A behavioral and ERP study of the role of radical position distribution in character recognition : evidence for position-specific radical representation

The present study investigated the role of radical position distribution in character recognition using a masked primed lexical decision task. Thirty-four normal adults (mean age: 22 years old) who were skilled readers of Chinese and native Cantonese speakers participated in the study. Radicals were used as the primes and complex characters were used as the targets. Participants were asked to judge whether the complex characters presented is a real character or not as quickly and accurately as possible. Response latencies, accuracy rates and ERP data were recorded. Behavioral data indicated that characters with position-biased related primes were recognized significantly faster than those with position-biased unrelated ones and the reverse was observed in position-neutral radical priming. ERP data only observed lexicality effect in N400 component. The findings have demonstrated the complex role of radical position distribution in character recognition and substantiated the argument for position-specific radical representation. A Behavioral and ERP Study of Radical Feature 3 A Behavioral and ERP Study of the Role of Radical Position Distribution in Character Recognition: Evidence for Position-Specific Radical Representation The Chinese writing system is a non-alphabetic script with words composed of characters. Each character occupies a squared-shaped space that is constructed by combination of stroke patterns. Particular grouping of strokes form radicals and they form constituent of complex characters (Hoosain, 1991). Radical can be defined as “contiguity of its strokes on the one hand and recurrence in different characters on the other. ” (Taft & Zhu, 1997, p.761). Many complex characters contain radicals carrying phonetic (e.g. 椰, jE21 contain phonetic radical 耶, jE21) or semantic (e.g. 樹 “tree” contain semantic radical 木 “wood”) cues (Hoosain, 1991). Different spatial arrangement of radicals results in different complex character configurations. Horizontal (AB 說, ABC 辦), vertical (呆) and semi-enclosed (送) configuration (the reader may refer to Appendix A for phonetics and meanings of Chinese characters appeared in this paper) are some examples (Chen, 1996). Studies investigating different aspects of radical feature using different tasks and paradigms had provided evidence supporting radical as an important level of representation in Chinese orthographic processing system. For example, considering radical form, Taft and Zhu (1997) found an effect of radical type frequency (number of characters containing that radical) and radical status (real or invented radical) in a lexical decision task. Considering radical function, Feldman and Siok (1997) found an effect of combinability (whether a radical can enter into few or many combinations in compound characters) for semantic and phonetic radicals in lexical decision. Zhou and Marslen-Wilson (1999) observed priming effects in a primed lexical decision task when the simple character target is semantically related to the phonetic radical in the complex character prime even though the prime and target were not semantically related. While it is evident that the radical acts as a sublexical processing unit, a question A Behavioral and ERP Study of Radical Feature 4 arises regarding its nature in orthographic processing. In Chinese script, radicals can be located in different positions of characters (Hoosain, 1991). For example, a radical (e.g. 田) can be located at the left (e.g. 略), the right (e.g. 細), the top (e.g. 胃) or the bottom (e.g. 雷) of characters. With respect to this feature, the issue of position specificity of radicals has been intensively investigated but with contradictory results. On the one hand, Taft and Zhu (1997) found that character decision latency was influenced by radical position frequency (number of characters containing that radical in that position). Specifically, for two characters of equal character frequency, the one with high radical position frequency (e.g. 鴣 containing 鳥 which is located at the right of many characters) was easier to be recognized than the one with low radical position frequency (e.g. 捫 containing 門 which is located at the right of few characters). Furthermore, Taft, Zhu, and Peng (1999) observed no interference in character recognition when transposable characters were presented in both lexical decision and naming tasks. Specifically, characters containing transposable radicals (e.g. 呆 and 杏) had response latencies and error rates comparable to those containing non-transposable radicals (e.g. 孕). This suggested that the same radical occurring in different positions were represented differently. In a priming study, Ding, Peng, and Taft (2004) further observed that the priming effect was significant when prime-target characters shared a radical in the same position (e.g. 軀-樞) but was not significant when they shared a radical in different positions (e.g. 歐-樞). In short, these results suggest that the radical is specified for position information which is sensitive to position frequency and could help distinguish the same radical unit occurring in different positions. On the other hand, Tsang and Chen (2009) found that participants would mistakenly perceive the target character as being one of the two preceding source characters when target-source characters have shared radical(s). They found this effect to be comparable no A Behavioral and ERP Study of Radical Feature 5 matter whether the shared radical is in the same (e.g. 拮 preceded by 結 and 栓) or different (e.g. 頡 preceded by 結 and 栓) positions across source-target. The authors argued this result to position-general radicals which would activate characters containing it in whatever position, therefore resulting in the same degree of illusory effect abovementioned. They also argued that the findings were consistent with Lai and Huang’s study (as cited in Tsang & Chen, 2009) which was not explicitly addressing radical position-specificity but nonetheless implied position-general over position-specific radical units. The present study was therefore motivated by the inconsistent findings concerning position-specificity of radical representation, and would advance the discussion by exploring how radical position distribution influences character recognition. Previous literature studying radical position-specificity was based on the description of a specific position occupied by a radical. Another way of conceiving radical position is the relative distribution of a radical across all possible positions in characters containing it. As mentioned, radicals can occupy different positions in characters, it is worth noting that some radicals have a usual location. For example, some radicals (e.g. 冊) can occur in different positions but occur more frequently on the right (e.g. 珊) than on the left (e.g. 刪) of a character (Biased radical distribution). However, some radicals (e.g. 公) occur equally frequently in different positions (e.g. 訟, 頌, 翁 etc) of a character (Neutral radical distribution). These two distribution patterns (biased and neutral) had probably been mixed up in the conceptualization of radical position in previous literature. For example, in Taft and Zhu’s (1997) second experiment, stimuli for each experimental condition were matched in terms of character frequency and position-sensitive radical frequency. However, according to the Hong Kong Corpus of Chinese NewsPaper (Leung & Lau, 2011), for two characters matched on frequency (e.g. 珊: 87.97 per million, 松: 70.52 per million) and position-sensitive radical frequency (e.g. 冊 as A Behavioral and ERP Study of Radical Feature 6 right radical: 100.45 per million, 公 as right radical: 112.19 per million), the critical radicals can be either with biased (冊) or neutral (公) distribution. Regarding this, radical position was manipulated in terms of relative position distribution which is a finer conceptualization to further investigate position-specificity of radical representation in the current study. If position information is specified at the radical level, such information should be sensitive to position distribution which is an inherent property of a radical. Specifically, if characters containing a radical with biased distribution are recognized differently to those containing neutrally distributed radicals, the argument for position-specific radicals will be substantiated. To test this hypothesis, the present study employed a lexical decision task using a masked priming paradigm which can reveal how information in the prime influences target processing (Grainger & Jacob, 1999) with further processing of the prime being blocked by the mask (Holcomb & Grainger, 2006). Simple radicals with biased or neutral distribution were used as primes. Complex characters containing either type of prime were used as targets. According to Taft’s (2006) Chinese word processing model, words are processed hierarchically from feature, to radical, then to complex character and word level. Thus, higher-level character processing would be affected by lower-level radical processing. In other words, attributes of radical would influence character processing. If radicals with different position distributions are processed differently at lower-level radical processing, higher-level character processing will be affected. Therefore, by contrasting recognition of complex characters containing radical with different position distributions, the role of radical position distribution in character recognition can be revealed. The role of radical position distribution was investigated in two prime durations, 48 ms and 96 ms. Theoretically, when the prime is presented for different durations, different amounts of information would be activated from the prime (Perfetti & Tan, 1998). The manipulation of prime duration would reveal how different amounts of pre-activated A Behavioral and ERP Study of Radical Feature 7 information influence subsequent characte