell and O’Seaghdha, 1992; Levelt et al, 1999; Indefrey and Levelt, 2000; Elman, 2004). The concept network (in some models seen as a knowledge repository, located above the mental lexicon) stores and organizes the meanings of words. Neural models for simulating speech processing help to uncover the complex relationships that exist between neural dysfunctions and corresponding behavioral patterns

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.