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Concepts and their mental associations influence how language is processedand used. Networks represent powerful models for exploring such cognitivesystem, known as mental lexicon. This study investigates lexicon robustness toprogressive word failure with multiplex network attacks. The average lexicon ofan adult English speaker is built by considering 16000 words connected throughsemantic free associations and phonological sound similarities. Progressivestructural degradation is modelled as random and targeted attacks. Words withhigher psycholinguistic features (e.g. frequency, length, age of acquisition,polysemy) or network centrality (e.g. closeness, PageRank, betweenness anddegree) are targeted first. Aphasia-inspired attacks are introduced here andtarget first words named correctly, more or less frequently, by patients withanomic aphasia, a pathology disrupting word finding. Robustness is measured asconnectedness, fundamental for activation spreading and lexical retrieval, andviability, a multi-layer connectivity identifying language kernels. The lexiconis resilient to random, aphasia-inspired and psycholinguistic attacks.Catastrophic phase transitions happen when phonological and semantic degreesare combined, making the lexicon fragile to multidegree attacks. The viablekernel is fragile to multi-PageRank and to aphasia-inspired attacks.Consequently, connectedness in the lexicon is mediated by hubs, whereasviability enables a lexical semantic/phonological interplay and corresponds toa facilitative naming effect in aphasia. These effects persist also throughageing, in different network representations of younger and older lexicons.This study indicates the need to prevent failure of high multidegree and viablewords in the mental lexicon when pursuing the design of effective languagerestoration strategies against cognitive impairing.

Multiplex networks quantify robustness of the mental lexicon to catastrophic concept failures, aphasic degradation and ageing