{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T12:46:05Z","timestamp":1783946765257,"version":"3.55.0"},"reference-count":45,"publisher":"MIT Press - Journals","issue":"9","content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Language is composed of small building blocks, which combine to form larger meaningful structures. To understand language, we must process, track, and concatenate these building blocks into larger linguistic units as speech unfolds over time. An influential idea is that phase-locking of neural oscillations across different levels of linguistic structure provides a mechanism for this process. Building on this framework, the goal of the current study was to determine whether neural phase-locking occurs more robustly to novel linguistic items that are successfully learned and encoded into memory, compared to items that are not learned. Participants listened to a continuous speech stream composed of repeating nonsense words while their EEG was recorded and then performed a recognition test on the component words. Neural phase-locking to individual words during the learning period strongly predicted the strength of subsequent word knowledge, suggesting that neural phase-locking indexes the subjective perception of specific linguistic items during real-time language learning. These findings support neural oscillatory models of language, demonstrating that words that are successfully perceived as functional units are tracked by oscillatory activity at the matching word rate. In contrast, words that are not learned are processed merely as a sequence of unrelated syllables and thus not tracked by corresponding word-rate oscillations.<\/jats:p>","DOI":"10.1162\/jocn_a_01581","type":"journal-article","created":{"date-parts":[[2020,5,19]],"date-time":"2020-05-19T15:21:12Z","timestamp":1589901672000},"page":"1735-1748","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":21,"title":["Syllables in Sync Form a Link: Neural Phase-locking Reflects Word Knowledge during Language Learning"],"prefix":"10.1162","volume":"32","author":[{"given":"Laura","family":"Batterink","sequence":"first","affiliation":[{"name":"Brain and Mind Institute, Western University, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","published-online":{"date-parts":[[2020,9,1]]},"reference":[{"key":"2022042815231801100_bib1","doi-asserted-by":"crossref","unstructured":"Assaneo,  M. F., Ripoll\u00e9s,  P., Orpella,  J., Lin,  W. M., de Diego-Balaguer,  R., & Poeppel,  D. (2019). Spontaneous synchronization to speech reveals neural mechanisms facilitating language learning. Nature Neuroscience, 22, 627\u2013632.","DOI":"10.1038\/s41593-019-0353-z"},{"key":"2022042815231801100_bib2","doi-asserted-by":"crossref","unstructured":"Batterink,  L. J., & Paller,  K. A. (2017). Online neural monitoring of statistical learning. Cortex, 90, 31\u201345.","DOI":"10.1016\/j.cortex.2017.02.004"},{"key":"2022042815231801100_bib3","doi-asserted-by":"crossref","unstructured":"Batterink,  L. J., & Paller,  K. A. (2019). Statistical learning of speech regularities can occur outside the focus of attention. Cortex, 115, 56\u201371.","DOI":"10.1016\/j.cortex.2019.01.013"},{"key":"2022042815231801100_bib4","doi-asserted-by":"crossref","unstructured":"Batterink,  L. J., Reber,  P. J., & Paller,  K. A. (2015). Functional differences between statistical learning with and without explicit training. Learning & Memory, 22, 544\u2013556.","DOI":"10.1101\/lm.037986.114"},{"key":"2022042815231801100_bib5","doi-asserted-by":"crossref","unstructured":"Bradlow,  A. R., & Bent,  T. (2008). Perceptual adaptation to non-native speech. Cognition, 106, 707\u2013729.","DOI":"10.1016\/j.cognition.2007.04.005"},{"key":"2022042815231801100_bib6","doi-asserted-by":"crossref","unstructured":"Brodbeck,  C., Hong,  L. E., & Simon,  J. Z. (2018). Rapid transformation from auditory to linguistic representations of continuous speech. Current Biology, 28, 3976\u20133983.","DOI":"10.1016\/j.cub.2018.10.042"},{"key":"2022042815231801100_bib7","doi-asserted-by":"crossref","unstructured":"Buiatti,  M., Pe\u00f1a,  M., & Dehaene-Lambertz,  G. (2009). Investigating the neural correlates of continuous speech computation with frequency-tagged neuroelectric responses. Neuroimage, 44, 509\u2013519.","DOI":"10.1016\/j.neuroimage.2008.09.015"},{"key":"2022042815231801100_bib8","doi-asserted-by":"crossref","unstructured":"Chang,  S. W., McGuire,  J. F., Walkup,  J. T., Woods,  D. W., Scahill,  L., Wilhelm,  S., et al (2018). Neurocognitive correlates of treatment response in children with Tourette's disorder. Psychiatry Research, 261, 464\u2013472.","DOI":"10.1016\/j.psychres.2017.12.066"},{"key":"2022042815231801100_bib9","doi-asserted-by":"crossref","unstructured":"Choi,  D., Batterink,  L., Black,  A. K., Paller,  K., & Werker,  J. F. (2020). Prelingual infants discover statistical word patterns at similar rates as adults: Evidence from neural entrainment. https:\/\/doi.org\/10.31234\/osf.io\/fuqd2.","DOI":"10.31234\/osf.io\/fuqd2"},{"key":"2022042815231801100_bib10","doi-asserted-by":"crossref","unstructured":"Clopper,  C. G., & Pisoni,  D. B. (2004). Effects of talker variability on perceptual learning of dialects. Language and Speech, 47, 207\u2013238.","DOI":"10.1177\/00238309040470030101"},{"key":"2022042815231801100_bib11","doi-asserted-by":"crossref","unstructured":"Delorme,  A., & Makeig,  S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134, 9\u201321.","DOI":"10.1016\/j.jneumeth.2003.10.009"},{"key":"2022042815231801100_bib12","doi-asserted-by":"crossref","unstructured":"Dickter,  C. L., & Kieffaber,  P. D. (2014). EEG methods for the psychological sciences. Thousand Oaks, CA: Sage.","DOI":"10.4135\/9781446270356"},{"key":"2022042815231801100_bib13","doi-asserted-by":"crossref","unstructured":"Ding,  N., Melloni,  L., Yang,  A., Wang,  Y., Zhang,  W., & Poeppel,  D. (2017). Characterizing neural entrainment to hierarchical linguistic units using electroencephalography (EEG). Frontiers in Human Neuroscience, 11, 481.","DOI":"10.3389\/fnhum.2017.00481"},{"key":"2022042815231801100_bib14","doi-asserted-by":"crossref","unstructured":"Ding,  N., Melloni,  L., Zhang,  H., Tian,  X., & Poeppel,  D. (2016). Cortical tracking of hierarchical linguistic structures in connected speech. Nature Neuroscience, 19, 158\u2013164.","DOI":"10.1038\/nn.4186"},{"key":"2022042815231801100_bib15","doi-asserted-by":"crossref","unstructured":"Ding,  N., & Simon,  J. Z. (2012). Emergence of neural encoding of auditory objects while listening to competing speakers. Proceedings of the National Academy of Sciences, U.S.A., 109, 11854\u201311859.","DOI":"10.1073\/pnas.1205381109"},{"key":"2022042815231801100_bib16","doi-asserted-by":"crossref","unstructured":"Doelling,  K. B., Arnal,  L. H., Ghitza,  O., & Poeppel,  D. (2014). Acoustic landmarks drive delta\u2013theta oscillations to enable speech comprehension by facilitating perceptual parsing. Neuroimage, 85, 761\u2013768.","DOI":"10.1016\/j.neuroimage.2013.06.035"},{"key":"2022042815231801100_bib17","doi-asserted-by":"crossref","unstructured":"Finn,  A. S., & Hudson Kam,  C. L. (2015). Why segmentation matters: Experience-driven segmentation errors impair \u201cmorpheme\u201d learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 1560\u20131569.","DOI":"10.1037\/xlm0000114"},{"key":"2022042815231801100_bib18","doi-asserted-by":"crossref","unstructured":"Getz,  H., Ding,  N., Newport,  E. L., & Poeppel,  D. (2018). Cortical tracking of constituent structure in language acquisition. Cognition, 181, 135\u2013140.","DOI":"10.1016\/j.cognition.2018.08.019"},{"key":"2022042815231801100_bib19","doi-asserted-by":"crossref","unstructured":"Giraud,  A.-L., & Poeppel,  D. (2012). Cortical oscillations and speech processing: Emerging computational principles and operations. Nature Neuroscience, 15, 511\u2013517.","DOI":"10.1038\/nn.3063"},{"key":"2022042815231801100_bib20","doi-asserted-by":"crossref","unstructured":"G\u00f3mez,  R. L.\n           (2002). Variability and detection of invariant structure. Psychological Science, 13, 431\u2013436.","DOI":"10.1111\/1467-9280.00476"},{"key":"2022042815231801100_bib21","doi-asserted-by":"crossref","unstructured":"Greenspan,  S. L., Nusbaum,  H. C., & Pisoni,  D. B. (1988). Perceptual learning of synthetic speech produced by rule. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 421\u2013433.","DOI":"10.1037\/0278-7393.14.3.421"},{"key":"2022042815231801100_bib22","doi-asserted-by":"crossref","unstructured":"Gross,  J., Hoogenboom,  N., Thut,  G., Schyns,  P., Panzeri,  S., Belin,  P., et al (2013). Speech rhythms and multiplexed oscillatory sensory coding in the human brain. PLoS Biology, 11, e1001752.","DOI":"10.1371\/journal.pbio.1001752"},{"key":"2022042815231801100_bib23","doi-asserted-by":"crossref","unstructured":"Horton,  C., D'Zmura,  M., & Srinivasan,  R. (2013). Suppression of competing speech through entrainment of cortical oscillations. Journal of Neurophysiology, 109, 3082\u20133093.","DOI":"10.1152\/jn.01026.2012"},{"key":"2022042815231801100_bib24","doi-asserted-by":"crossref","unstructured":"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\u2013647.","DOI":"10.1146\/annurev.psych.093008.131123"},{"key":"2022042815231801100_bib25","doi-asserted-by":"crossref","unstructured":"Lakatos,  P., Karmos,  G., Mehta,  A. D., Ulbert,  I., & Schroeder,  C. E. (2008). Entrainment of neuronal oscillations as a mechanism of attentional selection. Science, 320, 110\u2013113.","DOI":"10.1126\/science.1154735"},{"key":"2022042815231801100_bib26","doi-asserted-by":"crossref","unstructured":"Mullen,  T. R., Kothe,  C. A. E., Chi,  Y. M., Ojeda,  A., Kerth,  T., Makeig,  S., et al (2015). Real-time neuroimaging and cognitive monitoring using wearable dry EEG. IEEE Transactions on Biomedical Engineering, 62, 2553\u20132567.","DOI":"10.1109\/TBME.2015.2481482"},{"key":"2022042815231801100_bib27","doi-asserted-by":"crossref","unstructured":"Nozaradan,  S., Peretz,  I., & Keller,  P. E. (2016). Individual differences in rhythmic cortical entrainment correlate with predictive behavior in sensorimotor synchronization. Scientific Reports, 6, 20612.","DOI":"10.1038\/srep20612"},{"key":"2022042815231801100_bib28","doi-asserted-by":"crossref","unstructured":"Nozaradan,  S., Peretz,  I., Missal,  M., & Mouraux,  A. (2011). Tagging the neuronal entrainment to beat and meter. Journal of Neuroscience, 31, 10234\u201310240.","DOI":"10.1523\/JNEUROSCI.0411-11.2011"},{"key":"2022042815231801100_bib29","doi-asserted-by":"crossref","unstructured":"Park,  H., Ince,  R. A. A., Schyns,  P. G., Thut,  G., & Gross,  J. (2015). Frontal top\u2013down signals increase coupling of auditory low-frequency oscillations to continuous speech in human listeners. Current Biology, 25, 1649\u20131653.","DOI":"10.1016\/j.cub.2015.04.049"},{"key":"2022042815231801100_bib30","doi-asserted-by":"crossref","unstructured":"Peelle,  J. E., & Davis,  M. H. (2012). Neural oscillations carry speech rhythm through to comprehension. Frontiers in Psychology, 3, 320.","DOI":"10.3389\/fpsyg.2012.00320"},{"key":"2022042815231801100_bib31","doi-asserted-by":"crossref","unstructured":"Riecke,  L., Formisano,  E., Sorger,  B., Ba\u015fkent,  D., & Gaudrain,  E. (2018). Neural entrainment to speech modulates speech intelligibility. Current Biology, 28, 161\u2013169.","DOI":"10.1016\/j.cub.2017.11.033"},{"key":"2022042815231801100_bib32","doi-asserted-by":"crossref","unstructured":"Rimmele,  J. M., Zion Golumbic,  E., Schr\u00f6ger,  E., & Poeppel,  D. (2015). The effects of selective attention and speech acoustics on neural speech-tracking in a multi-talker scene. Cortex, 68, 144\u2013154.","DOI":"10.1016\/j.cortex.2014.12.014"},{"key":"2022042815231801100_bib33","doi-asserted-by":"crossref","unstructured":"Saffran,  J. R., Newport,  E. L., & Aslin,  R. N. (1996). Word segmentation: The role of distributional cues. Journal of Memory and Language, 35, 606\u2013621.","DOI":"10.1006\/jmla.1996.0032"},{"key":"2022042815231801100_bib34","doi-asserted-by":"crossref","unstructured":"Saffran,  J. R., Newport,  E. L., Aslin,  R. N., Tunick,  R. A., & Barrueco,  S. (1997). Incidental language learning: Listening (and learning) out of the corner of your ear. Psychological Science, 8, 101\u2013105.","DOI":"10.1111\/j.1467-9280.1997.tb00690.x"},{"key":"2022042815231801100_bib35","doi-asserted-by":"crossref","unstructured":"Sanders,  L. D., Newport,  E. L., & Neville,  H. J. (2002). Segmenting nonsense: An event-related potential index of perceived onsets in continuous speech. Nature Neuroscience, 5, 700\u2013703.","DOI":"10.1038\/nn873"},{"key":"2022042815231801100_bib36","doi-asserted-by":"crossref","unstructured":"Schroeder,  C. E., & Lakatos,  P. (2009). Low-frequency neuronal oscillations as instruments of sensory selection. Trends in Neurosciences, 32, 9\u201318.","DOI":"10.1016\/j.tins.2008.09.012"},{"key":"2022042815231801100_bib37","unstructured":"Seltman,  H. J.\n           (2012). Experimental design and analysis. Carnegie Mellon University. http:\/\/www.stat.cmu.edu\/\u223chseltman\/309\/Book\/Book.pdf."},{"key":"2022042815231801100_bib38","doi-asserted-by":"crossref","unstructured":"Siegelman,  N., Bogaerts,  L., Elazar,  A., Arciuli,  J., & Frost,  R. (2018). Linguistic entrenchment: Prior knowledge impacts statistical learning performance. Cognition, 177, 198\u2013213.","DOI":"10.1016\/j.cognition.2018.04.011"},{"key":"2022042815231801100_bib39","doi-asserted-by":"crossref","unstructured":"Siegelman,  N., Bogaerts,  L., Kronenfeld,  O., & Frost,  R. (2018). Redefining \u201clearning\u201d in statistical learning: What does an online measure reveal about the assimilation of visual regularities?Cognitive Science, 42, 692\u2013727.","DOI":"10.1111\/cogs.12556"},{"key":"2022042815231801100_bib40","doi-asserted-by":"crossref","unstructured":"Singh,  L.\n           (2008). Influences of high and low variability on infant word recognition. Cognition, 106, 833\u2013870.","DOI":"10.1016\/j.cognition.2007.05.002"},{"key":"2022042815231801100_bib41","doi-asserted-by":"crossref","unstructured":"Thut,  G., Miniussi,  C., & Gross,  J. (2012). The functional importance of rhythmic activity in the brain. Current Biology, 22, R658\u2013R663.","DOI":"10.1016\/j.cub.2012.06.061"},{"key":"2022042815231801100_bib42","doi-asserted-by":"crossref","unstructured":"Vouloumanos,  A., Brosseau-Liard,  P. E., Balaban,  E., & Hager,  A. D. (2012). Are the products of statistical learning abstract or stimulus-specific?Frontiers in Psychology, 3, 70.","DOI":"10.3389\/fpsyg.2012.00070"},{"key":"2022042815231801100_bib43","doi-asserted-by":"crossref","unstructured":"Wilsch,  A., Neuling,  T., Obleser,  J., & Herrmann,  C. S. (2018). Transcranial alternating current stimulation with speech envelopes modulates speech comprehension. Neuroimage, 172, 766\u2013774.","DOI":"10.1016\/j.neuroimage.2018.01.038"},{"key":"2022042815231801100_bib44","doi-asserted-by":"crossref","unstructured":"Zion Golumbic,  E. M., Ding,  N., Bickel,  S., Lakatos,  P., Schevon,  C. A., McKhann,  G. M., et al (2013). Mechanisms underlying selective neuronal tracking of attended speech at a \u201ccocktail party\u201d. Neuron, 77, 980\u2013991.","DOI":"10.1016\/j.neuron.2012.12.037"},{"key":"2022042815231801100_bib45","doi-asserted-by":"crossref","unstructured":"Zoefel,  B., Archer-Boyd,  A., & Davis,  M. H. (2018). Phase entrainment of brain oscillations causally modulates neural responses to intelligible speech. Current Biology, 28, 401\u2013408.","DOI":"10.1016\/j.cub.2017.11.071"}],"container-title":["Journal of Cognitive Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/direct.mit.edu\/jocn\/article-pdf\/32\/9\/1735\/2013783\/jocn_a_01581.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/direct.mit.edu\/jocn\/article-pdf\/32\/9\/1735\/2013783\/jocn_a_01581.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:49:45Z","timestamp":1651193385000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/jocn\/article\/32\/9\/1735\/95478\/Syllables-in-Sync-Form-a-Link-Neural-Phase-locking"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,1]]},"references-count":45,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,9,1]]},"published-print":{"date-parts":[[2020,9,1]]}},"URL":"https:\/\/doi.org\/10.1162\/jocn_a_01581","relation":{},"ISSN":["0898-929X","1530-8898"],"issn-type":[{"value":"0898-929X","type":"print"},{"value":"1530-8898","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,9]]},"published":{"date-parts":[[2020,9,1]]}}}