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Characterizing neural entrainment to hierarchical linguistic units using electroencephalography (EEG)

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Melloni,  Lucia
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neurology, New York University Langone Medical Center;
Department of Neurophysiology, Max-Planck Institute for Brain Research;

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Poeppel,  David
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Psychology, New York University;

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Melloni, Poeppel EEG.pdf
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Citation

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.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002E-1073-F
Abstract
To understand speech, listeners have to combine the words they hear into phrases and sentences. Recent magnetoencephalography (MEG) and electrocorticography (ECoG)studies show that cortical activity is concurrently entrained/synchronized to the rhythms of multiple levels of linguistic units including words, phrases, and sentences. Here we investigate whether this phenomenon can be observed using electroencephalography (EEG), a technique that is more widely available than MEG and ECoG. We show that the EEG responses concurrently track the rhythms of hierarchical linguistic units such as syllables/words, phrases, and sentences. The strength of the sentential-rate response correlates with how well each subject can detect random words embedded in a sequence of sentences. In contrast, only a syllabic-rate response is observed for an unintelligible control stimulus. In sum, EEG provides a useful tool to characterize neural encoding of hierarchical linguistic units, potentially even in individual participants.