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

Abstract

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.

Keywords: Chinese; connectionist model; fMRI; stimulus correlation approach; visual word reading.

FIGURE 1

The contrasts of Real > NN (A) and Pseudo > NN (B) showed a similar neural network for lexical decision (LD) task. The conjunction map (C) showed pseudo-characters activated more regions at right hemisphere and more spatial extending regions at left hemisphere than real characters.

FIGURE 2

Brain areas showing a significant correlation between neural activity and reaction time in LD task, frequency, consistency degree, and stroke numbers.

FIGURE 3

Map of nine ROIs (A) identified from correlation analysis, with bar graphs (B) illustrating patterns of percent signal change for four types of pseudo-characters.

FIGURE 4

Brain map (A) of conjunction analysis on inferior frontal cortex correlated to frequency (blue), consistency (red) and both (yellow), with the bar graphs (B) illustrating patterns of percent signal change for four types of pseudo-characters.