Literature DB >> 22688633

The neurobiology of syntax: beyond string sets.

Karl Magnus Petersson1, Peter Hagoort.   

Abstract

The human capacity to acquire language is an outstanding scientific challenge to understand. Somehow our language capacities arise from the way the human brain processes, develops and learns in interaction with its environment. To set the stage, we begin with a summary of what is known about the neural organization of language and what our artificial grammar learning (AGL) studies have revealed. We then review the Chomsky hierarchy in the context of the theory of computation and formal learning theory. Finally, we outline a neurobiological model of language acquisition and processing based on an adaptive, recurrent, spiking network architecture. This architecture implements an asynchronous, event-driven, parallel system for recursive processing. We conclude that the brain represents grammars (or more precisely, the parser/generator) in its connectivity, and its ability for syntax is based on neurobiological infrastructure for structured sequence processing. The acquisition of this ability is accounted for in an adaptive dynamical systems framework. Artificial language learning (ALL) paradigms might be used to study the acquisition process within such a framework, as well as the processing properties of the underlying neurobiological infrastructure. However, it is necessary to combine and constrain the interpretation of ALL results by theoretical models and empirical studies on natural language processing. Given that the faculty of language is captured by classical computational models to a significant extent, and that these can be embedded in dynamic network architectures, there is hope that significant progress can be made in understanding the neurobiology of the language faculty.

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Year:  2012        PMID: 22688633      PMCID: PMC3367693          DOI: 10.1098/rstb.2012.0101

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  56 in total

1.  Analog neural nets with gaussian or other common noise distribution cannot recognize arbitrary regular languages.

Authors:  W Maass; E D Sontag
Journal:  Neural Comput       Date:  1999-04-01       Impact factor: 2.026

Review 2.  A genomic regulatory network for development.

Authors:  Eric H Davidson; Jonathan P Rast; Paola Oliveri; Andrew Ransick; Cristina Calestani; Chiou-Hwa Yuh; Takuya Minokawa; Gabriele Amore; Veronica Hinman; Cesar Arenas-Mena; Ochan Otim; C Titus Brown; Carolina B Livi; Pei Yun Lee; Roger Revilla; Alistair G Rust; Zheng jun Pan; Maria J Schilstra; Peter J C Clarke; Maria I Arnone; Lee Rowen; R Andrew Cameron; David R McClay; Leroy Hood; Hamid Bolouri
Journal:  Science       Date:  2002-03-01       Impact factor: 47.728

3.  Dynamic changes in the functional anatomy of the human brain during recall of abstract designs related to practice.

Authors:  K M Petersson; C Elfgren; M Ingvar
Journal:  Neuropsychologia       Date:  1999-05       Impact factor: 3.139

Review 4.  Functional MRI of language: new approaches to understanding the cortical organization of semantic processing.

Authors:  Susan Bookheimer
Journal:  Annu Rev Neurosci       Date:  2002-03-19       Impact factor: 12.449

Review 5.  The faculty of language: what is it, who has it, and how did it evolve?

Authors:  Marc D Hauser; Noam Chomsky; W Tecumseh Fitch
Journal:  Science       Date:  2002-11-22       Impact factor: 47.728

Review 6.  Language, music, syntax and the brain.

Authors:  Aniruddh D Patel
Journal:  Nat Neurosci       Date:  2003-07       Impact factor: 24.884

7.  Unpredictability and undecidability in dynamical systems.

Authors: 
Journal:  Phys Rev Lett       Date:  1990-05-14       Impact factor: 9.161

8.  Syntactic structure assembly in human parsing: a computational model based on competitive inhibition and a lexicalist grammar.

Authors:  T Vosse; G Kempen
Journal:  Cognition       Date:  2000-05-15

9.  Caspr2, a new member of the neurexin superfamily, is localized at the juxtaparanodes of myelinated axons and associates with K+ channels.

Authors:  S Poliak; L Gollan; R Martinez; A Custer; S Einheber; J L Salzer; J S Trimmer; P Shrager; E Peles
Journal:  Neuron       Date:  1999-12       Impact factor: 17.173

Review 10.  Computational and evolutionary aspects of language.

Authors:  Martin A Nowak; Natalia L Komarova; Partha Niyogi
Journal:  Nature       Date:  2002-06-06       Impact factor: 49.962

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  13 in total

1.  Pattern perception and computational complexity: introduction to the special issue.

Authors:  W Tecumseh Fitch; Angela D Friederici; Peter Hagoort
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-07-19       Impact factor: 6.237

2.  Prolegomena to a neurocomputational architecture for human grammatical encoding and decoding.

Authors:  Gerard Kempen
Journal:  Neuroinformatics       Date:  2014-01

3.  Neuronal spike-rate adaptation supports working memory in language processing.

Authors:  Hartmut Fitz; Marvin Uhlmann; Dick van den Broek; Renato Duarte; Peter Hagoort; Karl Magnus Petersson
Journal:  Proc Natl Acad Sci U S A       Date:  2020-08-11       Impact factor: 11.205

4.  Disruption of hierarchical predictive coding during sleep.

Authors:  Melanie Strauss; Jacobo D Sitt; Jean-Remi King; Maxime Elbaz; Leila Azizi; Marco Buiatti; Lionel Naccache; Virginie van Wassenhove; Stanislas Dehaene
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-03       Impact factor: 11.205

Review 5.  Artificial grammar learning meets formal language theory: an overview.

Authors:  W Tecumseh Fitch; Angela D Friederici
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-07-19       Impact factor: 6.237

6.  Metrical presentation boosts implicit learning of artificial grammar.

Authors:  Tatiana Selchenkova; Clément François; Daniele Schön; Alexandra Corneyllie; Fabien Perrin; Barbara Tillmann
Journal:  PLoS One       Date:  2014-11-05       Impact factor: 3.240

7.  Sleep promotes the extraction of grammatical rules.

Authors:  Ingrid L C Nieuwenhuis; Vasiliki Folia; Christian Forkstam; Ole Jensen; Karl Magnus Petersson
Journal:  PLoS One       Date:  2013-06-05       Impact factor: 3.240

8.  MUC (Memory, Unification, Control) and beyond.

Authors:  Peter Hagoort
Journal:  Front Psychol       Date:  2013-07-12

9.  Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

Authors:  Vasiliki Folia; Karl Magnus Petersson
Journal:  Front Psychol       Date:  2014-02-04

10.  Auditory artificial grammar learning in macaque and marmoset monkeys.

Authors:  Benjamin Wilson; Heather Slater; Yukiko Kikuchi; Alice E Milne; William D Marslen-Wilson; Kenny Smith; Christopher I Petkov
Journal:  J Neurosci       Date:  2013-11-27       Impact factor: 6.167

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