4.5 Article

Item-specific and generalization effects on brain activation when learning Chinese characters

Journal

NEUROPSYCHOLOGIA
Volume 46, Issue 7, Pages 1864-1876

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neuropsychologia.2007.09.010

Keywords

lexical; training; transfer; fMRI; Chinese; radical

Funding

  1. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [R01HD042049] Funding Source: NIH RePORTER
  2. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH &HUMAN DEVELOPMENT [R56HD042049] Funding Source: NIH RePORTER
  3. NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS [R21DC006149] Funding Source: NIH RePORTER
  4. NICHD NIH HHS [R01 HD042049, R01 HD042049-05A2, HD042049, R56 HD042049] Funding Source: Medline
  5. NIDCD NIH HHS [R21 DC006149, DC06149] Funding Source: Medline

Ask authors/readers for more resources

Neural changes related to learning of the meaning of Chinese characters in English speakers were examined using functional magnetic resonance imaging (fMRI). We examined item specific learning effects for trained characters, but also the generalization of semantic knowledge to novel transfer characters that shared a semantic radical (part of a character that gives a clue to word meaning, e.g. water for lake) with trained characters. Behavioral results show that acquired semantic knowledge improves performance for both trained and transfer characters. Neuroimaging results show that the left fusiform gyrus plays a central role in the visual processing of orthographic information in characters. The left superior parietal cortex seems to play a crucial role in learning the visual-spatial aspects of the characters because it shows learning related decreases for trained characters, is correlated with behavioral improvement from early to late in learning for the trained characters, and is correlated with better longterm retention for the transfer characters. The inferior frontal gyrus seems to be associated with the efficiency of retrieving and manipulating semantic representations because there are learning related decreases for trained characters and this decrease is correlated with greater behavioral improvement from early to late in learning. (c) 2007 Published by Elsevier Ltd.

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