experimental and computational approaches to
language processing and cognition
the structure (and statistics) of language in neural dynamics
Current Position
Lise Meitner Group Leader
Principal Investigator
PI Group: Language and Computation in Neural Systems
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
2024
*Zioga, I., Zhou, J., Weissbart, H., Martin, A. E., & Haegens, S. (2024). Alpha and beta oscillations differentially support word production in a rule-switching task. Accepted at eNeuro.
2023
*ten Oever, S., & Martin, A. E. (2023). Interdependence of what and when in the brain. In press at Journal of Cognitive Neuroscience.
*Coopmans, C. W., Mai, A., Slaats, S., Weissbart, H., & Martin, A. E. (2023) What oscillations can do for syntax depends on your theory of structure building. Letter in Nature Reviews Neuroscience. [.pdf]
*Tezcan, F., Weissbart, H., & Martin, A. E. (2023). A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension. eLife. [.pdf]
*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. Journal of Neuroscience. [.pdf]
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. Journal of Neuroscience. [.pdf]
*Coopmans, C. W., Kaushik, K., & Martin, A. E. (2023). Hierarchical structure in language and action: A formal comparison. Psychological Review. [.pdf] [preprint]
*Guest, O. & Martin, A. E. (2023). On logical inference over brains, 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
Weissbart, H., & Martin, A. E. (2023). The structure and statistics of language jointly shape cross-frequency dynamics during spoken language comprehension. [biorxiv]
*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; 2020-2025; converted to Lise Meitner Group).
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, invited lectures, and other videos
Brain Inspired Podcast hosted by Paul Middlebrooks - Neural Dynamics and Language. May 2023. [video + podcast recording]
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