The Mental Lexicon: Conceptual and Empirical Aspects of a Powerful Metaphor

Dear Colleagues,

If concepts constitute the building blocks of thought, then words constitute those of language. Despite their number and variety, we process them rapidly and without conscious effort. Words support fundamental cognitive functions, including thought, communication, and memory. No doubt, words are important.

To be accessed and remembered, words must be represented, stored, and organized—a process that differs depending on the medium: paper, computer, or the brain. We will focus here on the mental lexicon (MLex), a term whose precise meaning remains elusive. Despite a substantial body of work on the subject, no consensus on its definition has emerged. Clarifying this elusive concept is therefore a primary goal of this Special Issue.

People typically produce two to three words per second (Levelt, 1989). Except in cases like aphasia or tip-of-the-tongue states, they retrieve the correct form with remarkably few errors, even from a vast stored repertoire (Brysbaert et al., 2016). This impressive efficiency has motivated decades of research, yet key questions remain unanswered, several of which are taken up in this issue.

Unlike a conventional dictionary, which stores shared knowledge, the mental lexicon is idiosyncratic. It is shaped by personal experience, evolves over a lifetime, and is not directly observable. While it is smaller than published lexical resources, it is not task-specific. It is equally well suited to reading, writing, and translation.

The representation, storage, and access of words depend on the medium—paper, computer, or the brain. Traditional dictionaries organize words alphabetically, thesauri by topic, and associative networks (e.g., WordNet) by semantic relations. Time-course models (Levelt et al., 1999), by contrast, describe word production as a synthetic process rather than word retrieval: words are decomposed into abstract semantic, grammatical, and phonological components, which are incrementally activated over time.

The first group treats words as holistic units, organized alphabetically, conceptually, or relationally. Time-course models, in contrast, decompose lexical entries into semantic, grammatical, and phonological representations, tracking their activation over time. For instance, the concept 'horse' activates the lemma ‘horse’ [N, SG], which then triggers the phonological form /hɔːrs/.

These perspectives are complementary: online models capture the millisecond dynamics of processing, while offline models offer a map of the stable structure of lexical networks. While most prior research has focused on isolated tasks (e.g., reading, translation) or on specific parts of the process, recent work has begun integrating these views within unified frameworks (e.g., Stella et al., 2024).

Given the promise of this integrative approach, this Special Issue aims to address the many remaining questions. We invite submissions on the mental lexicon that offer theoretical, methodological, or empirical contributions from linguistic, cognitive (psycholinguistic, neuroscientific), and AI perspectives. Topics of interest include, but are not limited to, the following:

1. How can we empirically substantiate the concept of the mental lexicon, given that it is an unobservable internal system?
2. Are the lexical networks we construct valid representations of the mental lexicon, or are they merely artifacts of our data-collection methods?
3. If speakers can readily access lexical neighbors for any given word, does this imply they possess an implicit mental representation of their own lexicon's structure?
4. How can we efficiently map individual lexicons, given that word meaning and organization are shaped by lived experience?
5. How can we explain the uniform retrieval speed of words, despite their diverse syntactic categories and widely varying semantic distances? Is this uniformity a byproduct of a 'small-world' network effect?
6. How does network topology affect lexical access? Specifically, do structural properties (e.g., clustering vs. sparsity) predict retrieval speed, and which network models best reflect actual cognitive processing in word recognition and production?
7. How can we support the oral acquisition of vocabulary in a foreign language—particularly in classroom settings—for instance, by leveraging elaborative encoding or mnemonic cues to strengthen form-meaning mapping?
8. What strategies can effectively help individuals overcome tip-of-the-tongue (TOT) states?
9. How does the mental lexicon change across the lifespan in both healthy aging and pathological conditions (e.g., Alzheimer's disease, aphasia), and how can these insights inform therapeutic interventions for language disorders?
10. How is the mental lexicon organized in bilingual or multilingual speakers, and how do multiple languages interact during lexical access?
11. Which aspects of the mental lexicon can be successfully modeled by large language models, and what can we learn about human lexical processing from them?
12. Can cognitive models of the mental lexicon inform the design of dictionaries and other lexical navigation tools?

While the literature on the topic is very large here are some pointers that you may find helpful:

• Mental lexicon: Aitchison, 2003; de Deyne et al., 2016; Papafragou et al. 2021 ; Zock 2015, 2023)
• Cognitive Aspects of the Lexicon (Cogalex), a workshop series at Coling since 2008, https://sites.google.com/view/cogalex-viii-2024/home/previous-events-pbs
• Neuroscience: Indefrey & Levelt, 2004; Huth, 2016
• Association networks: Schvaneveldt, 1989; Nelson et al. 1999 ; Meara, 2009.
• Lexical resources: Fellbaum, 1998, Navigli et al. 2021 ; Roget, 1852
• Word access in language production: Levelt, 1989; Levelt et al. 1999; Schiller & Verdonshot, 2014; Kerr et al. 2023
• The Tip of theTongue Problem: Brown, 2012; Lafourcade & Joubert, 2015; Cleary & Schwartz, 2025.
• Shared task to overcome the Tip of the Tongue Problem : Rapp & Zock, 2014, Arguello et al. 2026.
• Network science: Haim & Stella, 2026; Wilks & Meara, 2002; Baronchelli et al 2013; Siew et al., 2019.
• Large Language Models: de Schryver, 2023.

For more pointers see: http://pageperso.lif.univ-mrs.fr/~michael.zock/Docs/MZ_Refs_ML.pdf

Paper length: There is no strict length requirement. However, a minimum of 4,000 words for the main text is recommended.

Contributors: reviewers can also be the contributors to this Special Issue.

Fee: There is an article processing charge (1600 CHF). However, being aware of the problem this may pose for some authors, and, recognizing the fact that funding varies across institutions, the journal may offer discounts or even full waivers upon request. Please contact Aron Wang (aron.wang@mdpi.com) to discuss your specific case. If your institution can cover the fee, the journal would appreciate it—helping them reserve waivers for those without alternative funding.

Reviewer Voucher: Reviewers will get 50-100 CHF vouchers that can be used for the APC of their own submissions. And there is not a maximum limit for the use of vouchers.

Tentative Completion Schedule
Abstract Submission Deadline: 15 October 2026
Notification of Abstract Acceptance: 15 November 2026
Full Manuscript Deadline: 15 April 2027

References

Aitchison, J. (2003). Words in the Mind: an Introduction to the Mental Lexicon. Oxford: Blackwell.

Arguello, J., Diaz, F., Fröebe, M., Kim, T. E., & Mitra, B. (2026). Overview of the TREC 2025 Tip-of-the-Tongue track. arXiv preprint arXiv:2601.20671.

Baronchelli, A., Ferrer-i-Cancho, R., Pastor-Satorras, R., Chater, N., & Christiansen, M. H. (2013). Networks in cognitive science. Trends in Cognitive Sciences, 17, 348–360.

Brown, A. S. (2012). The tip of the tongue state. Taylor & Francis.

Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). How many words do we know? Practical estimates of vocabulary size dependent on word definition, the degree of language input and the participant’s age. Frontiers in psychology, 7, 1116.

Cleary, A. M., & Schwartz, B. L. (2025). Tip of the tongue states: Retrieval, metacognition, and experience. Cambridge University Press.

De Deyne, S., Verheyen, S. & Storms, G. (2016). Structure and organization of the mental lexicon: A network approach derived from syntactic dependency relations and word associations. In Mehler, A., et al. (Eds.). Towards a theoretical framework for analyzing complex linguistic networks (pp. 47–79). Berlin: Springer.

De Schryver, G. M. (2023). Generative AI and Lexicography: The Current State of the Art Using ChatGPT. International Journal of Lexicography, 36(4), 355-387.

De Schryver: https://sites.google.com/view/cogalex-viii-2024/home/invited-speaker

Fellbaum, C. (Ed.) (1998). WordNet: An electronic lexical database and some of its applications. Cambridge: MIT Press.

Haim, E., & Stella, M. (2026). Cognitive Networks for Knowledge Modeling: A Gentle Introduction for Data‐and Cognitive Scientists. Wiley Interdisciplinary Reviews: Cognitive Science, 17(2), e70026.

Indefrey, P. & Levelt, W. J. (2004). The spatial and temporal signatures of word production components. Cognition, 92(1-2), 101-144.

Huth A. G. De Heer W. A. Griffiths T. L. Theunissen F. E. & Gallant J. L. (2016). Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532(7600) 453-458.

Kerr, E., Ivanova, B. & Strijkers, K. (2023). Lexical access in speech production: Psycho-and neurolinguistic perspectives on the spatiotemporal dynamics. In Hartsuiker, R. J. & Strijkers, K. (Eds.). Language Production. Routledge.(pp. 32-65). Routledge.

Lafourcade, M., and Joubert, A. (2015). TOTAKI: A help for lexical access on the TOT Problem. In Gala, N., Rapp, R. et Bel-Enguix, G. (Eds). Language Production, Cognition, and the Lexicon. Festschrift in honor of Michael Zock. Dordrecht, Springer, pp. 95-112

Levelt, W. (1989)? Speaking: From intention to articulation. MIT press.

Levelt W., Roelofs A. & Meyer, A. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22, 1-75.

Meara, P. (2009). Connected words: Word associations and second language vocabulary acquisition. John Benjamins Publishing.

Miller, G., Fellbaum, C., Kegl, J. & Miller, K. (1988). WordNet: An Electronic Lexical Reference System Based on Theories of Lexical Memory. Revue québécoise de linguistique, vol. 17, n° 2, pp. 181-212.

Navigli, R., Bevilacqua, M., Conia, S., Montagnini, D., & Cecconi, F. (2021). Ten years of BabelNet: A survey. In IJCAI (International Joint Conferences on Artificial Intelligence Organization). 4559-4567. https://doi.org/10.24963/ijcai.2021/620

Nelson, D. L., McEvoy, C. L. & Schreiber, T. A. (1999). The University of South Florida Word Association, Rhyme and Fragment Norms. (http://w3.usf.edu/FreeAssociation/Intro.html)

Papafragou, A., Trueswell, J. C., & Gleitman, L. R. (Eds.). (2021). The Oxford handbook of the mental lexicon. Oxford University Press.

Rapp, R., & Zock, M. (2014, August). The CogALex-IV shared task on the lexical access problem. In Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex) (pp. 1-14). https://pageperso.lis-lab.fr/~michael.zock/ColingWorkshops/CogALex-4/cogalex-webpage/pst.html

Roget, P. (1852) Thesaurus of English Words and Phrases, Longman, London

Schiller, N. O., & Verdonschot, R. G. (2014). Accessing words from the mental lexicon. In, Taylor, J. (ed.) The Oxford Handbook of the word. Oxford University Press. pp. 161-190

Schvaneveldt, R. editor. (1989). Pathfinder Associative Networks: Studies in knowledge organization. Norwood. N.J.

Stella, M., Citraro, S., Rossetti, G., Marinazzo, D., Kenett, Y. N., & Vitevitch, M. S. (2024). Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges. Psychonomic Bulletin & Review, 31(5), 1981-2004.

Siew, C. S., Wulff, D. U., Beckage, N. M. & Kenett, Y. N. (2019). Cognitive Network Science: A review of research on cognition through the lens of network representations, processes, and dynamics.  (https://www.hindawi.com/journals/complexity/2019/2108423/)

Wilks, C. & Meara, P. (2002). Untangling word webs: Graph theory and the notion of density in second language word association networks. Second Language Research, 18(4), 303-324.

Zock, M. (2015). Words in Books, Computers, and the Human Mind. Introduction to 'Special Issue' of Journal of Cognitive Science. 16-4: 355-378, DOI : 10.17791/jcs.2015.16.4.355

Zock, M. (2023). The mental lexicon: A blueprint for the dictionaries of tomorrow? Frontiers, Artificial Intelligence, Volume 5. https://doi.org/10.3389/frai.2022.1027392, https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2022.1027392/full

Prof. Dr. Michael Zock
Prof. Dr. Massimo Stella
Dr. Nichol Castro
Guest Editors

Edith Haim e-mail 
Guest Editor Assistant
Affiliations: 1. Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
                   2. CogNosco Lab, Trento, Italy
Interests: cognitive network science; mental lexicon; multilayer lexical networks; scientific creativity

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• mental lexicon
• lexical representation
• lexical access
• lexical networks
• psycholinguistics