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Simple Search
Hits 1 – 7 of 7
1
Implicit acquisition of grammars with crossed and nested non-adjacent dependencies: investigating the push-down stack model
Hagoort, Peter
;
Petersson, Karl Magnus
;
Ingvar, Martin
...
In:
Cognitive science. - Hoboken, NJ : Wiley-Blackwell
36 (2012) 6, 1078-1101
BLLDB
OLC Linguistik
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2
What artificial grammar learning reveals about the neurobiology of syntax
Folia, Vasiliki
;
Petersson, Karl Magnus
;
Hagoort, Peter
In:
Brain & language. - Orlando, Fla. [u.a.] : Elsevier
120 (2012) 2, 83-95
BLLDB
OLC Linguistik
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3
Shared Syntax in Language Production and Language Comprehension—An fMRI Study
Segaert, Katrien
;
Menenti, Laura
;
Weber, Kirsten
. - : Oxford University Press, 2012
BASE
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4
The neurobiology of syntax: beyond string sets
Hagoort, Peter
;
Petersson, Karl Magnus
. - : Royal Soc, 2012
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. ; Max Planck Institute for Psycholinguistics; Donders Institute for Brain, Cognition and Behaviour; Fundacao para a Ciencia e Tecnologia (IBB/CBME, LA, FEDER/POCI) [PTDC/PSI-PCO/110734/2009]; Vetenskapsradet ; info:eu-repo/semantics/publishedVersion
Keyword:
Analog
;
Artificial grammar
;
Brain
;
Brocas region
;
Comprehension
;
Dynamical-systems
;
Embedded english sentences
;
Functional Mri
;
Human language
;
Working-memory
URL:
http://hdl.handle.net/10400.1/11792
https://doi.org/10.1098/rstb.2012.0101
BASE
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5
Implicit acquisition of grammars with crossed and nested non-adjacent dependencies: investigating the push-down stack model
Udden, Julia
;
Ingvar, Martin
;
Hagoort, Peter
. - : Wiley-Blackwell, 2012
BASE
Show details
6
From Reference to Sense: How the Brain Encodes Meaning for Speaking
Menenti, Laura
;
Petersson, Karl Magnus
;
Hagoort, Peter
. - : Frontiers Research Foundation, 2012
BASE
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7
The neurobiology of syntax: beyond string sets
Petersson, Karl Magnus
;
Hagoort, Peter
. - : The Royal Society, 2012
BASE
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