Developmental Neuropsychology Two-Character ...

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Two-Character Chinese Compound Word Processing in Chinese Children With and Without Dyslexia: ERP Evidence a

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Xiuhong Tong , Kevin Kien Hoa Chung & Catherine McBride

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Department of Psychology, The Chinese University of Hong Kong, Hong Kong b

Department of Special Education and Counselling, The Hong Kong Institute of Education, Hong Kong Published online: 22 May 2014.

To cite this article: Xiuhong Tong, Kevin Kien Hoa Chung & Catherine McBride (2014) Two-Character Chinese Compound Word Processing in Chinese Children With and Without Dyslexia: ERP Evidence, Developmental Neuropsychology, 39:4, 285-301, DOI: 10.1080/87565641.2014.907720 To link to this article: http://dx.doi.org/10.1080/87565641.2014.907720

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DEVELOPMENTAL NEUROPSYCHOLOGY, 39(4), 285–301 Copyright © 2014 Taylor & Francis Group, LLC ISSN: 8756-5641 print / 1532-6942 online DOI: 10.1080/87565641.2014.907720

Two-Character Chinese Compound Word Processing in Chinese Children With and Without Dyslexia: ERP Evidence Xiuhong Tong Department of Psychology, The Chinese University of Hong Kong, Hong Kong

Kevin Kien Hoa Chung Department of Special Education and Counselling, The Hong Kong Institute of Education, Hong Kong

Catherine McBride Department of Psychology, The Chinese University of Hong Kong, Hong Kong

Using event-related potential (ERP) measures, we examined the time course of Chinese compound word processing in 15 dyslexic and 10 normal children in a lexical decision task with three con(house)), reversed nonwords (e.g., can be transposed ditions including real words (e.g., (ocean)) and random nonwords (e.g., is not a real word when transposto a real word ing). Behavioral results showed that dyslexic children performed slower and less accurately than normal children did across conditions. ERP data revealed that normal children exhibited significant N400 effects across conditions. The dyslexics did not show any difference on N400, however, suggesting a possible weakness of morphological processing in dyslexic children.

Although morphological awareness defined as awareness of and access to a morpheme within a multi-morpheme word (Carlisle, 1995) has been shown to be strongly associated with word reading across languages (e.g., Casalis & Louis-Alexandre, 2000; McBride-Chang, Shu, Zhou, Wat, & Wagner, 2003; Shu, McBride-Chang, Wu, & Liu, 2006), there remains the question of how children process morphological information during word processing. This question is important for Chinese dyslexic children, that is, those who have difficulties in reading and spelling despite normal intelligence and adequate formal education, because Chinese children with developmental dyslexia have shown deficits in morphological awareness (Shu et al., 2006). In Hong Kong, the prevalence rate of dyslexia is approximately 9.7–12% in Hong Kong school children (Chan, Ho, Tsang, Lee, Chung, 2007; Lam et al., 2008). However, we know little about the temporal Correspondence should be addressed to Kevin Kien Hoa Chung, Social and Cognitive Neuroscience Unit, Department of Special Education and Counselling, The Hong Kong Institute of Education, 10 Lo Ping Road, Tai Po, N.T., Hong Kong. E-mail: [email protected]


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TONG, CHUNG, MCBRIDE

course of morphological processing of Chinese compound words in Chinese children with and without dyslexia, because most previous studies on morphological processing in Chinese children have used correlational or behavioral measures, for which the temporal course of morphological information processing might not be clearly detectable (e.g., Kiefer & Brendel, 2006; Landi & Perfetti, 2007). One way we can further understand the processing of morphological information in children is to use a direct measure such as an event-related potential (ERP) approach. The ERP approach provides a continuous record of brain activity with millisecond temporal resolution (e.g., Molfese, Molfese, & Espy, 1999). Also, ERPs are time-locked to the onset of stimuli, which makes it possible to determine which stage or stages of processing are affected by a specific experimental manipulation (Luck, 2005). In the present study, we, therefore, adopted an ERP approach to investigate the morphological processing of two-character compound words in Chinese children with and without dyslexia. To date, several correlational studies on morphological awareness in children have suggested that young children are able to use morphological information about individual morphemes in processing multi-morpheme compound words (e.g., Casalis & Louis-Alexandre, 2000; Jones, 1991; McBride-Chang et al., 2003). For example, Jones (1991) used tasks that involved imitating morphologically complex words, leaving out a part of words, and discussing the meaning of resulting word parts to examine the underlying representation of morphophonemic segments among first graders. Results indicated that language-advanced children who performed well on metalinguistic and reading skills demonstrated superior representations of morphophonemic segments compared to language-delayed age-matched children. McBride-Chang and colleagues (2003) reported similar findings showing that Chinese children as young as 5 years of age were aware of the compounding rules in multi-morpheme words and could create novel combinations of several single morphemes to form new multi-morpheme pseudo-words that would be “legal” in the language. For example, they could generate a novel pseudo-multi-morpheme word “mushroom oil” when they were asked to answer the question “When an oil is made of peanut, we call that ‘peanut oil;’ what should we call it if the oil is made of mushrooms?” In addition, studies have consistently reported that Chinese children with dyslexia have difficulties in combining separate morphemes into Chinese compound words (e.g., McBride-Chang, Lam, et al., 2011; McBride-Chang, Liu, Wong, Wong, & Shu, 2011; Shu et al., 2006). Moreover, such morphological awareness weakness persists into adolescence (Chung, Ho, Chan, Tsang, & Lee, 2010), and it has become one of the most salient indicators of Chinese children with development dyslexia (e.g., Shu et al., 2006). Findings from these studies support a link between morphological knowledge of Chinese compound words and children’s ability to read Chinese. The unique features of Chinese language in morphology also support this link. The most common method of word formation in Chinese is lexical compounding (e.g., Zhou & Marslen-Wilson, 1995). It has been estimated that the Chinese language consists of more than 70% words are compound words (Institute of Language Teaching and Research, 1986). The individual morphemes of a compound word each contribute to the meaning of the compound word. For example, the word “garden” is represented by a twoin Chinese. The morpheme of means flower, and the meaning character compound word of the morpheme is a place for public cultivation. Although children may not be familiar with , they can gain some idea of its meaning by semantically combining the two morword phemes, “a place for cultivating the flower.” The awareness and ability in understanding and


COMPOUND WORD PROCESSING, CHINESE DYSLEXIA, ERP STUDY

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manipulating the morphological compound structure has been identified to significantly correlate with children’s language learning and literacy development (e.g., McBride-Chang et al., 2003; Shu et al., 2006). In addition, in the Chinese orthography, a character, the basic writing unit in Chinese, typically maps directly onto both a morpheme and a syllable, which is the same unit in Chinese. The rules of regular or quasi-regular letter sounds in alphabetic languages cannot be found in Chinese (Tan & Perfetti, 1998). This may focus Chinese readers less on phonology as compared to readers of alphabetic languages. Phonological information is also relatively unreliable in Chinese (McBride-Chang & Liu, 2011). For example, less than 30% of Chinese characters are pronounced identically to their phonetic components (e.g., Shu, Chen, Anderson, Wu, & Xuan, 2003). Furthermore, it is well known that there are a lot of homophones in Chinese. According to Xiandai Hanyu Pinyin Cidian (1986), there are 4,575 characters in modern-day usage. These 4,575 characters make up a 1,800,000 Chinese word corpus. However, there are only about 420 syllables (disregarding tone) in Mandarin; thus, around 11 characters on average share one pronunciation in Mandarin (Su, Klingebiel, & Weekes, 2010). For example, the Cantonese syllable /cai/ could represent infuse/ /, wife/ /, build/ /, and so on. The ability to distinguish across homophones with different meanings has been found to correlate with Chinese children’s literacy development (e.g., McBride-Chang et al., 2003). Overall, the rich morphological nature of Chinese makes morphological awareness a strong correlate of Chinese reading development and impairment (e.g., Shu et al., 2006). Despite the fact that previous studies (e.g., McBride-Chang et al., 2003; Shu et al., 2006) have underscored the importance of morphological processing across dyslexic and typically developing children, it is still unclear how Chinese children process morphological information in the unfolding time course of word processing. The morphological processing in this study especially refers to children’s implicit awareness or sensitivity to morpheme constituents within a twocharacter Chinese compound word. The ERP measure, as noted above, is an approach with very fine temporal resolution, which can represent the brain’s response to an eliciting input. Also, ERP is suggestive of the distribution of brain mechanisms that subserve functions such as language even though its spatial resolution is not high (Molfese, Molfese, & Kelly, 2001). Therefore, in this study, we used the ERP measure to explore the temporal course of two-character compound word processing in Chinese normal and dyslexic children. To date, several ERP components, including early components (e.g., N150, P200) and later components (e.g., N400, P600), have been reported to relate to different aspects of language information processing (e.g., Friederici, Hahne, & Mecklinger, 1996; Penke et al., 1997). The N400 component is of particular relevance for the present study, because this component has been reported in recent ERP studies addressing the question of morphological processing in adults across languages (e.g., Gross, Say, Kleingers, Clahsen, & Münte, 1998; Huang, Lee, Huang, & Chou, 2011; Münte, Say, Clahsen, Schiltz, & Kutas, 1999). The N400 is a scalp negative deflection peaking around 400 msec post stimulus. It is taken as a measure for the semantic evaluation of words generally observed in lexical decision/priming tasks or sentence acceptance tasks (e.g., Deacon, Hewitt, Yang, & Nagata, 2000; Gomes, Ritter, Tartter, Vaughan, & Rosen, 1997; Holcomb, 1988; Kutas & Hillyard, 1984). In addition, the N400 component has been found to be sensitive to morphological structure processing (e.g., Gross et al., 1998; Huang et al., 2011; Münte et al., 1999).


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For example, Bai, Cai, and Schumacher (2011) used an ERP measure examining the pro(tie) vs. (lead)) via a lexical decision cessing of reversed compounds in Chinese (e.g., paradigm in adults ranging in age from 21–26 years. In their study, there were four experimental (tie)), reversible B+A (e.g., (lead)), nonconditions, including reversible A+B (e.g., (task)), and nonreversible B+ A ( (nonsense word)) conditions. The reversible (e.g., researchers found that there were significant differences in ERPs for reversible words as compared to nonreversible words. That is, a more pronounced fronto-central maximum N400 was found for the reversible words followed by a positive deflection for nonreversible words. Also, the pseudo words comprising two constituents, which, when read backwards, constituted a real word, showed a more negative N400 relative to the reversible words. The ERP findings shown in the study by Bai et al. (2011) indicate that character reversibility (irrespective of whether the actual combination constitutes a real word or not) has a detectable influence on the processing of twocharacter entities and that the availability of a competing reverse structure may restrain semantic retrieval. Thus, Bai et al. (2011) suggest that the effect of character reversibility reflects that the processing of two-character Chinese compound word may be a decomposition /re-composition process. In this study, two-character compound words were selected as stimuli. The experimental design and paradigm were the same as in the behavioral study by Liu, Chung, McBride-Chang, and Tong (2010) on children. Three experimental conditions were created: (1) Real word con(weather); dition, in which real Chinese compound words were presented, for example, (2) Reversed nonword condition, where a stimulus was generated by reversing the order of morcame from the word (holiday); and (3) Random phemes in a real compound word (e.g., is a nonword condition, in which two free morphemes were randomly combined (e.g., combined nonword by randomly combined the morphemes and .) We expected that it should be the most difficult for children to judge stimuli presented in the reversed nonword condition, followed by the random and real word conditions. Our rationale for this hypothesis was that a real two-character compound word might be processed as a “chunk” when considering the “look and say” method used in word teaching in Hong Kong. With the “look and say” method children learn words as whole units, rather than segmenting a word into individual morphemes. Children eventually recognize words through pattern recognition without a focused attempt to decompose the word down into its parts in the real word condition. In contrast, the two morphemes may be independently activated at the semantic level in the reversed (ocean) + (sea)) and random conditions (e.g., (fight) + (travel)) because there (e.g., is no such lexical representation in children’s lexicon for the nonword in the reversed condition ) or random condition (e.g., ). Thus, the lexical decision of real words should be (e.g., performed more quickly compared to the performance in the reversed and random conditions. ), we hypothesized that this should be the As for the processing of reversed nonwords (e.g., most difficult, because children may have to inhibit the influence of the activation of the real (sea). The differences across experimental word by reversing the two morphemes, that is, conditions should be found in the time window of N400, which has been reported in several ERP studies on morphological processing (e.g., Bai et al., 2011). In addition, if dyslexic children have no deficit in processing morphological information, they would be expected to show the same patterns as the control group across experimental conditions. However, if they did, in fact, manifest difficulties in processing morphological information at some point during the processing period, they were expected to exhibit atypical patterns compared to age-matched children in the present study.


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METHOD


Participants Twenty-five Hong Kong children from third and fourth grades were tested: 15 dyslexic children (7 females and 8 males) aged between 104 and 125 months (M age = 116.67 months, SD = 6.54) and 10 typically developing control children (6 female and 4 male) ages 100 to 120 months (M age = 112.70 months, SD = 6.18) as age-matched control group. There was no difference in age between the dyslexic and control groups (t = 1.54, p = .14). Children in the control and dyslexic groups were recruited through the local primary schools and education authorities, respectively. According to the diagnosis reports given, all dyslexic children had normal intelligence (i.e., IQ > 85). They were also diagnosed as suffering from developmental dyslexia by professional psychologists in accordance with the diagnostic criteria set out in the Hong Kong Test of Specific Learning Difficulties in Reading and Writing (HKT-P (II); Ho et al., 2007). This test battery consists of literacy skills, speeded naming, phonological awareness, phonological memory and orthographic skills. Gardner’s (1996) Test of Visual-Perceptual Skills (Non-motor) Revised (TVPS-R) was also used to test children’s visual perceptual and visual memory skills. To be classified as manifesting dyslexia, children’s literacy composite score and one cognitive composite score had to be at least one standard deviation below their respective age means for the HKT-P (II) and TVPS-R. The cognitive composite score used here refers to cognitive abilities involved in reading-spelling related cognitive abilities only. For children in the control group, the teachers were asked to nominate students who were relatively average performers in the class. None of the 10 normal children had any history of developmental dyslexia or any other type of learning difficulty or psychopathology reported by parents and schools. In addition, in order to make sure the two groups differed in word reading and word dictation, a Chinese word reading adapted from a previous study (Liu et al., 2010) and a Chinese character dictation task developed based on the dictation subset of The Hong Kong Test of Specific Learning Difficulties in Reading and Writing (Ho, Chan, Tsang, & Lee, 2000) were administered. Statistical analyses revealed that the two groups scored significantly differently in Chinese word reading (M = 48.30 and 30.00, SD = 3.83 and 10.50 for the control and dyslexic groups, respectively) and Chinese character dictation (M = 21.20 and 9.60, SD = 6.83 and 6.54 for control and dyslexic groups, respectively). In addition, all of the selected participants were right-hand dominant children. Two children who were left-hand dominant were excluded from the experiment. None of the participants had a history of neurological, psychiatric, or brain injury problems, and all had normal or corrected-to-normal vision. Materials Stimuli were real Chinese two-character compound words, reversed nonwords, and randomly combined nonwords for the real word, reversed and random conditions, respectively. There were 80 real two-character compound words in the real word condition, 40 reversed nonwords in the reversed condition, and 40 randomly combined nonwords in the random condition. There were also 10 items for practice. The stimuli for the reversed and random conditions were created following on the study by Liu et al. (2010). First, a set of the two-character compound words,


290


such as ( (sea)) were selected from a list of words learned by Hong Kong primary school students and these words are common words that are all taught by grade 2. Then the order of the from (sea)). These reversed nonwords are not real two characters was reversed (e.g., words when read from left to right. We then created the stimuli for the random condition on the basis of stimuli selected for the reversed condition by randomly combining two characters used in the reversed condition. For example, we first created two nonwords as the reversed nonwods (the reversed form of the real word (fight) and (by reversing the order of the (e.g., and in the real word (travel)). To create stimuli for the random word two morphemes from and the morpheme from condition, we randomly combined the morpheme to form a nonword as a stimulus for the random condition. The nonword was not a real word either reading from left to right or from right to left. These two types of nonwords (reversed nonwords and random nonwords) have been successfully used in a previous behavoural study for the same age of normal children (Liu et al., 2010). As for the real words in the real word condition, all we selected were not real words when the order of the two characters was reversed. In the reversed and random conditions, we also ensured that neither the nonwords (the reversed nonwords in the reversed condition) nor their homophones were real words. The same characters were used in the reversed and random conditions, in order to control the variance in items in relation to visual complexity across the two conditions. Moreover, all words including the words used for generating nonwords used in this study were Chinese two-character compound words, and they were selected from a list of those identified as typically learned among children of given grade levels from the Chinese Language Education Section of Hong Kong (2009); only words that were expected to have been learned by third grade were included. We checked to ensure that all words were compound ones on the website developed by the Quality Education Fund (2003). All stimuli were selected to be sufficiently easy to recognize such that any decisions made about them would not be related to literacy levels of the stimuli per se. The use-in-common rank index of all characters listed by the Quality Education Fund (2003) was further used to assess the frequencies of these materials. As a rank index, the larger the usein-common index, the lower is the frequency of the character in use. The first 3,000 characters are considered as the most commonly used in Chinese, and almost all of the characters we selected were ranked in the top 1,500. The stroke numbers of the characters were also considered in selecting the materials. Finally, the semantic transparency of the compound words was rated by five native Cantonesespeaking college students on a scale ranging from 0 to 10. They were asked to judge whether the meaning of the whole word was related to the original meaning of the constituent characters. The words we selected were judged to be relatively semantically transparent. Detailed information about these materials is listed in Table 1. Procedure A consent form and parental questionnaire were presented to the families for completion before testing began. The parental questionnaire was used to screen out children with ADHD and other related learning disabilities; this questionnaire also ensured that the first language of all children was Cantonese. Following completion of these forms, participants were invited to come into a sound-attenuated ERP lab to be tested. A cartoon video was shown to participants


291

TABLE 1 Details of the Experimental Materials Selected Across the Experimental Conditions


Character familiarity Stroke number

Real

Reversed

Random

t

518.04 (434.80) 9.01 (4.04)

489.89 (411.15) 9.21 (3.51)

— —

.26 .65

Note. The numbers in parentheses are standard deviations.

FIGURE 1 Procedure of trial presentation.

during experiment preparation (during which an assistant helped each participant to wash her/his hair, plug electrodes, etc.). After preparation, one helper, a native Cantonese speaker, instructed each participant on details of the experimental procedure. The child was told that each real word should be labeled as such if it could be recognized as one seen before. In contrast, non-real words were defined as those never seen before. Six real words or non-real words printed on paper were shown to each participant, and children were asked to read aloud the words and judge them as real or non-real as examples (no reading aloud took place during the actual experiment). Detailed instructions about completion of the task were also presented via computer screen before the task began. Children were asked to judge whether the stimuli presented on the screen were real words or not by pressing the corresponding button via a Universal Serial Bus (USB) corresponding box with two buttons (“right button” for real words and “left button” for non-real words) as quickly and as accurately as possible. E-Prime software was used to design the testing program and record children’s reaction times and accuracy rates. First, a fixation “+” was presented at the center of the computer screen for 600 msec; a blank was presented after “+” with 500 msec. It was then replaced by the stimulus. This stimulus was presented for a total of 2,000 msec. Following presentation of the target word, there was a 1,500 msec interval. All stimuli were presented in Kaiti font with a font size of 38 for each stimulus. The procedure for each trial presentation is shown in Figure 1. Half of the real words in real word condition were combined with the stimuli in the reversed nonword condition to form Block 1, while the other half of the words in the real word condition were combined with the stimuli in the randomly combined nonword condition to become Block 2. Thus there were 80 items in Block 1 and 80 in Block 2. The items in each block were scrambled and the order was randomized during testing. Half of the participants of each group saw Block 1 first, and the other half saw Block 2 first.


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Participants were tested individually in a sound-attenuating and electrically shielded room. They were seated in a comfortable chair in front of a computer monitor at a distance of 80 cm from the computer monitor. Before formal EEG recording, participants were instructed to observe changes of the waveforms caused by their movements or eye blinks. These demonstrations were used to reinforce our request that all participants try hard to keep quiet and refrain from moving as much as possible; they were also asked to avoid excessive eye movements and blinking as much as possible during the testing. There were some practice trials to help children to become familiar with the experiment. In order to make sure that they understood the task, they were not allowed to continue the experiment when their accuracy was lower than 75% in the practice section. EEG Recordings Electroencephalographic (EEG) activity was recorded with 30 channels (FP1, FP2, F7, F3, FZ, F4, F8, FT7, FC3, FCZ, FC4, FT8, T7, C3, CZ, C4, T8,TP7, CP3, CPZ, CP4, TP8, P7, P3, PZ, P4, P8, O1, OZ and O2). The 30 channels were arranged according to a 10/20 system referred to two mastoids. The vertical electrooculogram (EOG) was obtained from below versus above the left eye (vertical EOG) and the left versus right lateral orbital rim (horizontal EOG). The AFz electrode on the cap served as ground. During recording, the electrode impedance was kept below 5K. The EEG and EOG signals were amplified with a bandpass of 0.05 to 100 Hz and digitized at a sampling rate of 500 Hz. Data Analysis EEG data were analyzed off-line using Scan 4.4 software. Trials contaminated by eye movements and blinks were rejected before averaging. The continuous data were filtered with a 0.10 Hz to 30 Hz band pass. The filtered data were segmented into epochs of 1,000 msec long, with 100 msec pre-stimulus as the baseline. Segments were averaged separately for each experimental condition. For the reaction time and accuracy data, we performed the mixed-design analyses of variance (ANOVAs), with experimental conditions (the real vs. the reversed vs. the random) as a within factor and groups (controls vs. dyslexics) as a between factor. The grand averaged ERP waveforms for the two groups are shown in Figures 2 and 3, respectively. Repeated measures ANOVAs with group (dyslexia and controls) as a between-subject factor and experimental condition (real vs. reversed vs. random) and electrode as within-subject factors were performed. For each ANOVA, the Greenhouse-Geisser adjustment to the degrees of freedom was used to correct for the violations of sphericity associated with repeated measures.

RESULTS Behavioral Results Repeated-measure ANOVAs with a within-subject factor of experimental conditions (three levels: real word vs. reversed nonword vs. random nonword) and group (dyslexic and control) serving as the between-subject factor were performed in relation to both reaction times (RTs) and accuracy



293

FIGURE 2 Grand averaged event-related potentials for the dyslexic group at representative electrodes. The solid line represents the real condition, the dot for the random condition, and the dash dot for the reversed condition for the word judgment task.

(Acc). For RTs, a main group effect was significant (F(1, 23) = 51.66, p < .001, ES = .69). RTs for the dyslexic group (1,324.31 msec) were significantly slower than for the control group (952.68 msec), suggesting that the dyslexic group tended to show greater weakness in processing the morphological information than the control group did. Moreover, there was a significant main effect of experimental condition on RTs (F(2, 46) = 27.91, p < .001, ES = .75) showing that the reversed nonwords were more difficult to process (1,251.48 msec) than the real words (989.31msec) and random nonwords (1,174.71 msec). No group by experimental conations was revealed (F(2, 46) = .10, p > .89, ES = .01). For accuracy, there was a main group effect (F(1, 23) = 9.07, p < .01, ES = .28), reflecting lower accuracy in the dyslexic group (81%) than in the control group (94%). This suggests that dyslexic children were generally less accurate at processing two-character compound words than were the normal children. A main effect of experimental condition was also found (F(2, 46) = 5.61, p < .05, ES = .33) showing that the reversed nonwords had the lowest accuracy (81%) compared to the real words (89%) and random nonwords (92%). However, no significant interaction between group and accuracy was found in the present study.


294


FIGURE 3 Grand averaged event-related potentials for the control group at representative electrodes. The solid line represents the real condition, the dot for the random condition, and the dash dot for the reversed condition for the word judgment task.

Similar patterns were found for the item analyses with the longest reaction time for the reversed nonword condition for both groups in RT (Mean = 1462.72 and 1069.08 for dyslexic and control groups, respectively), followed by the random nonword condition (Mean = 1356.29 and 943.36 for dyslexic and control groups, respectively) and the real condition (Mean = 1160.70 and 817.74 for dyslexic and control groups, respectively) and lowest accuracy in the reversed nonword condition (Mean = 0.72 and 0.90 for dyslexic and control groups, respectively) followed by the random nonword condition (Mean = 0.87 and 0.96 for dyslexic and control groups, respectively) and the real word condition (Mean = 0.85 and 0.94 for dyslexic and control groups, respectively). The RTs and accuracy rates based on the subject analyses are shown in Table 2. ERP Results Only trials on which a participant made a correct response were included in the average. On average, in the dyslexic group, there were 62, 27, and 31 trials that were usable for data analyses for


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TABLE 2 Reaction Times (msec) and Accuracy (Percentage) for Control and Dyslexic Groups in the Task Reaction Time


Conditions Real Reversed Random

Accuracy (%)

Dyslexic

Control

Dyslexic

Control

1166.67 (176.36) 1438.63 (176.11) 1367.63 (203.78)

811.94 (81.07) 1064.33 (143.93) 981.78 (119.67)

85.08 (11.30) 71.21 (25.08) 87.45 (12.07)

94.10 (3.01) 90.93 (7.10) 95.97 (3.39)

Note. The numbers in parentheses are standard deviations.

the real, reversed, and random conditions, respectively. In the control group, we used, on average, 74, 35, and 38 trials for the real, reversed, and random conditions, respectively. Statistical analyses were performed on the amplitude measured as the mean amplitude across the 300–500 msec time window for the N400 component. The mean amplitude across 500–1,000 msec was measured for the LPC component. Repeated measures ANOVAs with group as the between-subject factor and the experimental condition and electrode as within-subject factors were performed on the two components. For the LPC component, although the mean amplitude analyses in both the midline and lateral analyses revealed a significant interaction of group by experimental conditions, further tests indicated that there was only a significant difference found between the real word and reversed conditions in the control group. The difference between the reversed and random conditions, which was our main focus, did not reach statistical significance. Therefore, we have not reported the results of LPC analyses. The N400 component was distributed over the entire scalp. Both midline with five electrodes (FZ, FCZ, CZ, CPZ, and PZ) and lateral analyses with five electrodes for each hemisphere (Left hemisphere: F3, FC3, C3, CP3, and P3; Right hemisphere: F4, FC4, C4, CP4, and P4) were used in this time window. ANOVA analyses in the midline electrodes revealed main effects of experimental condition (F(2, 46) = 5.13, p < .05, ES = .36). Further tests indicated that the mean amplitude in the real word condition (–5.08 µV) was significantly less negative than the mean amplitude in the reversed nonword (–7.25 µV) and random nonword conditions (–7.11 µV), and no significant difference was found between the reversed nonword and random nonword conditions. The main effect of electrode was also found (F(4, 92) = 21.98, p < .001) with the most negative response for the Cz electrode (–9.39 µV) followed by FCz (–9.82 µV), Fz (–7.83 µV), CPz (–5.20 µV), and Pz (–.18 µV). There was no main effect of group in the midline electrode analyses (F(1, 23) = 1.78, p > .2, ES = .07), but a significant interaction between experimental condition and group was found (F(2, 46) = 5.47, p < .01, ES = .19). Further tests revealed that for the control group the reversed condition elicited the most negative response (–7.59 µV)relative to the real word condition (–3.29 µV) and random nonword condition (–6.09 µV). However, dyslexic children showed no difference in the mean amplitude across experimental conditions in the midline electrode analyses. Lateral analyses revealed a significant main effect of experimental condition (F(2, 46) = 6.14, p < .01, ES = .39) and a marginally significant main effect of hemisphere (F(1, 23) = 3.05, p = .09, ES = .12). Further tests showed that the mean amplitude in the real word condition (–3.25 µV) was less negative than the mean amplitude in the reversed condition (–5.31 µV) and random


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condition (–5.03 µV), and the mean amplitude in the left hemisphere (–5.13 µV) was more negative than the mean amplitude in the right hemisphere (–3.93 µV). Importantly, the lateral analyses showed a significant interaction between the experimental condition and group (F(2, 46) = 6.14, p < .01, ES = .38) with the more negative mean amplitude in the reversed nonword condition (–7.82 µV) for the control group compared to the mean amplitude in the random nonword condition (–6.29 µV) and real word condition (–3.51 µV). However, the dyslexic group showed no differences across experimental conditions for the lateral analyses. The interaction of hemisphere and condition was also found in the lateral analyses (F(2, 46) = 6.84, p < .01, ES = .43). Further tests showed that an interaction between group and experimental condition was found in the left hemisphere (F(2, 18) = 9.73, p < .01, ES = .20) with the most negative mean amplitude for the reversed nonword condition (–8.75 µV) followed by the random nonword condition (–6.63 µV) and the real word condition (–5.62 µV) in the control group. In the right hemisphere, further tests also revealed a significant interaction effect of experimental condition and group (F(2, 46) = 6.05, p < .01, ES = .21) with the more negative mean amplitude for the reversed condition (–6.89 µV) and the random condition (–5.94 µV) compared to the real word condition (–1.40 µV) in the control group. However, there was no significant difference between the reversed and random condition in the right hemisphere.

DISCUSSION The present study was among the first attempts to investigate the time course of compound word processing in Chinese children with and without dyslexia using ERP methodology. The behavioral data results showed that both dyslexic and normal children had the most difficulty in processing the stimuli in the reversed nonword condition. In particular, dyslexic children performed significantly slower and less accurately than normal children did across experimental conditions. The ERP results revealed that in the time window of 300–500 msec (the N400 component), only children in the control group showed significant differences across experimental conditions, with the most negative response emerging for the reversed nonword condition, followed by the random nonword and real word conditions. Our results suggest that morphological information influences the processes of two-character compound words for children at the time window of the N400 component. Moreover, dyslexic children appear to show a weakness in processing morphological information, reflected by the lack of N400 effect across experimental conditions in dyslexic children. The current findings that children in the control group showed the most difficulty in processing the nonwords composed of real word morphemes that were reversed relative to the nonwords composed of two random single morphemes was reflected by a strong N400 effect found in the reversed condition. These findings are consistent with a recent ERP study in Chinese adults [accident] vs. [story]) with a more negative on reversible two-character words (e.g., N400 response found in the reversible word condition relative to the nonreversible word condition (Bai et al., 2011). A recent magnetoencephalographic (MEG) study on Finnish complex words (e.g., aamu + lla) also found that the processing of morphologically complex Finnish words appeared to be associated with a stronger and longer activation in the time window of 200–800 msec) in the left superior temporal cortex relative to the monomophemic words (Vartiainen et al., 2009).



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In the present study, the enhancement of the N400 amplitude in the reversed nonword condition in the control children may be attributed to the conflict between activation of the real word representation by recombining two morphemes in the reversed conditions and the actually presented transposed word. Specifically, the N400 effect found in this study may reflect the diffican be cult process of lexical access for the reversed nonwords. For example, the nonword (sea) by reversing the two morphemes restructured as a real Chinese compound word of and within the nonword . An interference might occur between the and when . And the processing of should be the process of (ocean), (sea), and processing (seas and oceans). In contrast, there is no semantic representation for the new combination of ) in the random nonword condition after reversing the two morphemes two morphemes (e.g., and ; therefore, there should not be interference occurring for this random nonword condition. The semantic composition between the real word activation and the present stimuli in the reversed condition might lead to more difficult and more cognitive demands to process the stimuli in the reversed condition compared to the stimuli in the random condition, which was reflected by a pronounced N400 effect found in the reversed condition relative to the random condition in this study. Interestingly, the N400 effect between the real word and reversed nonword conditions seemed to extend to a relatively late time window (around 500–1,000 msec). That is, the significant difference was found between the real and reversed conditions in the time window of 500–1,000 msec (LPC). This finding appears to be consistent with a recent ERP study focusing on Chinese adults’ compound word processing conducted by Bai and colleagues (2008), but their effect was found in the time window of the N400 component. Using auditory presentation, Bai et al. (2008) examined how the semantic and syntactic information of the first constituent of a two-character Chinese compound word influenced the processing of the whole word level meaning. They found an enhanced ERP response at the N400 component for the compounds whose meanings differed from the constituent meanings. The authors suggested that “the combination of distinct constituent meanings to form an overall compound meaning consumes processing resources.” In this study, the LPC effect between real and reversed conditions may reflect the fact that the semantic combination of the two individual morphemes within a reversed nonword may require more cognitive resources to process compared to the real words in children. The most striking finding of this study is that dyslexic children showed no difference across real word, the reversed nonword and the random nonword conditions, as reflected by the lack of N400-effect. This result suggests that dyslexic children might have a weakness in processing morphological structure information. One plausible explanation for the lack of N400 effect is that dyslexic children’s imperfect tacit knowledge of morphemes and morphological structure (e.g., Shu et al., 2006) leads to less than adequate, abstract, and integrative semantic representations of two-character compound words. Perhaps no fine-grained meaning entity of the two-character compound word has been established and stored in dyslexic children’s semantic networks. Thus, they are relatively less sensitive to the difference between reversed nonwords and nonwords by randomly combining two morphemes. There was no competing representation of reversed words activated in the mental lexicon among dyslexic children; this was different from that which might be observed in control children. Therefore, no difference was observed in the semantic integration of two types of stimuli reflected by the lack of N400 effect. The current ERP findings provide new evidence that morphological skill weakness contributes to word reading difficulty in Chinese.


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Another important point to be highlighted in the present study is the different patterns observed in the behavioral and ERP data. The behavioral data showed that dyslexic and control children showed difficulty in processing stimuli in the reversed condition; it seems likely that both the dyslexic and control children may be able to process the morphological information; the differences between the dyslexic and control children in the behavioral data were a matter of degree. The fact that the ERP data revealed actual group differences in the N400 component suggests that the differences between the dyslexic and control children in processing of morphological information is not only a matter of degree, but may reflect an underlying difference. Dissociations between behavioral and ERP measures have been reported in several previous studies (e.g., Brown & Hagoort, 1993; Kiefer & Brendel, 2006; Kiefer & Spitzer, 2000; Landi & Perfetti, 2007). Variations in reaction time and accuracy may be difficult to attribute to variations in a specific cognitive process due to the fact that reaction time and accuracy may reflect multiple cognitive processes (Landi & Perfetti, 2007). In contrast, ERP measure, well known for its excellent temporal resolution, provides a powerful tool by which to record continuous brain activity between a stimulus and a response, which makes it possible to determine which stage or stages of processing are affected by a specific experimental manipulation (Luck, 2005). Thus, the question as to whether the differences across conditions as reflected by behavioral data in the dyslexic group in our study really reflect dyslexic children’s processing of morphological information is hard to answer simply by looking at the behavioral responses. However, studies of the N400 component have been very useful in addressing this issue. As is described by Landi and Perfetti (2007) “Reaction time measures processes that are related to a response (e.g., decision processes) and those that vary as a function of cognition whereas the N400 may reflect only those that vary as a function of cognition (e.g., automatic spreading activation)” (p. 12). For the purpose of the present study, we can conclude that differences in the N400 during two-character compound words may be attributed to a cognitive process that is not always detected in behavioral data. However, our results are preliminary, requiring further exploration in future work. Notably, the samples in this study were Hong Kong Chinese children who use the traditional script, which is different from the simplified Chinese script mostly used in Mainland China. The largest difference between simplified and traditional Chinese script lies in the number of [simplified character] is 9, and the stroke for [the traditional strokes (e.g., the stroke for character] is 15). Interestingly, there are a few empirical studies that have suggested that simplified Chinese characters might be easier to write compared to traditional Chinese characters. Traditional Chinese characters, in contrast, may be easier to recognize for novices (see a review by Zhang & McBride-Chang, 2011). Thus, we should be cautious in generalizing our findings from one script to the other. In addition, the approach of word learning is “look and say” in Hong Kong. Moreover, there is no Pinyin phonetic system used in Hong Kong society. Therefore, the results found in the present study may not be completely applied to children who use simplified script. We speculate that children who use simplified script may show a reduced N400 effect across the conditions compared to Hong Kong Chinese children, because the activation of the real word in the reversed condition may be less strong than it is in Hong Kong children. Because teachers usually use a decomposition approach to teach a new word in Mainland, children may be more inclined to focus on each morpheme during processing of the stimuli in each condition. This issue is one to be explored in future research. Our findings suggest an exciting direction for new research on morphological processing in dyslexics and this could contribute to a fuller understanding of language processing skills in Chinese dyslexics.



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Moreover, in the present study the dyslexic group was matched to the control group only by age. It might be useful to include different age-matched and reading-level matched groups. By involving more age groups, further research could more clearly establish a developmental trajectory in this area. In addition, without a reading-level matched group, it might be difficult to conclude that differences found between the dyslexic and control groups in ERP response were dyslexia-specific. Those differences might be due to developmental aspects underlying reading. For example, research on developmental dyslexics of alphabetic languages has shown that reduced and delayed N400 effects are not dyslexia-specific but related to low reading performance (Schulz et al., 2009) and may also depend on age and tasks demands (Robichon, Besson, & Habib, 2002). In future studies, more subjects matched by age and reading abilities should be involved to replicate and further test the extent to which the current findings might hold across conditions. Despite these limitations, however, we have demonstrated the potentially important finding that children with dyslexia showed different ERP patterns compared to their age-matched control counterparts in processing two-character compound words. The salience of morphological information in processing of two-character compound words across dyslexic and typically developing children was clear overall. Such findings may be useful in understanding reading development and impairment in Chinese.

ACKNOWLEDGMENTS Thanks to Phil Duo Liu for helping us with the stimuli. We also thank all children and parents for their participation.

FUNDING This research was supported by the General Research Fund of the Hong Kong Special Administrative Region Research Grants Council (CUHK: 451811) and (HKIED: GRF-841311) to Catherine McBride and Kevin K. H. Chung respectively.

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