The role of working memory in artificial grammar learning

2009 ◽  
Author(s):  
Michelle A. Hendricks ◽  
Christopher M. Conway ◽  
Ronald T. Kellogg
Keyword(s):  
Working Memory ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

scholarly journals The Role of Anti-harmony in Learning Neutral Vowels

2019 ◽  
Vol 7 ◽  
Author(s):  
Sara Finley
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Vowel Harmony ◽  
Front Vowel ◽  
Learning Paradigm ◽  
Grammar Learning ◽  
Back Vowel

The present study used an artificial grammar learning paradigm to explore the prediction that exposure to anti-harmony might help learners infer that a neutral vowel in a vowel harmony language is transparent. Participants were exposed to a back/round harmony language with a neutral vowel [a]. This neutral vowel either always selected a back vowel suffix,  always selected a front vowel suffix, or selected both front-and back vowel suffixes, in adherence to anti-harmony. Results indicated that exposure to a back/round harmony with the neutral vowel selecting either back vowel suffixes, or both front and back vowel suffixes, could induce a bias towards transparent vowels. Assuming that participants inferred that the centralized [a] paired with [o] harmonically, then the predictions that exposure to anti-harmony could induce a bias towards a transparent vowel interpretation were borne out. However, the bias towards a transparent vowel was not significantly different between the anti-harmony conditions and the harmony condition, suggesting that this effect should be replicated with other neutral vowels.

scholarly journals Electrical Stimulation of Broca's Area Enhances Implicit Learning of an Artificial Grammar

2010 ◽  
Vol 22 (11) ◽  
pp. 2427-2436 ◽  
Author(s):  
Meinou H. de Vries ◽  
Andre C. R. Barth ◽  
Sandra Maiworm ◽  
Stefan Knecht ◽  
Pienie Zwitserlood ◽  
...  
Keyword(s):  
Working Memory ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Acquisition Phase ◽  
Natural Setting ◽  
Broca’S Area ◽  
Anodal Tdcs ◽  
Broca's Area ◽  
Grammatical Knowledge ◽  
Grammar Learning

Artificial grammar learning constitutes a well-established model for the acquisition of grammatical knowledge in a natural setting. Previous neuroimaging studies demonstrated that Broca's area (left BA 44/45) is similarly activated by natural syntactic processing and artificial grammar learning. The current study was conducted to investigate the causal relationship between Broca's area and learning of an artificial grammar by means of transcranial direct current stimulation (tDCS). Thirty-eight healthy subjects participated in a between-subject design, with either anodal tDCS (20 min, 1 mA) or sham stimulation, over Broca's area during the acquisition of an artificial grammar. Performance during the acquisition phase, presented as a working memory task, was comparable between groups. In the subsequent classification task, detecting syntactic violations, and specifically, those where no cues to superficial similarity were available, improved significantly after anodal tDCS, resulting in an overall better performance. A control experiment where 10 subjects received anodal tDCS over an area unrelated to artificial grammar learning further supported the specificity of these effects to Broca's area. We conclude that Broca's area is specifically involved in rule-based knowledge, and here, in an improved ability to detect syntactic violations. The results cannot be explained by better tDCS-induced working memory performance during the acquisition phase. This is the first study that demonstrates that tDCS may facilitate acquisition of grammatical knowledge, a finding of potential interest for rehabilitation of aphasia.

The Role of Simple Semantics in the Process of Artificial Grammar Learning

2017 ◽  
Vol 46 (5) ◽  
pp. 1285-1308
Author(s):  
Birgit Öttl ◽  
Gerhard Jäger ◽  
Barbara Kaup
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

scholarly journals Role of selective attention in artificial grammar learning

2008 ◽  
Vol 15 (6) ◽  
pp. 1154-1159 ◽  
Author(s):  
Daisuke Tanaka ◽  
Sachiko Kiyokawa ◽  
Ayumi Yamada ◽  
Zoltán Dienes ◽  
Kazuo Shigemasu
Keyword(s):  
Selective Attention ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

Visual artificial grammar learning by rhesus macaques (Macaca mulatta): exploring the role of grammar complexity and sequence length

2018 ◽  
Vol 21 (2) ◽  
pp. 267-284 ◽  
Author(s):  
Lisa A. Heimbauer ◽  
Christopher M. Conway ◽  
Morten H. Christiansen ◽  
Michael J. Beran ◽  
Michael J. Owren
Keyword(s):  
Macaca Mulatta ◽  
Rhesus Macaques ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Sequence Length ◽  
Grammar Learning

Abstraction Processes in Artificial Grammar Learning

1997 ◽  
Vol 50 (1) ◽  
pp. 216-252 ◽  
Author(s):  
David R. Shanks ◽  
Theresa Johnstone ◽  
Leo Staggs
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning
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