experimental and computational approaches to language and cognition
language and structured representations in minds, brains, and machines
Current Position
Lise Meitner Group Leader
Principal Investigator, Language and Computation in Neural Systems Group
Radboud University
Education and Experience
2019 - 2020 Max Planck Research Group Leader, Language and Computation in Neural Systems (LaCNS), MPI
2018 - 2019 Senior Investigator, Psychology of Language Department (PoL), MPI
2016 - 2017 Staff Scientist, PoL, MPI
2012 - 2017 Lecturer (US Assistant Professor) in Psychology,
School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Scotland, UK
2010 - 2012 Postdoctoral researcher
Basque Center on Cognition, Brain, and Language (BCBL), Donostia-San Sebastián, Spain
2006 M.A. General Psychology, NYU
1999-2000 Columbia University, New York, NY, USA.
Publications [.pdfs personal use only]
*indicates a lab-member-led paper
2023
*Slaats, S., Weissbart, H., Schoffelen, J. M., Meyer, A. S., & Martin, A. E. (2023). Delta-band neural responses to individual words are modulated by sentence processing. Accepted at Journal of Neuroscience.
Foraker, S., Cunnings, I., & Martin, A. E. (2023). Speed-accuracy tradeoff modeling and its interface with experimental syntax. In Sprouse, J. (Ed.). (2023). The Oxford handbook of experimental syntax. Oxford University Press. [psyarxiv]
*Zioga, I., Weissbart, H., Lewis, A. S., Haegens, S. & Martin, A. E. (2023). Naturalistic spoken language comprehension is supported by alpha and beta oscillations. Accepted at Journal of Neuroscience.
*Coopmans, C. W., Kaushik, K., & Martin, A. E. (2023). Hierarchical structure in language and action: A formal comparison. Accepted at Psychological Review. [preprint]
*Guest, O. & Martin, A. E. (2023). On logical inference over brain, behavior, and artificial neural networks. Computational Brain & Behavior. [.pdf]
2022
*ten Oever, S., Carta, S., Kaufeld, G., & Martin, A. E. (2022). Neural tracking of phrases in spoken language comprehension is automatic and task-dependent. eLife. [.pdf]
*ten Oever, S., Kaushik, K., & Martin, A. E. (2022). Inferring the nature of linguistic computations in the brain. PLoS Computational Biology. [.pdf]
*Bai, F. , Meyer, A. S., & Martin, A. E. (2022). Neural dynamics differentially encode phrases and sentences during spoken language comprehension. PLoS Biology. [.pdf]
*Coopmans, C. W., De Hoop, H., Hagoort, P., & Martin, A. E. (2022). Effects of structure and meaning on cortical tracking of linguistic units in naturalistic speech. Neurobiology of Language. [.pdf]
Doumas, L. A. A., Puebla, G., Martin, A. E., & Hummel, J. (2022). A theory of relation learning and cross-domain generalization. Psychological Review. [.pdf]
2021
*Coopmans, C. W., De Hoop, H., Kaushik, K., Hagoort, P., & Martin, A. E. (2021). Hierarchy in language interpretation: Evidence from behavioral experiments and computational modeling. Language, Cognition, and Neuroscience. [pubman]
*ten Oever, S. & Martin, A. E. (2021). An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions. eLife. [.pdf] preprint at [biorxiv]
*Puebla, G., Martin, A. E., Doumas, L. A. A. (2021). The relational processing limits of classic and contemporary neural network models of language processing. Language, Cognition, and Neuroscience. [arxiv] [.pdf]
Guest, O. & Martin, A. E. (2021). How computational modeling can force theory building in psychological science. Perspectives on Psychological Science. [.pdf]
Doumas, L. A. A., & Martin, A. E. (2021). A model for learning structured representations of similarity and relative magnitude from experience. Current Opinion in Behavioral Sciences. [.pdf]
2020
*Hashemzadeh, M., Kaufeld, G., White, M., Martin, A. E., & Fyshe, A. (2020). From Language to Language-ish: How Brain-Like is an LSTM’s Representation of Atypical Language Stimuli? In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings. [.pdf]
*Kaufeld, G., Bosker, H. R., Ten Oever, S., Alday, P. M., Meyer, A. S., & Martin, A. E. (2020) Linguistic structure and meaning organize neural oscillations into a content-specific hierarchy. Journal of Neuroscience. [.pdf]
Meyer, L., Sun, Y., & Martin, A. E. (2020). "Entraining" to speech, generating language? Language, Cognition, and Neuroscience. [.pdf]
Brennan, J. R. & Martin, A. E. (2020). Phase synchronization varies systematically with linguistic structure composition. Philosophical Transactions of the Royal Society B: Biological Sciences. [.pdf]
*Cutter, M. G., Martin, A. E., & Sturt, P. (2020). Readers detect an low-level phonological violation between two parafoveal words. Cognition. [.pdf]
*Cutter, M. G., Martin, A. E., & Sturt, P. (2020). The Activation of Contextually Predictable Words in Syntactically Illegal Positions. Quarterly Journal of Experimental Psychology. [.pdf]
Martin, A. E. (2020). A compositional neural architecture for language. Journal of Cognitive Neuroscience. [.pdf]
Martin, A. E. & Baggio, G. (2020). Modeling meaning composition from formalism to mechanism. Philosophical Transactions of the Royal Society B: Biological Sciences. [.pdf]
Martin, A. E. & Doumas, L. A. A. (2020). Tensors and compositionality in neural systems. Philosophical Transactions of the Royal Society B: Biological Sciences. [.pdf]
2019
*Kaufeld, G., Naumann, W., Meyer, A. S., Bosker, H. R., & Martin, A. E. (2019). Contextual speech rate influences morphosyntactic prediction and integration. Language, Cognition, and Neuroscience. [.pdf]
Meyer, L., Sun, Y., & Martin, A. E. (2019). Synchronous, but not Entrained: Exogenous and Endogenous Cortical Rhythms of Speech and Language Processing. Language, Cognition, and Neuroscience. [uncorrected proof] [link to OA .pdf]
*Cutter, M. G., Martin, A. E., & Sturt, P. (2019). Capitalization Interacts with Syntactic Complexity. Journal of Experimental Psychology: Learning, Memory, and Cognition. [.pdf]
*Kaufeld, G., Ravenschlag, A., Meyer, A. S., Martin, A. E., & Bosker, H. R. (2019). Knowledge-based and signal-based cues are weighted flexibly during spoken language comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition. [.pdf]
Martin, A. E. & Doumas, L. A. A. (2019). Predicate learning in neural systems: Using oscillations to discover latent structure. Current Opinion in Behavioral Sciences [.pdf]
2018
Martin, A. E. (2018). Cue integration during sentence comprehension: Electrophysiological evidence from ellipsis. PLoS ONE [ .pdf]
Doumas, L. A. A., & Martin, A. E. (2018). Learning structured representations from experience. Psychology of Learning and Motivation, 69, 165-203. [.pdf]
Lakens, D. et al. (Martin, A. E. is author no. 57) (2018). Justify your alpha: A Response to "Redefine Statistical Significance." Nature Human Behavior. [.pdf] pre-print on PsyArXiv [.pdf]
Martin, A. E., & McElree, B. (2018). Retrieval cues and syntactic ambiguity resolution: Speed-accuracy tradeoff evidence. Language, Cognition, and Neuroscience [.pdf]
2017
Doumas, L. A. A., Hamer, A., Puebla, G., & Martin, A. E. (2017). A theory of the detection and learning of stimulus similarity and magnitude. In Proceedings of the 39th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [.pdf]
*Ito, A., Martin, A. E., & Nieuwland, M. S. (2017). Why the A/AN prediction effect may be hard to replicate: A rebuttal to Delong, Urbach, & Kutas (2017). Language, Cognition, and Neuroscience, 32(8), 974-983. [.pdf]
Martin, A. E., Huettig, F., & Nieuwland, M. S. (2017). Can structural priming answer the important questions about language? Comment on target article "An experimental approach to linguistic representation" by Branigan & Pickering. Behavioral and Brain Sciences, 40: e304. [.pdf]
Martin, A. E., & Doumas, L. A. A. (2017). A mechanism for the cortical computation of hierarchical linguistic structure. PLoS Biology, 15(3), e2000663. [.pdf; simulations runnable at: OSF and github ]
Nieuwland, M. S., & Martin, A. E. (2017). Neural oscillations and a nascent cortico-hippocampal theory of reference. Journal of Cognitive Neuroscience, 29:5, 896-910. [.pdf]
*Ito, A., Martin, A. E., & Nieuwland, M. S. (2017). On predicting form and meaning in a second language. Journal of Experimental Psychology: Learning, Memory, Cognition, 43(4), 635-652. [.pdf]
2016
Doumas, L. A. A., & Martin, A. E. (2016). Abstraction in time: Finding hierarchical linguistic structure in a model of relational processing. In Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [.pdf]
*Ito, A., Martin, A. E., & Nieuwland, M. S. (2016). How robust are prediction effects in language comprehension? Failure to replicate article-elicited N400 effects. Language, Cognition, and Neuroscience. doi:10.1080/23273798.2016.1242761. [.pdf]
Martin, A. E.**, Monahan, P. J.**, & Samuel, A. G. (2016). Interplay between agreement prediction and phonetic overlap shapes sublexical identification. Language and Speech. doi:10.1177/0023830916650714. [.pdf ] **equal authorship contribution, alphabetical listing
Martin, A. E. (2016). Language processing as cue integration: Grounding the psychology of language in perception and neurophysiology. Frontiers in Psychology: Language Sciences, 7:120. doi:10.3389/fpsyg.2016.00120. [.pdf]
*Ito, A., Corley, M., Pickering, M., Martin, A. E., & Nieuwland, M. S. (2016). Predicting form and meaning: Evidence from brain potentials. Journal of Memory and Language, 86, 157-171. [.pdf]
2014
Martin, A. E., Nieuwland, M. S., & Carreiras, M. (2014). Agreement attraction during comprehension of grammatical sentences: ERP evidence from ellipsis. Brain and Language, 135, 42-51. [.pdf]
2013
Davidson, D. J., & Martin, A. E. (2013). Modelling accuracy as a function of response time with the generalized linear mixed effects model. Acta Psychologica, 44, 83-96. [.pdf]
Nieuwland, M. S., Martin, A. E., & Carreiras, M. (2013). Event-related brain potential evidence for animacy processing asymmetries during sentence comprehension. Brain and Language, 26, 151-158. [.pdf]
2012
Martin, A. E., Nieuwland, M. S., & Carreiras, M. (2012). Event-related brain potentials index cue-based retrieval interference during sentence comprehension. NeuroImage, 59, 1859-1869. [.pdf]
Nieuwland, M. S., & Martin, A. E. (2012). If the real-world were irrelevant, so to speak: The role of propositional truth-value in counterfactual sentence comprehension. Cognition, 122, 102-109. [.pdf]
Nieuwland, M. S., Martin, A. E., & Carreiras, M. (2012). Brain regions that process case: Evidence from Basque. Human Brain Mapping, 33, 2509-2520. [.pdf]
2011
Martin, A. E., & McElree, B. (2011). Direct-access retrieval during sentence comprehension: Evidence from Sluicing. Journal of Memory and Language, 64, 327-343. [.pdf]
2009
Martin, A. E., & McElree, B. (2009). Memory operations that support language comprehension: Evidence from verb-phrase ellipsis. Journal of Experimental Psychology: Learning, Memory, Cognition, 35, 1231-1239. [.pdf]
Pylkkänen, L., Martin, A. E., McElree, B., & Smart, A. (2009). The Anterior Midline Field: Coercion or Decision Making? Brain and Language, 108,184-190. [.pdf]
2008
Martin, A. E., & McElree, B. (2008). A content-addressable pointer mechanism underlies comprehension of verb-phrase ellipsis. Journal of Memory and Language, 58, 879-906. [.pdf]
Ashby, J., & Martin, A. E. (2008). Prosodic phonological representations in early visual word recognition. Journal of Experimental Psychology: Human Perception and Performance, 34, 224-236. [.pdf]
Preprints
*Slaats, S. & Martin, A. E. (2023). What's surprising about surprisal. [psyarxiv]
*Kaushik, K. R., & Martin, A. E. (2022). A mathematical neural process model of language comprehension, from syllable to sentence. [psyarvix]
Doumas, L. A. A., Puebla, G., & Martin, A. E. (2018). Human-like generalization in a machine through predicate learning. [arxiv]
Doumas, L. A. A., Puebla, G., & Martin, A. E. (2017). How we learn things we didn't know already: A theory of learning structured representations from experience. [biorxiv]
Grants
Lise Meitner Research Group "Language and Computation in Neural Systems" (Max Planck Society; 2021-2026)
Aspasia, Netherlands Organization for Scientific Research (2019).
Max Planck Independent Research Group "Language and Computation in Neural Systems" (Max Planck Society; 2020-2024).
VIDI Research Grant "The rhythms of computation: A combinatorial mechanism for language production and comprehension" Netherlands Organization for Scientific Research (NWO; 2019-2023).
Research Project Grant "Integration of Information in Reading," The Leverhulme Trust, UK. (2017-2019; Co-PI with Dr. Patrick Sturt).
Future Research Leaders Fellowship and Research Grant "Brain-to-brain coupling during dialogue: What sentence fragments can reveal about 'joint' mental representations," Economic and Social Research Council, UK. (2013-2017; 2014 Maternity leave).
Fellowships
Juan de la Cierva fellowship, Spanish Science and Innovation Ministry (MICINN). (2012-2015; declined from June 2012 onward)
Graduate Research Fellowship, National Science Foundation of the United States of America (NSF). (2006-2009)
Keynotes and other lectures
Brain2AI Workshop “How can findings about the brain improve AI systems?” Ninth International Conference on Learning Representations (ICLR). May 2021. [archived workshop and video]
Neurobiology of Language: Key Issues and Ways Forward. Nijmegen, The Netherlands. April 2021. [video]
Architectures and Mechanisms for Language Processing (AMLaP), Potsdam, Germany. September 2020. [video]
The 31st annual CUNY Human Sentence Processing Conference, UC Davis, California. March 2018. [video]
(c) 2023. Andrea E. Martin