Task by stimulus interactions in brain responses during Chinese character processing

Yang, Jianfeng; Wang, Xiaojuan; Shu, Hua; Zevin, Jason D.

doi:10.1016/j.neuroimage.2012.01.036

Cited by 19 publications

(18 citation statements)

References 69 publications

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“…On the other hand, we show here that MFG activity is strongly modulated by task (see also BOOTH, etc.). Analysis of effects of stimulus class [ 19 ] shows that activity in the MFG tracks with behavioral measures of difficulty during LDT. Notably, stimulus effects are not observed in MFG for the same stimuli in a one-back task [ 22 ], which arguably puts an even greater premium on visual processing, but requires less in the way of meta-linguistic decision-making.…”

Section: Discussionmentioning

confidence: 99%

“…That activity is restricted to the LD task is not surprising, given the insula’s role in error monitoring [ 45 , 46 ], and the language difference may be explained in terms of the lower overall accuracy in the Chinese behavioral data. Yang et al [ 19 ] and Yang & Zevin [ 64 ] further showed that insula activity to conditions with the lowest accuracy in the lexical decision task in both languages. This is a perfect example of a region that behaves very differently under artificial task conditions and naturalistic reading.…”

Section: Discussionmentioning

confidence: 99%

“…Data from the lexical decision experiment in Chinese are taken from a study that also included a symbol detection task, and revealed task by stimulus interactions in this population [ 19 ], and data from the English lexical decision experiment are taken from a parallel study [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

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Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

Wang

Yang

et al. 2015

PLoS ONE

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Differences in how writing systems represent language raise important questions about whether there could be a universal functional architecture for reading across languages. In order to study potential language differences in the neural networks that support reading skill, we collected fMRI data from readers of alphabetic (English) and morpho-syllabic (Chinese) writing systems during two reading tasks. In one, participants read short stories under conditions that approximate natural reading, and in the other, participants decided whether individual stimuli were real words or not. Prior work comparing these two writing systems has overwhelmingly used meta-linguistic tasks, generally supporting the conclusion that the reading system is organized differently for skilled readers of Chinese and English. We observed that language differences in the reading network were greatly dependent on task. In lexical decision, a pattern consistent with prior research was observed in which the Middle Frontal Gyrus (MFG) and right Fusiform Gyrus (rFFG) were more active for Chinese than for English, whereas the posterior temporal sulcus was more active for English than for Chinese. We found a very different pattern of language effects in a naturalistic reading paradigm, during which significant differences were only observed in visual regions not typically considered specific to the reading network, and the middle temporal gyrus, which is thought to be important for direct mapping of orthography to semantics. Indeed, in areas that are often discussed as supporting distinct cognitive or linguistic functions between the two languages, we observed interaction. Specifically, language differences were most pronounced in MFG and rFFG during the lexical decision task, whereas no language differences were observed in these areas during silent reading of text for comprehension.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

Wang

Yang

et al. 2015

PLoS ONE

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“…Among these studies, bottom-up factors have been mainly manipulated by comparing the activation patterns induced by different types of visual input ranging from checkerboards, objects, symbols, sequences of characters, pseudowords to real words (Carreiras et al, 2007;Twomey et al, 2011;Yang et al, 2012). As described below, the present study adopted a different approach that consisted in manipulating the bottom-up information while using only written words, i.e., visual stimuli that can potentially lead to the activation of orthographic, phonological and semantic information.…”

Section: Introductionmentioning

confidence: 99%

Automaticity of phonological and semantic processing during visual word recognition

Pattamadilok

Chanoine²,

Pallier

et al. 2017

NeuroImage

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A B S T R A C TReading involves activation of phonological and semantic knowledge. Yet, the automaticity of the activation of these representations remains subject to debate. The present study addressed this issue by examining how different brain areas involved in language processing responded to a manipulation of bottom-up (level of visibility) and top-down information (task demands) applied to written words. The analyses showed that the same brain areas were activated in response to written words whether the task was symbol detection, rime detection, or semantic judgment. This network included posterior, temporal and prefrontal regions, which clearly suggests the involvement of orthographic, semantic and phonological/articulatory processing in all tasks. However, we also found interactions between task and stimulus visibility, which reflected the fact that the strength of the neural responses to written words in several high-level language areas varied across tasks. Together, our findings suggest that the involvement of phonological and semantic processing in reading is supported by two complementary mechanisms. First, an automatic mechanism that results from a taskindependent spread of activation throughout a network in which orthography is linked to phonology and semantics. Second, a mechanism that further fine-tunes the sensitivity of high-level language areas to the sensory input in a task-dependent manner.

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“…Furthermore, the neural network of character reading is more uncertain when considering the language differences. Although, pSTG was consistently active for O-P processing in alphabetic word reading ( Paulesu et al, 2000 ), it was null or deactivated for Chinese character either in naming ( Tan et al, 2001a ) or lexical decision (LD) task ( Yang et al, 2012 ), whereas, it was active in Chinese during continuous reading ( Wang et al, 2015 ) and semantic judgment tasks ( Rueckl et al, 2015 ). That is, the task demands might influence the previous findings of the Chinese reading network.…”

Section: Introductionmentioning

confidence: 99%

The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading

et al. 2016

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Visual word recognition involves mappings among orthographic, phonological, and semantic codes. In alphabetic languages, it is hard to disentangle the effects of these codes, because orthographically well-formed words are typically pronounceable, confounding orthographic and phonological processes, and orthographic cues to meaning are rare, and where they occur are morphological, confounding orthographic and semantic processes. In Chinese character recognition, it is possible to explore orthography to phonology (O-P) and orthography to semantics (O-S) processes independently by taking advantage of the distinct phonetic and semantic components in Chinese phonograms. We analyzed data from an fMRI experiment using lexical decision for Chinese characters to explore the sensitivity of areas associated with character recognition to orthographic, phonological, and semantic processing. First, a correlation approach was used to identify regions associated with reaction time, frequency, consistency and visual complexity. Then, these ROIs were examined for their responses to stimuli with different types of information available. These results revealed two neural pathways, one for O-S processing relying on left middle temporal gyrus and angular gyrus, and the other for O-P processing relying on inferior frontal gyrus and insula. The two neural routes form a shared neural network both for real and pseudo-characters, and their cooperative division of labor reflects the neural basis for processing different types of characters. Results are broadly consistent with findings from alphabetic languages, as predicted by reading models that assume the same general architecture for logographic and alphabetic scripts.

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Task by stimulus interactions in brain responses during Chinese character processing

Cited by 19 publications

References 69 publications

Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

Automaticity of phonological and semantic processing during visual word recognition

The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading

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