Orthographic transparency modulates the functional asymmetry in the fusiform cortex: An artificial language training study

Leilei Mei,Gui Xue,Zhong-Lin Lu,Qinghua He,Mingxia Zhang,Feng Xue,Chuansheng Chen,Qi Dong

doi:10.1016/j.bandl.2012.01.006

Abstract

The laterality difference in the occipitotemporal region between Chinese (bilaterality) and alphabetic languages (left laterality) has been attributed to their difference in visual appearance. However, these languages also differ in orthographic transparency. To disentangle the effect of orthographic transparency from visual appearance, we trained subjects to read the same artificial script either as an alphabetic (i.e., transparent orthography) or a logographic (i.e., nontransparent orthography) language. Consistent with our previous results, both types of phonological training enhanced activations in the left fusiform gyrus. More interestingly, the laterality in the fusiform gyrus (especially the posterior region) was modulated by the orthographic transparency of the artificial script (more left-lateralized activation after alphabetic training than after logographic training). These results provide an alternative account (i.e., orthographic transparency) for the laterality difference between Chinese and alphabetic languages, and may have important implications for the role of the fusiform in reading.

Highlights

A longstanding question in the neurobiology of language is whether there are specific neural networks for different language systems (e.g., Chen, Xue, Mei, Chen, & Dong, 2009; Paulesu, Démonet, et al, 2001; Paulesu, McCrory, et al, 2000; Siok, Perfetti, Jin, & Tan, 2004; Tan, Laird, Li, & Fox, 2005)
Using an artificial language training paradigm, the present study examined the effect of orthographic transparency on the laterality of the subregions in the fusiform gyrus
Consistent with one previous study (Xue et al, 2006b), we found that phonological training resulted in increased activations in the fusiform gyrus

Summary

Introduction

A longstanding question in the neurobiology of language is whether there are specific neural networks for different language systems (e.g., Chen, Xue, Mei, Chen, & Dong, 2009; Paulesu, Démonet, et al, 2001; Paulesu, McCrory, et al, 2000; Siok, Perfetti, Jin, & Tan, 2004; Tan, Laird, Li, & Fox, 2005). Chinese characters possess a number of intricate strokes that are packed into a square shape, whereas alphabetic languages have linear combinations of letters. Based on this difference, researchers have hypothesized that, compared with alphabetic languages, reading Chinese characters might involve more visuospatial analysis, and recruit more regions in the right hemisphere (Liu, Dunlap, Fiez, & Perfetti, 2007; Tan et al, 2000).

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Results

Conclusion