Modulation of working memory capacity on predictive processing during language comprehension

References

• Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. https://doi.org/10.1016/j.jml.2007.12.005
   Web of Science ®Google Scholar
• Baggio, G. (2018). Meaning in the Brain. MIT Press.
   Google Scholar
• Baggio, G., & Hagoort, P. (2011). The balance between memory and unification in semantics: A dynamic account of the N400. Language and Cognitive Processes, 26(9), 1338–1367. https://doi.org/10.1080/01690965.2010.542671
   Web of Science ®Google Scholar
• Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
   Web of Science ®Google Scholar
• Bonhage, C. E., Mueller, J. L., Friederici, A. D., & Fiebach, C. J. (2015). Combined eye tracking and fMRI reveals neural basis of linguistic predictions during sentence comprehension. Cortex, 68, 33–47. https://doi.org/10.1016/j.cortex.2015.04.011
   PubMed Web of Science ®Google Scholar
• Borodkin, K., Kenett, Y. N., Faust, M., & Mashal, N. (2016). When pumpkin is closer to onion than to squash: The structure of the second language lexicon. Cognition, 156, 60–70. https://doi.org/10.1016/j.cognition.2016.07.014
   PubMed Web of Science ®Google Scholar
• Boudewyn, M. A., Long, D. L., & Swaab, T. Y. (2013). Effects of working memory span on processing of lexical associations and congruence in spoken discourse. Frontiers in Psychology, 4, 60. https://doi.org/10.3389/fpsyg.2013.00060
   PubMed Web of Science ®Google Scholar
• Brothers, T., Dave, S., Hoversten, L. J., Traxler, M. J., & Swaab, T. Y. (2019). Flexible predictions during listening comprehension: Speaker reliability affects anticipatory processes. Neuropsychologia, 135, 107225. https://doi.org/10.1016/j.neuropsychologia.2019.107225
   PubMed Web of Science ®Google Scholar
• Brothers, T., Swaab, T. Y., & Traxler, M. J. (2017). Goals and strategies influence lexical prediction during sentence comprehension. Journal of Memory and Language, 93, 203–216. https://doi.org/10.1016/j.jml.2016.10.002
   Web of Science ®Google Scholar
• Chinese Linguistic Data Consortium. (2003). 现代汉语通用词表 [Chinese lexicon] (CLDC-LAC-2003-001). Tsinghua University, State Key Laboratory of Intelligent Technology and Systems, and Chinese Academy of Sciences, Institute of Automation.
   Google Scholar
• Cui, Y., & Chen, Y. (1996). Predictive inference in reading. Acta Psychologica Sinica, 28(3), 238–244.
   Google Scholar
• Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466. https://doi.org/10.1016/S0022-5371(80)90312-6
   Google Scholar
• DeLong, K. A., Urbach, T. P., & Kutas, M. (2005). Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience, 8(8), 1117–1121. https://doi.org/10.1038/nn1504
   PubMed Web of Science ®Google Scholar
• Diaz, M. T., & Swaab, T. Y. (2007). Electrophysiological differentiation of phonological and semantic integration in word and sentence contexts. Brain Research, 1146, 85–100. http://doi.org/10.1016/j.brainres.2006.07.034
   PubMed Web of Science ®Google Scholar
• Dikker, S., & Pylkkänen, L. (2013). Predicting language: MEG evidence for lexical preactivation. Brain and Language, 127(1), 55–64. https://doi.org/10.1016/j.bandl.2012.08.004
   PubMed Web of Science ®Google Scholar
• Ding, J., Wang, L., & Yang, Y. (2020). The influence of emotional words on predictive processing during sentence comprehension. Language, Cognition and Neuroscience, 35(2), 151–162. https://doi.org/10.1080/23273798.2019.1628283
   Web of Science ®Google Scholar
• Estevez, A., & Calvo, M. G. (2000). Working memory capacity and time course of predictive inferences. Memory (Hove, England), 8(1), 51–61. https://doi.org/10.1080/096582100387704
   PubMed Web of Science ®Google Scholar
• Evans, J. S. B. T. (2002). Logic and human reasoning: an assessment of the deduction paradigm. Psychological Bulletin, 128(6), 978–996. https://doi.org/10.1037/0033-2909.128.6.978
   PubMed Web of Science ®Google Scholar
• Evans, J. S. B. T. (2003). In two minds: dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10), 454–459. https://doi.org/10.1016/j.tics.2003.08.012
   PubMed Web of Science ®Google Scholar
• Evans, J. S. B. T., & Over, D. E. (1996). Reasoning and rationality. Psychology Press.
   Google Scholar
• Federmeier, K. D. (2007). Thinking ahead: the role and roots of prediction in language comprehension. Psychophysiology, 44(4), 491–505. https://doi.org/10.1111/j.1469-8986.2007.00531.x
   PubMed Web of Science ®Google Scholar
• Federmeier, K. D., & Kutas, M. (1999). A rose by any other name: Long-term memory structure and sentence processing. Journal of Memory and Language, 41(4), 469–495. https://doi.org/10.1006/jmla.1999.2660
   Web of Science ®Google Scholar
• Federmeier, K. D., McLennan, D. B., De Ochoa, E., & Kutas, M. (2002). The impact of semantic memory organization and sentence context information on spoken language processing by younger and older adults: an ERP study. Psychophysiology, 39(2), 133–146. https://doi.org/10.1017/s0048577202001373
   PubMed Web of Science ®Google Scholar
• Forster, K. I., & Chambers, S. M. (1973). Lexical access and naming time. Journal of Verbal Learning and Verbal Behavior, 12(6), 627–635. https://doi.org/10.1016/S0022-5371(73)80042-8
   Google Scholar
• Freunberger, D., & Roehm, D. (2017). The costs of being certain: Brain potential evidence for linguistic preactivation in sentence processing. Psychophysiology, 54(6), 824–832. https://doi.org/10.1111/psyp.12848
   PubMed Web of Science ®Google Scholar
• Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138. https://doi.org/10.1038/nrn2787
   PubMed Web of Science ®Google Scholar
• Griffin, Z. M., & Bock, K. (1998). Constraint, word frequency, and the relationship between lexical processing levels in spoken word production. Journal of Memory and Language, 38(3), 313–338. https://doi.org/10.1006/jmla.1997.2547
   Web of Science ®Google Scholar
• Grisoni, L., Miller, T. M., & Pulvermüller, F. (2017). Neural Correlates of Semantic Prediction and Resolution in Sentence Processing. Journal of Neuroscience, 37(18), 4848–4858. https://doi.org/10.1523/jneurosci.2800-16.2017
   PubMed Web of Science ®Google Scholar
• Hagoort, P., Hald, L., Bastiaansen, M., & Petersson, K. M. (2004). Integration of word meaning and world knowledge in language comprehension. Science, 304(5669), 438–441. https://doi.org/10.1126/science.1095455
   PubMed Web of Science ®Google Scholar
• Hauk, O., Davis, M. H., Ford, M., Pulvermüller, F., & Marslen-Wilson, W. D. (2006). The time course of visual word recognition as revealed by linear regression analysis of ERP data. Neuroimage, 30(4), 1383–1400. https://doi.org/10.1016/j.neuroimage.2005.11.048
   PubMed Web of Science ®Google Scholar
• Howe, M. L., Rabinowitz, F. M., & Powell, T. L. (1998). Individual differences in working memory and reasoning-remembering relationships in solving class-inclusion problems. Memory & Cognition, 26(5), 1089–1101. https://doi.org/10.3758/BF03201185
   PubMed Web of Science ®Google Scholar
• Huettig, F. (2015). Four central questions about prediction in language processing. Brain Research, 1626, 118–135. https://doi.org/10.1016/j.brainres.2015.02.014
   PubMed Web of Science ®Google Scholar
• Huettig, F., & Janse, E. (2016). Individual differences in working memory and processing speed predict anticipatory spoken language processing in the visual world. Language, Cognition and Neuroscience, 31(1), 80–93. https://doi.org/10.1080/23273798.2015.1047459
   Web of Science ®Google Scholar
• Ito, A., Corley, M., & Pickering, M. J. (2018). A cognitive load delays predictive eye movements similarly during L1 and L2 comprehension. Bilingualism: Language and Cognition, 21(2), 251–264. https://doi.org/10.1017/S1366728917000050
   Web of Science ®Google Scholar
• 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, and Kutas (2017). Language, Cognition and Neuroscience, 32(8), 974–983. https://doi.org/10.1080/23273798.2017.1323112
   Web of Science ®Google Scholar
• Ito, A., & Pickering, M. J. (2021). Automaticity and prediction in non-native language comprehension. In E. Kaan, & T. Grüter (Eds.), Prediction in Second Language Processing and Learning (pp. 26–46). John Benjamins Publishing.
   Google Scholar
• Janse, E., & Jesse, A. (2014). Working memory affects older adults’ use of context in spoken-word recognition. Quarterly Journal of Experimental Psychology, 67(9), 1842–1862. https://doi.org/10.1080/17470218.2013.879391
   PubMed Web of Science ®Google Scholar
• Klaczynski, P. A., & Daniel, D. B. (2005). Individual differences in conditional reasoning: A dual-process account. Thinking & Reasoning, 11(4), 305–325. https://doi.org/10.1080/13546780442000196
   Web of Science ®Google Scholar
• Kochari, A. R., & Flecken, M. (2019). Lexical prediction in language comprehension: a replication study of grammatical gender effects in Dutch. Language, Cognition and Neuroscience, 34(2), 239–253. https://doi.org/10.1080/23273798.2018.1524500
   Web of Science ®Google Scholar
• Kuperberg, G. R., & Jaeger, T. F. (2016). What do we mean by prediction in language comprehension? Language, Cognition and Neuroscience, 31(1), 32–59. https://doi.org/10.1080/23273798.2015.1102299
   PubMed Web of Science ®Google Scholar
• Kutas, M., & Federmeier, K. D. (2000). Electrophysiology reveals semantic memory use in language comprehension. Trends in Cognitive Sciences, 4(12), 463–470. https://doi.org/10.1016/S1364-6613(00)01560-6
   PubMed Web of Science ®Google Scholar
• Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology, 62, 621–647. https://doi.org/10.1146/annurev.psych.093008.131123
   PubMed Web of Science ®Google Scholar
• Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207(4427), 203–205. https://doi.org/10.1126/science.7350657
   PubMed Web of Science ®Google Scholar
• Kutas, M., & Hillyard, S. A. (1984). Brain potentials during reading reflect word expectancy and semantic association. Nature, 307(5947), 161–163. https://doi.org/10.1038/307161a0
   PubMed Web of Science ®Google Scholar
• Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13
   Web of Science ®Google Scholar
• Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211–240. https://doi.org/10.1037//0033-295X.104.2.211
   Web of Science ®Google Scholar
• León-Cabrera, P., Rodríguez-Fornells, A., & Morís, J. (2017). Electrophysiological correlates of semantic anticipation during speech comprehension. Neuropsychologia, 99, 326–334. https://doi.org/10.1016/j.neuropsychologia.2017.02.026
   PubMed Web of Science ®Google Scholar
• Li, X., Ren, G., Zheng, Y., & Chen, Y. (2020). How does dialectal experience modulate anticipatory speech processing? Journal of Memory and Language, 115, 104169. https://doi.org/10.1016/j.jml.2020.104169
   Web of Science ®Google Scholar
• Li, X., Zhang, Y., Xia, J., & Swaab, T. Y. (2017). Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations. Neuropsychologia, 102, 70–81. https://doi.org/10.1016/j.neuropsychologia.2017.05.017
   PubMed Web of Science ®Google Scholar
• Linderholm, T. (2002). Predictive inference generation as a function of working memory capacity and causal text constraints. Discourse Processes, 34(3), 259–280. https://doi.org/10.1207/S15326950DP3403_2
   Web of Science ®Google Scholar
• Luck, S. J., & Gaspelin, N. (2017). How to get statistically significant effects in any ERP experiment (and why you shouldn't). Psychophysiology, 54(1), 146–157. https://doi.org/10.1111/psyp.12639
   PubMed Web of Science ®Google Scholar
• Maess, B., Mamashli, F., Obleser, J., Helle, L., & Friederici, A. D. (2016). Prediction signatures in the brain: Semantic pre-activation during language comprehension. Frontiers in Humman Neuroscience, 10, 591. https://doi.org/10.3389/fnhum.2016.00591
   PubMed Web of Science ®Google Scholar
• Mckoon, G., & Ratcliff, R. (1986). Inferences about predictable events. Journal of Experimental Psychology Learning Memory and Cognition, 12(1), 82–91. https://doi.org/10.1037//0278-7393.12.1.82
   PubMed Web of Science ®Google Scholar
• Nakano, H., Saron, C., & Swaab, T. Y. (2010). Speech and span: working memory capacity impacts the use of animacy but not of world knowledge during spoken sentence comprehension. Journal of Cognitive Neuroscience, 22(12), 2886–2898. https://doi.org/10.1162/jocn.2009.21400
   PubMed Web of Science ®Google Scholar
• Nieuwland, M. S., Barr, D. J., Bartolozzi, F., Busch-Moreno, S., Darley, E., Donaldson, D. I., … Von Grebmer Zu Wolfsthurn, S. (2020). Dissociable effects of prediction and integration during language comprehension: evidence from a large-scale study using brain potentials. Philosophical transactions of the Royal Society of London. Series B, Biological Sciences, 375(1791), 20180522. https://doi.org/10.1098/rstb.2018.0522
   PubMed Web of Science ®Google Scholar
• Nieuwland, M. S., Politzer-Ahles, S., Heyselaar, E., Segaert, K., Darley, E., Kazanina, N., … Huettig, F. (2018). Large-scale replication study reveals a limit on probabilistic prediction in language comprehension. Elife, 7), https://doi.org/10.7554/eLife.33468
   PubMed Web of Science ®Google Scholar
• Nieuwland, M. S., & Van Berkum, J. J. (2006). Individual differences and contextual bias in pronoun resolution: evidence from ERPs. Brain Research, 1118(1), 155–167. https://doi.org/10.1016/j.brainres.2006.08.022
   PubMedGoogle Scholar
• Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J. M. (2011). FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational intelligence and neuroscience, 2011, 156869. https://doi.org/10.1155/2011/156869
   PubMed Web of Science ®Google Scholar
• Otten, M., & Van Berkum, J. J. (2009). Does working memory capacity affect the ability to predict upcoming words in discourse? Brain Research, 1291, 92–101. https://doi.org/10.1016/j.brainres.2009.07.042
   PubMed Web of Science ®Google Scholar
• Payne, B. R., & Silcox, J. W. (2019). Chapter Seven - Aging, context processing, and comprehension. In K. D. Federmeier (Ed.), Psychology of Learning and Motivation (Vol. 71) (pp. 215–264). Academic Press.
   Google Scholar
• Pérez, A. I., Paolieri, D., Macizo, P., & Bajo, T. (2014). The role of working memory in inferential sentence comprehension. Cognitive Processing, 15(3), 405–413. https://doi.org/10.1007/s10339-014-0611-7
   PubMed Web of Science ®Google Scholar
• Piai, V., Anderson, K. L., Lin, J. J., Dewar, C., Parvizi, J., Dronkers, N. F., & Knight, R. T. (2016). Direct brain recordings reveal hippocampal rhythm underpinnings of language processing. Proceedings of the National Academy of Sciences of the United States of America, 113(40), 11366–11371. https://doi.org/10.1073/pnas.1603312113
   PubMed Web of Science ®Google Scholar
• Pulvermüller, F., & Grisoni, L. (2020). Semantic Prediction in Brain and Mind. Trends in Cognitive Sciences, 24(10), 781–784. https://doi.org/10.1016/j.tics.2020.07.002
   PubMed Web of Science ®Google Scholar
• R Core Team. (2018). A language and environment for statistical computing (Version 3.5.0). https://www.r-project.org.
   Google Scholar
• Rommers, J., Dickson, D. S., Norton, J. J. S., Wlotko, E. W., & Federmeier, K. D. (2017). Alpha and theta band dynamics related to sentential constraint and word expectancy. Language Cognition and Neuroscience, 32(5), 576–589. https://doi.org/10.1080/23273798.2016.1183799
   PubMed Web of Science ®Google Scholar
• Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: implications for the rationality debate? Behavioral and Brain Sciences, 23(5), 645–665. https://doi.org/10.1017/s0140525(00003435
   PubMed Web of Science ®Google Scholar
• Szewczyk, J. M., & Schriefers, H. (2018). The N400 as an index of lexical preactivation and its implications for prediction in language comprehension. Language, Cognition and Neuroscience, 33(6), 665–686. https://doi.org/10.1080/23273798.2017.1401101
   Web of Science ®Google Scholar
• Van Berkum, J. J., Brown, C. M., Zwitserlood, P., Kooijman, V., & Hagoort, P. (2005). Anticipating upcoming words in discourse: evidence from ERPs and reading times. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(3), 443–467. https://doi.org/10.1037/0278-7393.31.3.443
   PubMed Web of Science ®Google Scholar
• Van Petten, C., & Kutas, M. (1990). Interactions between sentence context and word frequency in event-related brain potentials. Memory and Cognition, 18, 380–393. https://doi.org/10.3758/BF03197127
   PubMed Web of Science ®Google Scholar
• Van Petten, C., & Kutas, M. (1991). Influences of semantic and syntactic context on open- and closed-class words. Memory and Cognition, 19, 95–112. https://doi.org/10.3758/BF03198500
   PubMed Web of Science ®Google Scholar
• Van Petten, C., & Luka, B. J. (2012). Prediction during language comprehension: benefits, costs, and ERP components. International Journal of Psychophysiology, 83(2), 176–190. https://doi.org/10.1016/j.ijpsycho.2011.09.015
   PubMed Web of Science ®Google Scholar
• Van Petten, C., & Rheinfelder, H. (1995). Conceptual relationships between spoken words and environmental sounds: Event-related brain potential measures. Neuropsychologia, 33, 485–508. https://doi.org/10.1016/0028-3932(94)00133-A
   PubMed Web of Science ®Google Scholar
• Van Petten, C., Weckerly, J., McIsaac, H. K., & Kutas, M. (1997). Working Memory Capacity Dissociates Lexical and Sentential Context Effects. Psychological Science, 8(3), 238–242. https://doi.org/10.1111/j.1467-9280.1997.tb00418.x
   Web of Science ®Google Scholar
• Vasishth, S. (2023). Some right ways to analyze (psycho) linguistic data. Annual Review of Linguistics, 9, 273–291. https://doi.org/10.1146/annurev-linguistics-031220-010345
   Web of Science ®Google Scholar
• Virtue, S., Parrish, T., & Jung-Beeman, M. (2008). Inferences during story comprehension: cortical recruitment affected by predictability of events and working memory capacity. Joural of Cognitive Neuroscience, 20(12), 2274–2284. https://doi.org/10.1162/jocn.2008.20160
   PubMed Web of Science ®Google Scholar
• Wang, L., Hagoort, P., & Jensen, O. (2018). Language Prediction Is Reflected by Coupling between Frontal Gamma and Posterior Alpha Oscillations. Journal of Cognitive Neuroscience, 30(3), 432–447. https://doi.org/10.1162/jocn_a_01190
   PubMed Web of Science ®Google Scholar
• Wang, L., Kuperberg, G., & Jensen, O. (2018). Specific lexico-semantic predictions are associated with unique spatial and temporal patterns of neural activity. Elife, 7, e39061. https://doi.org/10.7554/eLife.39061
   PubMed Web of Science ®Google Scholar
• Wicha, N. Y. Y., Moreno, E. M., & Kutas, M. (2003). Expecting gender: an event related brain potential study on the role of grammatical gender in comprehending a line drawing within a written sentence in Spanish. Cortex, 39(3), 483–508. https://doi.org/10.1016/s0010-9452(08)70260-0
   PubMed Web of Science ®Google Scholar
• Wicha, N. Y. Y., Moreno, E. M., & Kutas, M. (2004). Anticipating words and their gender: an event-related brain potential study of semantic integration, gender expectancy, and gender agreement in Spanish sentence reading. Journal of Cognitive Neuroscience, 16(7), 1272–1288. https://doi.org/10.1162/0898929041920487
   PubMed Web of Science ®Google Scholar
• Yang, X., Zhang, X., Zhang, Y., Zhang, Q., & Li, X. (2020). How working memory capacity modulates the time course of semantic integration at sentence and discourse level. Neuropsychologia, 140, 107383. https://doi.org/10.1016/j.neuropsychologia.2020.107383
   PubMed Web of Science ®Google Scholar
• Yeari, M. (2017). The role of working memory in inference generation during reading comprehension: Retention, (re)activation, or suppression of verbal information? Learning and Individual Differences, 56, 1–12. https://doi.org/10.1016/j.lindif.2017.04.002
   Web of Science ®Google Scholar
• Zheng, Y., Zhao, Z., Yang, X., & Li, X. (2021). The impact of musical expertise on anticipatory semantic processing during online speech comprehension: An electroencephalography study. Brain and Language, 221, 105006. https://doi.org/10.1016/j.bandl.2021.105006
   PubMed Web of Science ®Google Scholar
• Zuur, A. F., Ieno, E. N., & Elphick, C. S. (2010). A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution, 1(1), 3–14. https://doi.org/10.1111/j.2041-210X.2009.00001.x
   Web of Science ®Google Scholar