2009
DOI: 10.1016/j.neuroimage.2009.06.078
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Hierarchical coding of characters in the ventral and dorsal visual streams of Chinese language processing

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Cited by 22 publications
(20 citation statements)
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“…This result confirmed that Chinese participants could at least partially recognize the French words that were presented. In addition, contrasting French words versus nonwords revealed activations in the anterior parts of the VWFA of French participants (MNI: −39 −39 −21, Z = 4.24; below extent threshold), but not in Chinese participants, suggestive of French participantsʼ having a more developed sensitivity to their native language orthographic structure in ventral occipitotemporal regions (Mano et al, 2013;Chan et al, 2009;Vinckier et al, 2007;Binder, Medler, Westbury, Liebenthal, & Buchanan, 2006;Dehaene, Cohen, Sigman, & Vinckier, 2005).…”
Section: Activations To French Nonwordsmentioning
confidence: 87%
See 1 more Smart Citation
“…This result confirmed that Chinese participants could at least partially recognize the French words that were presented. In addition, contrasting French words versus nonwords revealed activations in the anterior parts of the VWFA of French participants (MNI: −39 −39 −21, Z = 4.24; below extent threshold), but not in Chinese participants, suggestive of French participantsʼ having a more developed sensitivity to their native language orthographic structure in ventral occipitotemporal regions (Mano et al, 2013;Chan et al, 2009;Vinckier et al, 2007;Binder, Medler, Westbury, Liebenthal, & Buchanan, 2006;Dehaene, Cohen, Sigman, & Vinckier, 2005).…”
Section: Activations To French Nonwordsmentioning
confidence: 87%
“…Finally, we explored the differences between the neural networks, which the two participant groups used when reading in their native script ( Figure 7C; see Nakamura et al, 2012;Wu et al, 2012;Perfetti et al, 2010;Chan et al, 2009;Chen et al, 2009;Wong, Jobard, James, James, & Gauthier, 2009;Bolger et al, 2005;Tan et al, 2005). Stronger activations in Chinese readers reading Chinese relative to French reading French were found in the lefthemisphere fusiform (MNI: −39 −63 −21, Z = 3.83) and intermediate visual areas (MNI: −39 −81 −6, Z = 4.81) and in the left inferior parietal sulcus (MNI: −27 −57 36, Z = 4.24).…”
Section: Comparisons Between French and Chinese Participantsmentioning
confidence: 99%
“…Instead, it could be due to the fact that visual processing of words and characters provides output to linguistic processing and writing. As an interface for communication with other modalities, orthographic representations comprising multiple letters or components or even a whole word or character could be the entry point of recognition of text, leading to obligatory attention to multiple components of a word or character (Chan et al, 2009;Dehaene, Cohen, Sigman, & Vinckier, 2005;.…”
Section: Discussionmentioning
confidence: 99%
“…Orthographic processing in Chinese is considered to involve visuospatial analysis of characters and application of a set of orthographic rules (e.g., radical position, orthographic legality) to help with character identification. Tasks in this category included orthographic judgment (whether a visually presented item was orthographically legal or illegal, e.g., (Dong et al, 2005)), stroke analysis (counting the number of a designated stroke within each presented character, e.g., (Chan et al, 2007)), orthographic search (whether the character contained a designated radical component, e.g., (Ding et al, 2003)), physical identical judgment (whether two characters or pseudo-characters presented in one trial were identical, e.g., (Chan et al, 2009;Wang et al, 2011;Zhao et al, 2010)), and font size judgment (whether the size of stimuli was small or large, e.g., (Liu et al, 2008)). …”
Section: Task Categorizationmentioning
confidence: 99%
“…Semantic processing evokes retrieval and analysis of meaning components of stimuli at the character-, word-, or sentence-level given the input orthography. Tasks included in this category covered character-level semantic decision judgment (whether two characters were semantically related, e.g., (Chan et al, 2009;Chou et al, 2009;Tan et al, 2001b), or selecting one character from two that was closest in meaning to the target character, e.g., (Chee et al, 2001)), word-level semantic association judgment (whether two words were semantically related to each other, e.g., (Dong et al, 2005;), or whether a probe word was semantically related to either of the two target words, e.g., (Booth et al, 2006;Cao et al, 2009;Xiang et al, 2003)), word semantic judgment (whether the presented item was semantically dangerous, e.g., , or whether the item was a type of animal, e.g., (Ding et al, 2003)), semantic knowledge judgment (answering yes/no semantic knowledge questions about visual attributes of living and non-living things, e.g., (Mo et al, 2005)), phrase/sentence semantic judgment (whether a presented phrase/ sentence was semantically acceptable, e.g., (Luke et al, 2002;Zhu et al, 2009)), and semantic generation task (generating a word that was semantically related to the stimulus, e.g., ).…”
Section: Task Categorizationmentioning
confidence: 99%