Standardized tests exist for the diagnostics of developmental lexical disorders, but it is still difficult to associate the resulting behavior of a child while speaking with functional deficits in the child´s brain. The mental lexicon is part of the speech and language knowledge repository of individuals. It enables humans to produce as well as to understand speech. The computational frameworks we used for implementing a model of the mental lexicon and speech processing are the NEF (Neural Engineering Framework, Eliasmith et al. 2012, Eliasmith 2013) and the SPA (Semantic Pointer Architecture, Eliasmith et al 2012, Stewart & Eliasmith 2014). These frameworks allow modeling of large scale neural networks, comprising sensory, motor and cognitive components. The modeled task is the WWT 6-10 (Word range and Word Retrieval Test, see Glück 2011), which comprises 95 items and is a picture naming and word comprehension task. In case of incorrect answers semantic and phonological cues are also given in order to facilitate word production. A major goal of this study is to introduce a quantitative neurocomputational model for lexical storage as well as for lexical retrieval. A further goal of this study is to associate neural dysfunctions with deficits in speech behavior. Concretely, the deficits of interest are in lexical storage and lexical access. The dysfunctions introduced here are the lesioning of specific neural SPA-buffers and of specific neural connections between these buffers. Based on the behavioral data given by the WWT, we are now able to associate functional neural deficits with symptomatic behavioral data. This allows us to identify potential dysfunctions at neural level for word retrieval and word storage.