Articles on WEAVER++ simulations

Articles on WEAVER++ simulations

Historical note: The first brief report on the model was in the Annual Report 1990 of the Max Planck Institute for Psycholinguistics, Nijmegen (pp. 4-6). Link

The articles listed below concern computer simulations. For other publications, click here

Highlights of what has been achieved

WEAVER++ is a psycholinguistic, computational, and neurocognitive model. The term psycholinguistic indicates that the model is designed to contribute to our knowledge of how language is cognitively represented and processed. The term computational indicates that the model is specified as a computer algorithm that makes mental representations and operations explicit, and that it is tested in computer simulations. The model was originally developed in the early 1990s to explain the time course of language processes in healthy speakers, and (since 2002) the relationship between cognitive processes and their neural basis, referred to by the term neurocognitive. Later (since 2014), the model was also applied to language problems following a stroke or caused by a neurodegenerative disease. WEAVER++/ARC is the neurocognitive version of the model that is "virtually damaged" to account for impairments.

Over the years, I have noticed that many researchers have little appreciation for computational models and believe that verbally described models are just as good. Worse still, research has shown that researchers spend most of their time collecting data at the expense of developing theories. This leads to more data without more insight. Moreover, when theories are developed, they are usually not formalized, making it difficult to test them rigorously, thereby violating a fundamental rule of good science. This situation can be remedied by constructing a computational model for the theory, deriving predictions via computer simulations, and assessing whether these correspond with empirical data. This was done using WEAVER++ and WEAVER++/ARC within the psycholinguistic neurocognitive domain to test theoretical ideas about word processes. Ideally, modeling is cumulative, just like good empirical research (e.g., Roelofs, 2005). A number of highlights of what has been achieved with cumulative modeling using WEAVER++ and WEAVER++/ARC are described below. This is followed by references to articles, grouped by subject.

Mental chronometry: WEAVER++ is among the first psycholinguistic computational models to successfully simulate chronometric findings, and is the first model to do so for the production of spoken words (Roelofs, 1992, 1997, Cognition). Before that time, computational psycholinguistics focused primarily on the probabilities of choice regarding words, letters, and sounds in reading and listening (e.g., the Interactive Activation model by McClelland and Rumelhart, 1981, and the TRACE model by McClelland and Elman, 1986) or speech errors in word production (e.g., Dell, 1986). WEAVER++ shifted the focus to the time domain by successfully predicting millisecond-level chronometric findings on word production in experimental paradigms such as picture-word interference, the color-word Stroop task, and implicit priming. The model also successfully simulated the duration of eye movements during dual-task performance (Roelofs, 2008, JEP:HPP).

Attentional control: WEAVER++ is the first psycholinguistic computational model that successfully simulated chronometric findings regarding the attentional control of language processes, particularly processes in planning the production of spoken words in Stroop-like tasks (Roelofs, 2003, PR). Attentional control mechanisms are (still) lacking in other implemented psycholinguistic models. These models can perform two or more tasks, such as word production, comprehension, repetition, reading for comprehension, or reading aloud. However, there are no attentional control mechanisms present in the models that enable selective processing for one task or the other, or that resolve interference when multiple stimuli are present, such as hearing or seeing a word while naming an object. To give an example of an equivalent of Stroop-like situations in real life: If someone is asked something, why is the question not repeated instead of giving the answer?

Multiple languages: WEAVER++ is the first psycholinguistic computational model that successfully simulated chronometric data on word-form encoding in multiple languages, including Dutch, English, Japanese, and Mandarin Chinese (Roelofs, 2015, JPR). These languages differ significantly in their sound structure, but the model shows that similar encoding mechanisms for the languages explain the performance. WEAVER++ was also the first model to successfully simulate chronometric findings regarding bilingual word production (Roelofs & Verhoef, 2006).

Functional neuroimaging: WEAVER++ is the first psycholinguistic computational neurocognitive model that successfully simulated functional neuroimaging data, specifically the BOLD (Blood-Oxygenation-Level-Dependent) response in the anterior cingulate cortex during word production in the color-word Stroop task (Roelofs & Hagoort, 2002). The model demonstrated that the hemodynamic response of the brain could be directly predicted by the duration of mental processes. Later, the model was also successfully applied to event-related brain potential (ERP) data (Roelofs et al., 2016) and magnetoencephalography (MEG) data (Piai et al., 2014).

Tractography: WEAVER++/ARC is the first psycholinguistic computational neurocognitive model that successfully simulated the relationship between white matter integrity, measured by tractography, and language processes, in particular data on the integrity of the arcuate fasciculus after a stroke and the accuracy of word production and repetition (Roelofs, 2014; 2024, BS&F).

Primary progressive aphasia: WEAVER++/ARC is the first psycholinguistic computational neurocognitive model that successfully simulated the accuracy of word production, comprehension, and repetition in all three variants of primary progressive aphasia (PPA), at both the group and individual patient levels (Roelofs, 2022, B&L), and how performance accuracy correlates with the degree of atrophy of the cortical gray matter (Roelofs, 2023, Cortex) and white matter fiber tracts (Janssen et al., 2020). Previous models (e.g., Lichtheim 2 by Ueno et al., 2011) explained only one variant (namely semantic dementia) and offered no quantitative explanation. WEAVER++/ARC was also the first to successfully simulate performance in Alzheimer's dementia, mild cognitive impairment, and the behavioral variant of frontotemporal dementia (Roelofs, 2023, B&L; 2023, Cortex).

Clinical relevance: WEAVER++ and WEAVER++/ARC have direct clinical relevance. The models simulate performance on tasks used in clinical practice, such as the Stroop task, tasks from the Boston Diagnostic Aphasia Examination (BDAE), and tasks from the Sydney Language Battery (SYDBAT) for screening for primary progressive aphasia, thereby providing insight into patients' language performance. WEAVER++ has also successfully simulated language recovery after a stroke following language therapy (Roelofs, 2021).

New empirical discoveries: Over the years, new predictions of the model have been confirmed in empirical studies, leading to new discoveries. These include chronometric evidence for lexical selection by competition (Roelofs, 1992) and for morphological encoding in planning the production of spoken words (Roelofs, 1996); neuroimaging evidence for attentional control from the anterior cingulate cortex (rather than conflict monitoring, which was the prevailing view), see Roelofs et al. (2006); and combined tractography-chronometric evidence that different subtracts of the arcuate fasciculus underlie repetition and conceptually driven word production (Janssen et al., 2023).

History: Chapter 5 of The Discovery of Mind: From Wundt to Neuroimaging (Roelofs, 2024) discusses WEAVER++ and WEAVER++/ARC in light of developments in psychology and cognitive neuroscience over the past two centuries, and Roelofs (2024, BS&F) and Roelofs (2025) specifically discuss developments in psycholinguistic and neurocognitive modeling, since Wernicke and Wundt. WEAVER++ has also been applied to Donders' classical chronometric data from 1868 (Roelofs, 2018, Acta). Roelofs (2021, JEP:G) compares WEAVER++ with the Wundt 2.0 model, in which Wundt's groundbreaking ideas from 1902 have been implemented.

Janssen, N., Kessels, R. P. C., Mars, R. B., Llera, A., Beckmann, C. F., & Roelofs, A. (2023). Dissociating the functional roles of arcuate fasciculus subtracts in speech production. Cerebral Cortex, 33, 2539–2547.Article (PDF 941K)

Roelofs, A. (2005). From Popper to Lakatos: A case for cumulative computational modeling. In A. Cutler (Ed.), Twenty-first century psycholinguistics: Four cornerstones (pp. 313-330). Hillsdale, NJ: LEA. Article (PDF 175K)

Roelofs, A. (2024). The discovery of mind: From Wundt to neuroimaging. Radboud University Press. Webpage

Roelofs, A. (2024). Wernicke’s functional neuroanatomy model of language turns 150: What became of its psychological reflex arcs? Brain Structure and Function, 229(9), 2079-2096. Article (PDF 1854K)

Roelofs, A. (2025). On the revival of neurocognitive modeling: Testing old ideas with new techniques. Human Arenas, 8, 750-774. Article (PDF 3411K)

Topics:

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Attentional control

Roelofs, A. (2000). Control of language: A computational account of the Stroop asymmetry. In N. Taatgen & J. Aasman (Eds.), Proceedings of the Third International Conference on Cognitive Modeling (pp. 234-241). Veenendaal, The Netherlands: Universal Press.

Roelofs, A. (2000). Attention to action: Securing task-relevant control in spoken word production. In L. R. Gleitman & A. K. Joshi (Eds.), Proceedings of the 22nd Annual Conference of the Cognitive Science Society (pp. 411-416). Mahwah, NJ: Erlbaum. Article (PDF 65K)

Roelofs, A., & Hagoort, P. (2002). Control of language use: Cognitive modeling of the hemodynamics of Stroop task performance. Cognitive Brain Research, 15, 85-97. Article (PDF 438K)

Meyer, A. S., Roelofs, A., & Levelt, W. J. M. (2003). Word length effects in object naming: The role of a response criterion. Journal of Memory and Language, 48, 131-147. Article (PDF 193K)

Roelofs, A. (2003). Goal-referenced selection of verbal action: Modeling attentional control in the Stroop task. Psychological Review, 110, 88-125. Article (PDF 585K)

Roelofs, A. (2004). Error biases in spoken word planning and monitoring by aphasic and nonaphasic speakers: Comment on Rapp and Goldrick (2000). Psychological Review, 111, 561-572. Article (PDF 150K)

Roelofs, A., & Verhoef, K. (2006). Modeling the control of phonological encoding in bilingual speakers. Bilingualism: Language and Cognition, 9, 167-176. Article (PDF 108K)

Roelofs, A., Van Turennout, M., & Coles, M. G. H. (2006). Anterior cingulate cortex activity can be independent of response conflict in Stroop-like tasks. Proceedings of the National Academy of Sciences USA, 103, 13884-13889. Article (PDF 350K)

Roelofs, A. (2007). Attention and gaze control in picture naming, word reading, and word categorizing. Journal of Memory and Language, 57, 232-251. Article (PDF 311K)

Roelofs, A., & Lamers, M. (2007). Modelling the control of visual attention in Stroop-like tasks. In A. S. Meyer, L. R. Wheeldon, and A. Krott (Eds.), Automaticity and control in language processing (pp. 123-142). Hove, UK: Psychology Press. Article (PDF 232K)

Roelofs, A. (2008). Dynamics of the attentional control of word retrieval: Analyses of response time distributions. Journal of Experimental Psychology: General, 137, 303-323. Article (PDF 392K)

Roelofs, A. (2008). Tracing attention and the activation flow in spoken word planning using eye movements. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 353-368. Article (PDF 285K)

Roelofs, A. (2008). Attention to spoken word planning: Chronometric and neuroimaging evidence. Language and Linguistics Compass, 2, 389-405. Article (PDF 327K)

Roelofs, A. (2008). Attention, gaze shifting, and dual-task interference from phonological encoding in spoken word planning. Journal of Experimental Psychology: Human Perception and Performance, 34, 1580-1598. Article (PDF 377K)

Lamers, M., & Roelofs, A. (2011). Attentional control adjustments in Stroop and Eriksen task performance can be independent of response conflict. Quarterly Journal of Experimental Psychology, 64, 1056-1081. Article (PDF 441K)

Piai, V., Roelofs, A., & Schriefers, H. (2011). Semantic interference in immediate and delayed naming and reading: Attention and task decisions. Journal of Memory and Language, 64, 404-423. Article (PDF 519K)

Roelofs, A., Piai, V., & Schriefers, H. (2011). Selective attention and distractor frequency in naming performance: Comment on Dhooge and Hartsuiker (2010). Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1032-1038. Article (PDF 113K)

Roelofs, A., & Piai, V. (2011). Attention demands of spoken word planning: A review. Frontiers in Psychology, 2, Article 307. Article (PDF 976K)

Roelofs, A., Piai, V., & Schriefers, H. (2013). Context effects and selective attention in picture naming and word reading: Competition versus response exclusion. Language and Cognitive Processes, 28, 655-671. Article (PDF 173K)

Roelofs, A., & Piai, V. (2013). Associative facilitation in the Stroop task: Comment on Mahon et al. (2012). Cortex, 49, 1767-1769. Article (PDF 311K)

Roelofs, A. (2014). A dorsal-pathway account of aphasic language production: The WEAVER++/ARC model. Cortex, 59, 33-48. Article (PDF 1339K)

Roelofs, A., Piai, V., Garrido Rodriguez, G., & Chwilla, D. J. (2016). Electrophysiology of cross-language interference and facilitation in picture naming. Cortex, 76, 1-16. Article (PDF 1026K)

WEAVER++, 30 years and still going strong:

Janssen, N., Roelofs, A., Mangnus, M., Sierpowska, J., Kessels, R. P. C., & Piai, V. (2020). How the speed of word finding depends on ventral tract integrity in primary progressive aphasia. NeuroImage: Clinical, 28, Article 102450. Article (PDF 3049K)

Roelofs, A. (2021). Phonological cueing of word finding in aphasia: Insights from simulations of immediate and treatment effects. Aphasiology, 35, 169-185. Article (PDF 1451K)

San José, A., Roelofs, A., & Meyer, A. S. (2021). Modeling the distributional dynamics of attention and semantic interference in word production. Cognition. Article (PDF 4121K)

Roelofs, A. (2022). What semantic errors restricted to either speaking or writing in aphasia tell us about lemmas. Language, Cognition and Neuroscience. Article (PDF 1206K)

Lemma retrieval

Roelofs, A. (1992). A spreading-activation theory of lemma retrieval in speaking. Cognition, 42, 107-142. Article (PDF 4210K)

Roelofs, A. (1993). Testing a non-decompositional theory of lemma retrieval in speaking: Retrieval of verbs. Cognition, 47, 59-87. Article (PDF 4078K)

Roelofs, A. (1993). A spreading-activation theory of lemma retrieval in speaking. In W. J. M. Levelt (Ed.), Lexical access in speech production (pp. 107-142). Cambridge, MA: Blackwell (Reprinted from Cognition 1992, 42, 107-142).

Roelofs, A. (1996). Computational models of lemma retrieval. In T. Dijkstra, & K. De Smedt (Eds.), Computational psycholinguistics: AI and connectionist models of human language processing (pp. 308-327). London: Taylor & Francis. Article (PDF 1026K)

Roelofs, A., Meyer, A. S., & Levelt, W. J. M. (1996). Interaction between semantic and orthographic factors in conceptually driven naming: Comment on Starreveld and La Heij (1995). Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 246-251. Article (PDF 730K)

Roelofs, A. (1997). A case for nondecomposition in conceptually driven word retrieval. Journal of Psycholinguistic Research, 26, 33-67. Article (PDF 2403K)

Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22, 1-38. Article (PDF 693K)

Roelofs, A. (2001). Set size and repetition matter: Comment on Caramazza and Costa (2000). Cognition, 80, 283-290. Article (PDF 108K)

Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (2002). A theory of lexical access in speech production. In G. T. M. Altmann (Ed.), Psycholinguistics: Critical concepts in psychology (Vol. 5, pp. 278-377). London: Routledge (Reprinted from Behavioral and Brain Sciences 1999, 22, 1-38).

Roelofs, A. (2003). Goal-referenced selection of verbal action: Modeling attentional control in the Stroop task. Psychological Review, 110, 88-125. Article (PDF 585K)

Roelofs, A. (2006). Functional architecture of naming dice, digits, and number words. Language and Cognitive Processes, 21, 78-111. Article (PDF 176K)

Roelofs, A. (2006). Context effects of pictures and words in naming objects, reading words, and generating simple phrases. Quarterly Journal of Experimental Psychology, 59, 1764-1784. Article (PDF 172K)

Roelofs, A., Dijkstra, T., & Gerakaki, S. (2013). Modeling of word translation: Activation flow from concepts to lexical items. Bilingualism: Language and Cognition, 16, 343-353. Article (PDF 313K)

Roelofs, A. (2014). A dorsal-pathway account of aphasic language production: The WEAVER++/ARC model. Cortex, 59, 33-48. Article (PDF 1339K)

Roelofs, A., Piai, V., Garrido Rodriguez, G., & Chwilla, D. J. (2016). Electrophysiology of cross-language interference and facilitation in picture naming. Cortex, 76, 1-16. Article (PDF 1026K)

Roelofs, A. (2018). A unified computational account of cumulative semantic, semantic blocking, and semantic distractor effects in picture naming. Cognition, 172, 59-72. Article (PDF 574K)

San José, A., Roelofs, A., & Meyer, A. S. (2021). Modeling the distributional dynamics of attention and semantic interference in word production. Cognition. Article (PDF 4121K)

Roelofs, A. (2022). A neurocognitive computational account of word production, comprehension, and repetition in primary progressive aphasia. Brain and Language, 227, 105094. Article (PDF 2399K)

Roelofs, A. (2022). What semantic errors restricted to either speaking or writing in aphasia tell us about lemmas. Language, Cognition and Neuroscience. Article (PDF 1206K)

Word-form encoding

Roelofs, A. (1994). On-line versus off-line priming of word-form encoding in spoken word production. In A. Ram & K. Eiselt (Eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society (pp. 772-777). Hillsdale, NJ: LEA.

Roelofs, A. (1996). Morpheme frequency in speech production: Testing WEAVER. In G. E. Booij and J. van Marle (Eds.), Yearbook of Morphology 1996 (pp. 135-154). Dordrecht: Kluwer Academic Publishers. Article (PDF 1133K)

Roelofs, A. (1996). Serial order in planning the production of successive morphemes of a word. Journal of Memory and Language, 35, 854-876. Article (PDF 249K)

Roelofs, A. (1997). Syllabification in speech production: Evaluation of WEAVER. Language and Cognitive Processes, 12, 657-693. Article (PDF 348K)

Roelofs, A. (1997). The WEAVER model of word-form encoding in speech production. Cognition, 64, 249-284. Article (PDF 375K)

Roelofs, A. (1997). Syllabification in speech production: Evaluation of WEAVER. In G. T. M. Altmann (Ed), Cognitive models of speech processing: Psycholinguistic and computational perspectives on the lexicon (pp. 657-693). Hove, UK: Psychology Press (Reprinted from Language and Cognitive Processes 1997, 12, 657-693).

Roelofs, A. (1998). Rightward incrementality in encoding simple phrasal forms in speech production: Verb-particle combinations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 904-921. Article (PDF 1584K)

Roelofs, A., & Meyer, A. S. (1998). Metrical structure in planning the production of spoken words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 922-939. Article (PDF 1520K)

Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22, 1-38. Article (PDF 693K)

Roelofs, A. (2002). Spoken language planning and the initiation of articulation. Quarterly Journal of Experimental Psychology, Section A: Human Experimental Psychology, 55, 465-483. Article (PDF 217K)

Meyer, A. S., Roelofs, A., & Levelt, W. J. M. (2003). Word length effects in object naming: The role of a response criterion. Journal of Memory and Language, 48, 131-147. Article (PDF 193K)

Roelofs, A. (2003). Modeling the relation between the production and recognition of spoken word forms. In N. O. Schiller & A. S. Meyer (Eds.), Phonetics and phonology in language comprehension and production: Differences and similarities (pp. 115-158). Berlin: Mouton de Gruyter. Article (PDF 245K)

Roelofs, A., & Verhoef, K. (2006). Modeling the control of phonological encoding in bilingual speakers. Bilingualism: Language and Cognition, 9, 167-176. Article (PDF 108K)

Roelofs, A. (2014). A dorsal-pathway account of aphasic language production: The WEAVER++/ARC model. Cortex, 59, 33-48. Article (PDF 1339K)

Roelofs, A. (2015). Modeling of phonological encoding in spoken word production: From Germanic languages to Mandarin Chinese and Japanese. Japanese Psychological Research, 57, 22-37. Article (PDF 513K)

Roelofs, A. (2018). One hundred fifty years after Donders: Insights from unpublished data, a replication, and modeling of his reaction times. Acta Psychologica, 191, 228-233. Article (PDF 666K)

Roelofs, A. (2021). Phonological cueing of word finding in aphasia: Insights from simulations of immediate and treatment effects. Aphasiology, 35, 169-185. Article (PDF 1451K)

Roelofs, A. (2022). A neurocognitive computational account of word production, comprehension, and repetition in primary progressive aphasia. Brain and Language, 227, 105094. Article (PDF 2399K)

Roelofs, A. (2022). What semantic errors restricted to either speaking or writing in aphasia tell us about lemmas. Language, Cognition and Neuroscience. Article (PDF 1206K)

Impairments

Roelofs, A. (2003). Goal-referenced selection of verbal action: Modeling attentional control in the Stroop task. Psychological Review, 110, 88-125. Article (PDF 585K)

Roelofs, A. (2014). A dorsal-pathway account of aphasic language production: The WEAVER++/ARC model. Cortex, 59, 33-48. Article (PDF 1339K)

Roelofs, A. (2021). Phonological cueing of word finding in aphasia: Insights from simulations of immediate and treatment effects. Aphasiology, 35, 169-185. Article (PDF 1451K)

Roelofs, A. (2022). A neurocognitive computational account of word production, comprehension, and repetition in primary progressive aphasia. Brain and Language, 227, 105094. Article (PDF 2399K)

Roelofs, A. (2023). What semantic errors restricted to either speaking or writing in aphasia tell us about lemmas. Language, Cognition and Neuroscience, 38, 277-287. Article (PDF 1214K)

Roelofs, A. (2023). Accounting for word production, comprehension, and repetition in semantic dementia, Alzheimer’s dementia, and mild cognitive impairment. Brain and Language, 238, 105243. Article (PDF 2903K)

Roelofs, A. (2023). Word production and comprehension in frontotemporal degeneration: A neurocognitive computational Pickian account. Cortex, 163, 42-56. Article (PDF 1581K)

Other labs

(WEAVER++ simulations independently run by other people)

Breien, A. (2005). Determiner selection in speech production: Evidence from Norwegian. Master thesis, University of Bergen, Norway.

Müller, O. (2005). Priming access of grammatical gender in language comprehension. In O. Müller (Ed.), Retrieving semantic and syntactic properties: ERP studies on the time course in language comprehension (pp. 47-66). Doctoral dissertation, University of Nijmegen.

Protopapas, A., Archonti, A., & Skaloumbakas, C. (2007). Reading ability is negatively related to Stroop interference. Cognitive Psychology, 54, 251-282. doi:10.1016/j.cogpsych.2006.07.003

Availability

Most of the WEAVER++ and WEAVER++/ARC applications have been programmed in the C programming language using the Microsoft Visual C++ environment. These programs are available from Ardi Roelofs. Source files are also available from the Open Science Framework (OSF) at https://osf.io/ue4bn/. Applications in Python have been made by Aitor San José.