BioMed Research International
Volume 2017 (2017), Article ID 5732642, 8 pages
https://doi.org/10.1155/2017/5732642

Research Article

Human Brain Mapping of Visual Script Familiarity between Phonological and Logographic Language: 3 T Functional MRI Study

Nambeom Kim,¹ Jongho Kim,² Chang-Ki Kang,1,3 Chan-A Park,⁴ Mi-Ra Lim,⁵ Young-Bo Kim,1,6 and Byung-Gee Bak⁷

¹Neuroscience Research Institute, Gachon University, Incheon, Republic of Korea
²Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
³Department of Radiological Science, College of Health Science, Gachon University, Incheon, Republic of Korea
⁴Bioimaging Research Team, Division of Bioconvergence Analysis, Korea Basic Science Institute, Ochang, Cheongju, Republic of Korea
⁵Department of General Education, Ajou University, Seoul, Republic of Korea
⁶Department of Neurosurgery, Gachon University Gil Hospital, Incheon, Republic of Korea
⁷Department of Education, Chonbuk National University, Jeonju, Republic of Korea

Correspondence should be addressed to Young-Bo Kim; neurokim@gachon.ac.kr and Byung-Gee Bak; bbak@jbnu.ac.kr

Received 10 January 2017; Revised 20 March 2017; Accepted 23 April 2017; Published 5 July 2017

Academic Editor: Nader Pouratian

Copyright © 2017 Nambeom Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Neurolinguistic circuitry for two different scripts of language, such as phonological scripts (PhonoS) versus logographic scripts (LogoS) (e.g., English versus Chinese, resp.), recruits segregated neural pathways according to orthographic regularity (OrthoR). The purpose of this study was to identify the effect of VSF for cortical representation according to different OrthoR to represent Hangul versus Hanja as PhonoS versus LogoS, respectively. A total of 24 right-handed, native Korean undergraduate students with the first language of PhonoS and the second language of LogoS were divided into high- or low-competent groups for L2 of LogoS. The implicit word reading task was performed using Hanja and Hangul scripts during functional magnetic resonance imaging (fMRI) acquisition. Fluctuations of fMRI BOLD signal demonstrated that the LogoS was associated with the ventral pathway, whereas PhonoS was associated with the dorsal pathway. By interaction analysis, compared with high-competent group, low-competent group showed significantly greater activation for Hanja than for Hangul reading in the right superior parietal lobule area and the left supplementary motor area, which might be due to neural efficiency such as attention and cognition rather than core neurolinguistic neural demand like OrthoR processing.

1. Introduction

Neurolinguistic circuitry for two different scripts of language, namely, phonological script (PhonoS) versus logographic script (LogoS) (e.g., English versus Chinese, resp.), recruits segregated neural pathways according to orthographic regularity (OrthoR) on human brain cortical mapping using functional magnetic resonance imaging (fMRI) [1, 2]. For example, reading PhonoS such as English, Japanese Kana, and Korean Hangul converts grapheme into phoneme as a type of assembled phonology, whereas reading LogoS such as Chinese, Japanese Kanji, and Korean Hanja only retrieves phonology from an internal lexicon as a type of addressed phonology [3, 4]. Neuroimaging studies revealed that PhonoS recruits the left dorsal pathway via the angular gyrus (AG) or supramarginal gyrus (SMG) and involves the ventrolateral prefrontal cortex (VLPFC) and the lower part of Broca’s area. On the other hand, LogoS recruits the left ventral pathway via the inferior medial temporal lobe involving the fusiform gyrus (FG) and the pars triangularis/pars opercularis [5–8].

Given the better understanding of neurolinguistic circuitry of PhonoS versus LogoS as depicted with fMRI study, further work investigated whether learning the second language (L2) is related to assimilation versus accommodation with respect to native first language circuitry (L1) [9–12]. Brain areas for L2 stimuli that overlap with those for L1 may be secondary to assimilating or accommodating the new writing system [13]. In this regard, it is very important to stabilize substantial cortical mapping across each script and eliminate many other confounding variables to recruit neural demands. Given neural demands and efficiency as the main determinant on cortical mapping, visual script familiarity (VSF) needs to be considered since it affects not only cortical representation [14–16] but also performance of verbal tasks, for example, picture naming [17], lexical decision-making [18], and visual word recognition [19].

Along with different OrthoR, the spatial pattern between scripts affects cortical activation on neurolinguistic fMRI and Korean script system provides an excellent opportunity to identify the effect of VSF given that the pair of Korean Hangul and Hanja has a unique property of very similar spatial pattern. Meta-analysis demonstrated different visual word form area (VWFA) of peak response and amplitude between LogoS of Chinese and PhonoS of the alphabetic script [20]. However, the Hangul was packaged into “square” units of several phonemes, representing a syllable, with the same visual appearance as Hanja and showed no significant difference of within-subject design of early Chinese-Korean bilinguals between LogoS of Chinese and PhonoS of Korean [21]. Also, because of the government policy, the younger Korean generation was exposed to the Hanja beginning in middle school, which leads to control of the age of language acquisition, consequently, to avoid potential confounders inducing different neural activation [12, 22].

Hence, the purpose of this study was to identify the extent and degree of which VSF affects cortical representation for Hangul versus Hanja as PhonoS versus LogoS, respectively, given different OrthoR. The native Koreans with a first language (L1) of PhonoS and a second language (L2) of LogoS were divided into high-competent (High-C) versus low-competent (Low-C) groups for L2 of LogoS. We hypothesized that the relative higher activation in Low-C group, if any, could more likely be due to neural efficiency such as attention and cognition rather than core neurolinguistic neural demand. The whole brain cortical topology of VSF effect could provide a platform on language processing such as in bilingualism using assimilation versus accommodation between L1 and L2 languages.

2. Materials and Methods

2.1. Participants

A total of 24 right-handed, native Korean undergraduate students at a local university participated in the fMRI study. The participants were divided into two groups, those familiar with Hanja (High-C group, mean years, , ) and those not familiar with Hanja (Low-C group, mean years, , ). All participants learned Hangul as the native language and were familiar with the script. Written consent was obtained from all subjects and the protocol was approved by the Institutional Review Board of Gachon Medical Center. The inclusion criteria for High-C group were subjects having a Hanja certificate above level 2 (high level) awarded by the Korean Association for the Promotion of Hanja Education (KAPHE) and reported daily experience with writing or reading Hanja at least for two recent years before the experiment.

2.2. fMRI Paradigm

The fMRI experiment had a block design consisting of Hanja and Hangul trials that were randomly intermixed across the run [5, 6]. A total of 150 two-letter Hanja words were chosen based on KAPHE guidelines for level 5 (middle to low level). To match the Hanja words, a total of 150 of the most frequently used two-letter Hangul words were selected. A Hanja item (e.g., “市場” = market) or a Hangul item (e.g., “” = friend) was presented for 1 second within the block according to the trial. Each block had 30 items. Subjects were instructed to internally read the Hanja or Hangul word displayed on the screen without actual vocalization (implicit reading) during the fMRI scan. After finishing each block, a fixed cross was displayed for 30 seconds. The run order was randomized for each subject to eliminate systemic bias. One run consisted of 5 blocks and each participant performed two runs. The total duration of the experiment was approximately 30 minutes (Figure 1). After finishing the fMRI experiments, all participants were asked to disclose any Hanja scripts that they could not read during the fMRI task, and no one responded. The words were presented using a beam projector with an 8-inch screen and DMDX software (http://www.u.arizona.edu/~kforster/dmdx/dmdx.htm) [18].

Figure 1: LogoS and PhonoS used for the word reading experiment. LogoS words were selected based on level 5 proficiency guided by the KAPHE, which is equivalent to a middle school educational level in Korea. PhonoS words were chosen based on those most frequently used in daily life. Within each activation block, a word was displayed for 1 s. A total of 30 words were presented in each block.

2.3. MRI Procedure and Image Analysis

A 3 T whole-body Siemens scanner (Siemens, Magnetom Verio, Erlangen, Germany) was used for image acquisition with an interleaved T2-weighted EPI gradient-echo sequence ( ms/28 ms/90°, slice thickness = 3 mm, in-plane  mm², 39 slices,  mm, and matrix ). Each subject’s anatomical image was acquired using a high-resolution ( mm³), T1-weighted, 3D gradient-echo pulse sequence (MPRAGE;  ms/2.93 ms/900 ms). fMRI images were analyzed using statistical parametric mapping (SPM 8) (Wellcome Department of Cognitive Neurology, London, UK) running under MATLAB 2008a (Mathworks, Sherborn, MA, USA).

The first five images were discarded from analysis to eliminate the nonequilibrium effects of magnetization. Functional volumes were realigned, coregistered to anatomical images, and normalized to the Montreal Neurological Institute (MNI) template using a transformation matrix acquired from the T1 anatomical image normalization based on the SPM T1 template. Finally, spatial smoothing was performed with an 8 mm full-width at the half-maximum Gaussian kernel. The resulting time-series was high-pass filtered with a cut-off time window of 128 s to remove low-frequency drift in the blood-oxygen level dependent (BOLD) signal. Then, the design matrix was temporally convolved with a canonical hemodynamic response function for a better fit.

A voxel-based general linear model was used at the single subject level to estimate the parameters associated with the conditions of interest (Hanja reading or Hangul reading versus fixed cross as a baseline) along with six motion parameters as covariates of no interest. With the parameters acquired from the first level analysis, a group level analysis was performed using a factorial design. Group results were estimated by comparing the parameter estimates acquired at the first level analysis. The two contrasts of interest were the main effect analysis used to identify cortical regions where the BOLD response increased during Hanja versus Hangul reading, due to the effect of the script, and the interaction effect analysis used to identify substantially different neural involvement modulated by Hanja script competency. The interaction analysis was confined to the regions with a positive response for Hanja reading compared to Hangul reading at uncorrected (t-contrast) to exclude deactivated voxels. Because our primary interest was the regions representing positive responses for Hanja reading compared to Hangul reading and based on combined intensity and cluster size thresholds for the complex cognitive and affective processes which have small effect size, the significance threshold for the main effect and the interaction effect was set at uncorrected and uncorrected , respectively (assuming independence, joint probability of type I is , approximately 0.001) with a spatial extent larger than 50 voxels [23, 24]. xjView toolbox (http://www.alivelearn.net/xjview) and automated anatomical labeling (http://www.gin.cnrs.fr/AAL) were used to display the statistical results and report anatomical locations of peak -values.

3. Results and Discussion

3.1. The Main Effect of Cortical Representation of Orthographic Regularity

The main effect analysis of script showed increased cortical activation in both High-C and Low-C () groups at the threshold of uncorrected with a cluster size of 50 voxels. The cortical areas with significantly greater activation for reading Hanja than Hangul reading included the bilateral FG, right inferior temporal gyrus, and corresponding dorsal stream extending to the bilateral superior parietal lobule (SPL), bilateral inferior precentral gyrus (IPcG, left > right), bilateral insula, and supplementary motor area (SMA). In addition to cortical regions, two clusters yielded activation in bilateral cerebellar region 6 (right > left). Significantly greater activation for Hangul than for Hanja reading was observed in the left anterior temporal, AG (left ≫ right)/SMG (left ≫ right), bilateral dorsomedial prefrontal cortex (DMPFC, left > right), left VLPFC, and precuneus (Table 1 and Figure 2).

Table 1: BOLD activation for LogoS versus PhonoS reading ().

Contrast
Region
BA
Cluster size

score

LogoS > PhonoS
Fusiform_L
37
518
−32
−58
−18
5.68

Occipital_Mid_L
19
589
−32
−88
16
5.17

Parietal_Sup_L
7
934
−28
−60
48
5.35

Precentral_L
9
789
−44
2
32
5.37

Insula_L
13
618
−32
18
12
4.62

Precentral_L
6
113
−28
−6
54
3.80

Supp_Motor_Area_L
6
334
−8
4
62
4.15

Fusiform_R
37
514
34
−52
−16
5.13

Temporal_Inf_R
37
227
48
−66
−12
5.13

Parietal_Sup_R
7
890
26
−66
50
4.62

Insula_R
13
576
34
22
6
4.55

Precentral_R
9
255
44
4
32
4.95

Cllm_6_L

160
−32
−54
−24
5.68

Cllm _6_R

682
32
−62
−26
5.13

PhonoS > LogoS
Occipital_Mid_L
39
1746
−44
−76
32
4.74

Temporal_Mid_L
21, 38
797
−50
4
−34
4.34

Frontal_Sup_L
8, 9, 10
2048
−28
34
36
5.16

Frontal_Inf_Orb_L
11
536
−50
36
−16
4.74

Cingulum_Mid_L
24
167
0
−18
42
4.11

Temporal_Mid_R
21
554
56
−64
20
4.34

Temporal_Inf_R
20, 21
99
62
−26
−18
3.60

Paracentral_Lobule_R
5
1140
2
−44
66
4.21

Frontal_Sup_R
8
282
24
30
52
3.89

Precuneus_R
31
53
12
−42
44
3.59

Cllm _Crus2_L

113
−44
−78
−48
4.23

Cllm _Crus2_R

563
30
−92
−38
5.21

Cllm _9_R

59
8
−58
−64
3.70

(a)

(b)

Figure 2: Main effect analysis of script (LogoS versus PhonoS reading) for all subjects (). Red color represents greater BOLD signal for LogoS than for PhonoS reading. Green color represents greater BOLD signal for PhonoS than for LogoS reading. In the 3D rendered image, significantly greater activation for LogoS than for PhonoS reading was observed bilaterally in the inferior occipital/temporal and corresponding dorsal stream extending to the SPL. In comparison, significantly greater activation for PhonoS than for LogoS reading was observed in the bilateral anterior to mid-temporal cortices and the DMPFC (left predominant) (a). T-maps overlaid on sliced images clearly showed that both the FG and insular cortex were more activated for LogoS than for PhonoS reading and the precuneus was more activated for PhonoS than for LogoS reading (b) (uncorrected , ).

Different script systems recruit a different cortical involvement during reading written word depending on their OrthoR [25], supported by functional neuroimaging, lesion-based [26, 27], and electrical stimulation studies [28, 29]. The current study confirmed that LogoS was associated with a greater increase in BOLD response in the ventral pathway including the bilateral FG extending to the SPL whereas the dorsal pathway including the AG, SMG, and VLPFC was more activated for PhonoS which is in line with the previous studies except for greater activation in the right SPL extending to the right mid-occipital cortex and right inferior prefrontal cortex as well as left SMA, a similar pattern shown in an illustrative study with the Korean scripts [6].

3.2. The Interaction Effect of Cortical Representation of Visual Script Familiarity

The analysis of the interaction effect showed substantially different cortical activation depending on Hanja competency at the threshold of approximately uncorrected with a cluster size of 50 voxels. Significant greater activation for Hanja than for Hangul reading in the Low-C compared with High-C group occurred in the right SPL, SMA, right VLPFC, and dorsolateral prefrontal cortex. In comparison, areas showing significant greater activation for Hanja than Hangul reading in the High-C compared with Low-C group included the bilateral caudate (right ≫ left) (Table 2 and Figure 3).

Table 2: Interaction effect analysis of PhonoS versus LogoS and LogoS competency.

Contrast
Region
BA
Cluster size

score

LogoS-PhonoS in High-C > LogoS-PhonoS in Low-C
Caudate_R

82
12
16
10
2.99

Caudate_L

-6
10
8
2.40

LogoS-PhonoS in Low-C > LogoS-PhonoS High-C

Parietal_Sup_R
7
302
20
−64
48
2.62

Supp_Motor_Area_L
8
788
14
22
40
2.52

Frontal_Inf_Tri_R
46
64
52
24
28
2.03

Frontal_Sup_L
6
57
−22
−10
48
2.29

Frontal_Inf_Tri_L
47
60
−44
24
4
2.58

Figure 3: 3D surface rendered images of main effect analysis overlaid by the LogoS VSF difference between Low-C and High-C. The 3D rendered images showed the results of the main effect analysis of script overlaid by the greater activation in the Low-C than High-C for LogoS than for PhonoS reading. The overlaid surface rendered images clearly showed the right occipital cortex extending to the right SPL (red dotted circle, posterior and superior view) and right VLPFC (red arrow, superior view) including the SMA (blue dotted circle, superior view) were predominant in the Low-C (uncorrected , ).

Regarding OrthoR, the pairs of Korean Hangul (PhonoS) and Hanja (LogoS) are similar to the pairs of Japanese Kana and Kanji while the Korean writing system has an interestingly unique property. The spatial pattern between Hangul and Hanja script is very similar. Unlike the letters of the Latin alphabet, the Hangul is packaged into “square” units of subsyllable, each of which transcribes a syllable. It is actually composed of several consonant and vowel letters with the form of left to right or from top to down direction. The spatial features of Hanja have geometrical relationship between radicals, which is similar to that of Hangul [4, 6, 21]. The spatial pattern between scripts is essential in brain mapping. fMRI study showed that the anatomical location of neural involvement could be influenced by not only OrthoR but also the spatial pattern between scripts. The authors showed Chinese and English script to Chinese-English bilinguals who were native Chinese speakers fluent in English and English learners of Chinese and showed a location difference of peak response in visual word form area (VWFA) between Chinese and an alphabetic characters such as English [20]. However, evaluating early Chinese-Korean bilinguals using a within-subject design, they reported no significant difference in the location of peak response and amplitude in VWFA between Chinese and Korean script [21].

Additionally, controlling the age at which language acquisition induces different neural activation is needed. Regarding the age of acquisition, a spatially segregated region was found activated in Broca’s area but not Wernicke’s area in late L2 learners during L1 and L2 reading, whereas this phenomenon was not observed in early L2 learners; they shared a substantially overlapped region (both Broca’s area and Wernicke’s area) during L1 and L2 reading [12]. Another study also reported the influence of age in L2 exposure and showed increased variability of local brain activity in late L2 exposure [22].

Since the 14th century, Hangul (PhonoS) and Hanja (LogoS) have been the two basic scripts used in Korea, often combined for the purpose of better communication while Hangul and Hanja represent shallow and deep OrthoR, respectively. Also, because of the government policy, younger Korean generation currently is being exposed to Hanja starting in middle school, which leads to control of the age of language acquisition, consequently avoiding the potential confounder inducing different neural activation [12, 22].

To delineate the effect of VSF on the cortical representation, an implicit word reading task was performed for Hangul and Hanja in the subjects with L1 as Hangul divided into High-C versus Low-C group during fMRI acquisition. Compared with High-C group, Low-C group showed greater involvement of the right hemisphere including the right SPL, left SMA, and right IPcG during Hanja compared to Hangul reading. Given Low-C group less proficient in Hanja, the areas of greater activation in the Low-C might not be due to intrinsic linguistic processing such as OrthoR but increased demand for attention and cognition such as VSF [30]. VSF is one of the most influential factors affecting speed, the accuracy of visual word recognition [31, 32], and cortical representation [15, 16, 19, 33] as well as performance on verbal tasks such as picture naming [17] and lexical decision-making [18].

While phonological awareness is closely related to reading and learning PhonoS such as English, due to visual-spatial complexity, visuospatial processing is crucial for reading in LogoS (e.g., Chinese, Korean Hanja) [34]. Several previous studies have suggested that visual skills are more predictive of acquisition and reading in LogoS than PhonoS such as English. A cross-cultural study that examined phonological awareness, visual skills, and reading ability in British, Taiwanese, and Hong Kong children showed that visual skills were significantly related to the reading ability in both Taiwanese and Hong Kong children but not British children, suggestive of clear advantage on the visuospatial skill in reading LogoS [35–37].

The experimental studies suggested that the right parietal cortex has an important role in visuospatial processing such as visuospatial attention and mental rotation of an object in space [38]. In a parametric design with PET, gradually rotated character stimuli from 10% to 70% degree were shown to the participants and the participant were asked to decide whether each stimulus was normal or mirrored. It was demonstrated that the degree of cortical activation in right SPL is incrementally associated with increase of rotational degree of the stimuli [39]. Consistent with other findings, a study comparing patients with right parietal lobe lesions with left and matched normal controls demonstrated that the patient with right parietal lesion revealed low accuracy and delayed response time in constructing mental image rotation task, suggesting the specialization of right SPL in visuospatial processing [40, 41]. Taken together, visual property of the LogoS might cause the Low-C group to require an increase in cognitive demand for spatial processing during LogoS recognition [42, 43]. The SMA is mainly involved in the speech-motor preparation and execution components of reading in a less proficient language. So greater activation in the SMA in the Low-C group might have been due to increased cognitive demand during speech-motor preparation in subjects less proficient in LogoS [44]. In summary, the Low-C group might have required greater cognitive resources for the processing of visuospatial analysis and phonological retrieval by those less practiced and less proficient scripts than the High-C group, which consequently resulted in greater right hemisphere lateralization in the Low-C group. Delineation of neural circuitry concerning VSF on different scripts could be extended to the cortical mapping of acquisition and processing between L1 and L2 languages in bilingualism.

4. Conclusions

For cortical mapping to represent Hangul (PhonoS) versus Hanja (LogoS) in the subjects with the first language (L1) PhonoS divided into two groups as high versus low competency to L2 LogoS (High-C versus Low-C), Low-C group demonstrated activation and lateralization in the right SPL and VLPFC as well as left SMA, likely due to neural efficiency such as visuospatial attention and cognition rather than core neurolinguistic neural demand like OrthoR processing.

Conflicts of Interest

The authors have no conflicts of interest.

Authors’ Contributions

Byung-Gee Bak and Young-Bo Kim contributed equally to this work.

Acknowledgments

The authors would like to thank Dr. Michael DiGianvittorio (Johns Hopkins University School of Medicine, Baltimore, MD, US) for his assistance with the preparation of this manuscript. The authors would also like to acknowledge KAPHE for helping with data collection and Jemin Ahn for helping with data analysis. This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A5A2A03045081) and GRRC (Gyunggi Regional Research Center, Artificial Intelligence Health Care Research Center).

References

C. J. Price, “The anatomy of language: a review of 100 fMRI studies published in 2009,” Annals of the New York Academy of Sciences, vol. 1191, pp. 62–88, 2010.

D. J. Bolger, C. A. Perfetti, and W. Schneider, “Cross-cultural effect on the brain revisited: Universal structures plus writing system variation,” Human Brain Mapping, vol. 25, no. 1, pp. 92–104, 2005.

M. Coltheart, “Modeling Reading: The Dual-Route Approach,” in The Science of Reading: A Handbook, M. J. Snowling and C. Hulme, Eds., pp. 6–23, Blackwell Publishing Ltd, Malden, Mass, USA, 2005.

L. Mei, G. Xue, Z.-L. Lu et al., “Artificial language training reveals the neural substrates underlying addressed and assembled phonologies,” PLoS ONE, vol. 9, no. 3, Article ID e93548, 2014.

Y. Sakurai, T. Momose, M. Iwata, Y. Sudo, K. Ohtomo, and I. Kanazawa, “Different cortical activity in reading of Kanji words, Kana words and Kana nonwords,” Cognitive Brain Research, vol. 9, no. 1, pp. 111–115, 2000.

K.-M. Lee, “Functional MRI comparison between reading ideographic and phonographic scripts of one language,” Brain and Language, vol. 91, no. 2, pp. 245–251, 2004.

K. A. Buetler, D. D. L. Rodriguez, M. Laganaro, R. Müri, L. Spierer, and J.-M. Annoni, “Language context modulates reading route:An electrical neuroimaging study,” Frontiers in Human Neuroscience, vol. 8, no. 1, article 83, 2014.

M. W. Chee, E. W. Tan, and T. Thiel, “Mandarin and English single word processing studied with functional magnetic resonance imaging,” The Journal of Neuroscience, vol. 19, no. 8, pp. 3050–3056, 1999.

L. H. Tan, L. Chen, V. Yip et al., “Activity levels in the left hemisphere caudate-fusiform circuit predict how well a second language will be learned,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 6, pp. 2540–2544, 2011.

M. S. Koyama, J. F. Stein, C. J. Stoodley, and P. C. Hansen, “Cerebral mechanisms for different second language writing systems,” Neuropsychologia, vol. 51, no. 11, pp. 2261–2270, 2013.

S. Yokoyama, J. Kim, S. Uchida, T. Miyamoto, K. Yoshimoto, and R. Kawashima, “Cross-linguistic influence of first language writing systems on brain responses to second language word reading in late bilinguals,” Brain and Behavior, vol. 3, no. 5, pp. 525–531, 2013.

K. H. Kim, N. R. Relkin, K. M. Lee, and J. Hirsch, “Distinct cortical areas associated with native and second languages,” Nature, vol. 388, no. 6638, pp. 171–174, 1997.

J. R. Nelson, Y. Liu, J. Fiez, and C. A. Perfetti, “Assimilation and accommodation patterns in ventral occipitotemporal cortex in learning a second writing system,” Human Brain Mapping, vol. 30, no. 3, pp. 810–820, 2009.

A. Ischebeck, P. Indefrey, N. Usui, I. Nose, F. Hellwig, and M. Taira, “Reading in a regular orthography: an fMRI study investigating the role of visual familiarity,” Journal of Cognitive Neuroscience, vol. 16, no. 5, pp. 727–741, 2004.

A. Nakagawa and M. Sukigara, “Visual word form familiarity and attention in lateral difference during processing Japanese Kana words,” Brain and Language, vol. 74, no. 2, pp. 223–237, 2000.

K. Yoshizaki, “Effects of visual familiarity for words on interhemispheric cooperation for lexical processing,” Cognitive Brain Research, vol. 12, no. 3, pp. 409–414, 2001.

P. Bonin, M. Fayol, and M. Chalard, “Age of acquisition and word frequency in written picture naming,” Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, vol. 54, no. 2, pp. 469–489, 2001.

S. Gerhand and C. Barry, “Age of acquisition, word frequency, and the role of phonology in the lexical decision task,” Memory and Cognition, vol. 27, no. 4, pp. 592–602, 1999.

C. M. Connine, J. Mullennix, E. Shernoff, and J. Yelen, “Word familiarity and frequency in visual and auditory word recognition,” Journal of Experimental Psychology: Learning, Memory, and Cognition, vol. 16, no. 6, pp. 1084–1096, 1990.

C. A. Perfetti, Y. Liu, J. Fiez, J. Nelson, D. J. Bolger, and L.-H. Tan, “Reading in two writing systems: accommodation and assimilation of the brain's reading network,” Bilingualism, vol. 10, no. 2, pp. 131–146, 2007.

J. Bai, J. Shi, Y. Jiang, S. He, and X. Weng, “Chinese and Korean characters engage the same visual word form area in proficient early Chinese-Korean bilinguals,” PLoS ONE, vol. 6, no. 7, Article ID e22765, 2011.

C. Bloch, A. Kaiser, E. Kuenzli et al., “The age of second language acquisition determines the variability in activation elicited by narration in three languages in Broca's and Wernicke's area,” Neuropsychologia, vol. 47, no. 3, pp. 625–633, 2009.

M. D. Lieberman and W. A. Cunningham, “Type I and type II error concerns in fMRI research: re-balancing the scale,” Social Cognitive and Affective Neuroscience, vol. 4, no. 4, Article ID nsp052, pp. 423–428, 2009.

A. T. Shafer and F. Dolcos, “Neural correlates of opposing effects of emotional distraction on perception and episodic memory: an event-related fMRI investigation,” Frontiers in Integrative Neuroscience, vol. 6, article 70, 2012.

L. H. Tan, A. R. Laird, K. Li, and P. T. Fox, “Neuroanatomical correlates of phonological processing of Chinese characters and alphabetic words: a meta-analysis,” Human Brain Mapping, vol. 25, no. 1, pp. 83–91, 2005.

M. Kwon, J. S. Kim, J.-H. Lee, H. Sim, K. Nam, and H. Park, “Double dissociation of Hangul and Hanja reading in Korean patients with stroke,” European Neurology, vol. 54, no. 4, pp. 199–203, 2006.

Y. Sakurai, M. Asami, and T. Mannen, “Alexia and agraphia with lesions of the angular and supramarginal gyri: Evidence for the disruption of sequential processing,” Journal of the Neurological Sciences, vol. 288, no. 1-2, pp. 25–33, 2010.

T. H. Lucas II, G. M. McKhann II, and G. A. Ojemann, “Functional separation of languages in the bilingual brain: a comparison of electrical stimulation language mapping in 25 bilingual patients and 117 monolingual control patients,” Journal of Neurosurgery, vol. 101, no. 3, pp. 449–457, 2004.

K. Usui, A. Ikeda, M. Takayama et al., “Processing of Japanese morphogram and syllabogram in the left basal temporal area: electrical cortical stimulation studies,” Cognitive Brain Research, vol. 24, no. 2, pp. 274–283, 2005.

H. R. Heekeren, S. Marrett, P. A. Bandettini, and L. G. Ungerleider, “A general mechanism for perceptual decision-making in the human brain,” Nature, vol. 431, no. 7010, pp. 859–862, 2004.

C. A. Becker, “Semantic context and word frequency effects in visual word recognition,” Journal of Experimental Psychology: Human Perception and Performance, vol. 5, no. 2, pp. 252–259, 1979.

A. A. Cleland, M. G. Gaskell, P. T. Quinlan, and J. Tamminen, “Frequency effects in spoken and visual word recognition: evidence from dual-task methodologies,” Journal of Experimental Psychology: Human Perception and Performance, vol. 32, no. 1, pp. 104–119, 2006.

W.-J. Kuo, T.-C. Yeh, C.-Y. Lee et al., “Frequency effects of Chinese character processing in the brain: an event-related fMRI study,” NeuroImage, vol. 18, no. 3, pp. 720–730, 2003.

Y. C. Luo, X. Chen, S. H. Deacon, J. Zhang, and L. Yin, “The role of visual processing in learning to read Chinese characters,” Scientific Studies of Reading, vol. 17, no. 1, pp. 22–40, 2013.

H. S. Huang and J. R. Hanley, “Phonological awareness and visual skills in learning to read Chinese and English,” Cognition, vol. 54, no. 1, pp. 73–98, 1995.

Y. Zhou, C. McBride-Chang, and N. Wong, “What is the role of visual skills in learning to read?” Frontiers in Psychology, vol. 5, 2014.

W. T. Siok and P. Fletcher, “The role of phonological awareness and visual-orthographic skills in Chinese reading acquisition,” Developmental Psychology, vol. 37, no. 6, pp. 886–899, 2001.

X. Wu, W. Li, M. Zhang, and J. Qiu, “The neural basis of impossible figures: Evidence from an fMRI study of the two-pronged trident,” Neuroscience Letters, vol. 508, no. 1, pp. 17–21, 2012.

I. M. Harris, G. F. Egan, C. Sonkkila, H. J. Tochon-Danguy, G. Paxinos, and J. D. G. Watson, “Selective right parietal lobe activation during mental rotation a parametric PET study,” Brain, vol. 123, no. 1, pp. 65–73, 2000.

P. L. Ditunno and V. A. Mann, “Right hemisphere specialization for mental rotation in normals and brain damaged subjects,” Cortex, vol. 26, no. 2, pp. 177–188, 1990.

V. W. Ng, P. J. Eslinger, S. C. Williams et al., “Hemispheric preference in visuospatial processing: a complementary approach with fMRI and lesion studies,” Human Brain Mapping, vol. 10, no. 2, pp. 80–86, 2000.

M. S. Koyama, J. F. Stein, C. J. Stoodley, and P. C. Hansen, “Functional MRI evidence for the importance of visual short-term memory in logographic reading,” European Journal of Neuroscience, vol. 33, no. 3, pp. 539–548, 2011.

Y. Sun, Y. Yang, A. S. Desroches, L. Liu, and D. Peng, “The role of the ventral and dorsal pathways in reading Chinese characters and English words,” Brain and Language, vol. 119, no. 2, pp. 80–88, 2011.

G. Meschyan and A. E. Hernandez, “Impact of language proficiency and orthographic transparency on bilingual word reading: an fMRI investigation,” NeuroImage, vol. 29, no. 4, pp. 1135–1140, 2006.