Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

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

MPG-Autoren
/persons/resource/persons173724

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

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

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.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002D-CEBC-8
Zusammenfassung
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.