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  Rule-based and statistics-based processing of language: Insights from neuroscience

Ding, N., Melloni, L., Tian, X., & Poeppel, D. (2017). Rule-based and statistics-based processing of language: Insights from neuroscience. Language, Cognition and Neuroscience, 32(5), 570-575. doi:10.1080/23273798.2016.1215477.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-CEBC-8 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-CEBE-4
Genre: Journal Article

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 Creators:
Ding, Nai, Author
Melloni, Lucia1, 2, Author              
Tian, Xing, Author
Poeppel, David3, 4, Author              
Affiliations:
1New York University Langone Medical Center , New York, NY, USA, ou_persistent22              
2Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt, Germany, ou_persistent22              
3Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, Grüneburgweg 14, 60322 Frankfurt am Main, DE, ou_2421697              
4New York University, New York, NY, USA, ou_persistent22              

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Free keywords: Speech, language, neural oscillations, grammar, statistics
 Abstract: To flexibly convey meaning, the human language faculty iteratively combines smaller units such as words into larger structures such as phrases based on grammatical principles. During comprehension, however, it remains unclear how the brain encodes the relationship between words and combines them into phrases. One hypothesis is that internal grammatical principles governing language generation are also used to parse the hierarchical syntactic structure of spoken language. An alternative hypothesis suggests, in contrast, that decoding language during comprehension solely relies on statistical relationships between words or strings of words, that is, the N-gram statistics, and no hierarchical linguistic structures are constructed. Here, we briefly review distinctions between rule-based hierarchical models and statistics-based linear string models for comprehension. Recent neurolinguistic studies show that tracking of probabilistic relationships between words is not sufficient to explain cortical encoding of linguistic constituent structure and support the involvement of rule-based processing during language comprehension.

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Language(s): eng - English
 Dates: 2016-01-152016-07-052016-08-062017
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1080/23273798.2016.1215477
 Degree: -

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Title: Language, Cognition and Neuroscience
Source Genre: Journal
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Publ. Info: London : Routledge
Pages: - Volume / Issue: 32 (5) Sequence Number: - Start / End Page: 570 - 575 Identifier: Other: ISSN
CoNE: /journals/resource/2327-3798