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      Cortical Tracking of Hierarchical Linguistic Structures in Connected Speech

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          Abstract

          The most critical attribute of human language is its unbounded combinatorial nature: smaller elements can be combined into larger structures based on a grammatical system, resulting in a hierarchy of linguistic units, e.g., words, phrases, and sentences. Mentally parsing and representing such structures, however, poses challenges for speech comprehension. In speech, hierarchical linguistic structures do not have boundaries clearly defined by acoustic cues and must therefore be internally and incrementally constructed during comprehension. Here we demonstrate that during listening to connected speech, cortical activity of different time scales concurrently tracks the time course of abstract linguistic structures at different hierarchical levels, e.g. words, phrases, and sentences. Critically, the neural tracking of hierarchical linguistic structures is dissociated from the encoding of acoustic cues as well as from the predictability of incoming words. The results demonstrate that a hierarchy of neural processing timescales underlies grammar-based internal construction of hierarchical linguistic structure.

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          Most cited references39

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          An Introduction to the Bootstrap

          Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
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            Statistical learning by 8-month-old infants.

            Learners rely on a combination of experience-independent and experience-dependent mechanisms to extract information from the environment. Language acquisition involves both types of mechanisms, but most theorists emphasize the relative importance of experience-independent mechanisms. The present study shows that a fundamental task of language acquisition, segmentation of words from fluent speech, can be accomplished by 8-month-old infants based solely on the statistical relationships between neighboring speech sounds. Moreover, this word segmentation was based on statistical learning from only 2 minutes of exposure, suggesting that infants have access to a powerful mechanism for the computation of statistical properties of the language input.
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              Is Open Access

              Towards a neural basis of auditory sentence processing.

              Functional dissociations within the neural basis of auditory sentence processing are difficult to specify because phonological, syntactic and semantic information are all involved when sentences are perceived. In this review I argue that sentence processing is supported by a temporo-frontal network. Within this network, temporal regions subserve aspects of identification and frontal regions the building of syntactic and semantic relations. Temporal analyses of brain activation within this network support syntax-first models because they reveal that building of syntactic structure precedes semantic processes and that these interact only during a later stage.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                23 February 2016
                07 December 2015
                January 2016
                07 June 2016
                : 19
                : 1
                : 158-164
                Affiliations
                [1 ]Department of Psychology, New York University, New York, NY, USA
                [2 ]College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China
                [3 ]Department of Neurology, New York University Langone Medical Center, New York, NY, USA
                [4 ]Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt, Germany
                [5 ]Department of Psychiatry, Columbia University, New York, NY, USA
                [6 ]Department of Psychology, Peking University, Beijing, China
                [7 ]PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
                [8 ]Peking-Tsinghua Center for Life Sciences, Beijing, China
                [9 ]New York University Shanghai, Shanghai, China
                [10 ]NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China
                [11 ]Neuroscience Department, Max-Planck Institute for Empirical Aesthetics, Frankfurt, Germany
                Author notes
                [* ]Correspondence to: Nai Ding, College of Biomedical Engineering and Instrument Sciences, Zhejiang, University, Hangzhou, China. ding_nai@ 123456zju.edu.cn David Poeppel, Neuroscience Department, Max-Planck Institute for Empirical Aesthetics, Frankfurt, Germany. david.poeppel@ 123456nyu.edu
                Article
                NIHMS735484
                10.1038/nn.4186
                4809195
                26642090
                47e624d9-9ad7-4947-a6b7-9f0d5e3a04b1

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                Neurosciences
                Neurosciences

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