Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T12:25:17.922Z Has data issue: false hasContentIssue false

The stranding of the ideography: A nonnegligible role of the spoken language

Published online by Cambridge University Press:  02 October 2023

Bohua Zhang
Affiliation:
School of Psychology, Shanghai University of Sport, Shanghai, China [email protected]; [email protected]
Xueping Hu
Affiliation:
College of Education, Huaibei Normal University, Huaibei, Anhui, China [email protected]
Qing Li
Affiliation:
Faculty of Psychology, Southwest University, Chongqing, China [email protected]
Antao Chen
Affiliation:
School of Psychology, Shanghai University of Sport, Shanghai, China [email protected]; [email protected]

Abstract

Morin suggested that one of the reasons for the difficulty in standardizing graphic codes is that the production of spoken language reduces the need for graphic codes. Here we try to extend their claims from a psychological perspective, which allows us to conclude that the puzzle of ideography is perhaps related to human psychological traits and psychological evolution.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Morin's standardization hypothesis is important for understanding the puzzle of ideography, but we suggest that understanding the ideographic puzzle, from psychological perspectives, has great potential value. Because people can be advantageous on learning, memory, and survival if spoken languages can be combined with graphic codes, people may prefer to combine spoken language with graphic codes and the target article should strengthen this part of the discussion. In this commentary, the effects that spoken languages have on graphic codes would be further discussed from three perspectives.

Perspective of error-driven learning

First, in terms of psychological mechanisms, the combination of spoken language and graphic codes contributes to standardization. Spoken language is the cheap and transient signal, and when people combine spoken language with graphic codes, they can verbally correct misunderstandings about the meaning of graphic codes, which is related to error-driven learning (Li et al., Reference Li, Hu, Li, Long, Gu, Tang and Chen2021). We have built an error-driven standardization model. Therefore, we can understand the mechanisms by which spoken language corrects misunderstandings of graphic codes at a psychological level (Fig. 1). As the figure shows, when the ideography appears, each interlocutor will have an initial expectation for it (expectation 1), followed by a first interaction with other interlocutors to exchange meanings (response 1). During the information communication, each interlocutor will receive information from other interlocutors (feedback 1), which may result in support, opposition, or supplement to the interlocutor's existing views and then give rise to prediction error (prediction error 1). When the prediction error happens (i.e., the expected view does not match the received feedback), the interlocutor will receive the error signal, first performing error monitoring to detect the mismatched information, then making targeted posterror attentional adjustments to integrate their information (Li, Wang, Li, & Chen, Reference Li, Wang, Li and Chen2022), and eventually becoming identical to the existing standard. The interlocutor generates new expectations (expectation 2) by correcting misinformation and updating common ground. This is followed by a second interaction to process individual standardization. In the interaction, the interlocutors support, debate, or correct each other, cycling through the above processes in order to revise and update the information several times. Until the end of the nth interaction, each interlocutor's prediction error would become zero (i.e., the expected viewpoint is the same as the received feedback). It means that the group has reached a consensus through the interaction, forming a uniform standard that can be shared and completing group standardization. In short, interlocutors standardize ideography by engaging in a cheap and transient interaction process of individual standardization combined with group standardization, which is compatible with the natural tendency to combine spoken language with graphic codes.

Figure 1. Error-driven standardization model of ideography supported by spoken language.

Perspective of memory

Second, combining spoken language with graphic codes is more beneficial to human memory. For example, both working memory and long-term memory are better with pronunciation added than without pronunciation (Hopkins & Edwards, Reference Hopkins and Edwards1972; MacLeod, Gopie, Hourihan, Neary, & Ozubko, Reference MacLeod, Gopie, Hourihan, Neary and Ozubko2010; Tan, Li, & Bai, Reference Tan, Li and Bai2022). Memory for pictures with pronunciation is also more effective than without pronunciation, when content-rich pictures are used as stimuli (Zormpa, Brehm, Hoedemaker, & Meyer, Reference Zormpa, Brehm, Hoedemaker and Meyer2019). From the neuroscience perspective, vocabulary memorization with pronunciation also has an activation advantage, compared with vocabulary memorization without pronunciation (Bailey et al., Reference Bailey, Bodner, Matheson, Stewart, Roddick, O'Neil and Newman2021). The learning hypothesis in the target article claims the human mind cannot memorize large numbers of pairings between meanings and visual symbols. However, we argue that humans are capable of remembering large numbers of pairings between meanings and visual symbols; it's just that memory efficiency and performance could be largely improved by combining pronunciation with visual symbols, therefore, humans choose the discarded less-efficient way of memorizing things.

Perspective of psychological evolution

As mentioned above, it can be demonstrated that adding spoken language enables humans to achieve better performance on learning and memory. Human's learning and memory are closely related to long-term psychological evolution, who may have evolved a tendency to learn and remember out of survival interests (Nairne, Thompson, & Pandeirada, Reference Nairne, Thompson and Pandeirada2007). For our ancestors, in order to solve the crisis of survival and repopulation, it was necessary to use a system of information that could be passed on from generation to generation. Thereby, the crisis could be better resolved and corresponding experiences could be preserved for a long time. For survival, our ancestors would have preferred a more efficient way of learning and memory. After some practice, this operation of combining spoken language does not need to consume cognitive resources, and have become an automatic operation after psychological evolution (Hu et al., Reference Hu, Wang, Gu, Luo, Yin, Wang and Chen2017; Yin, Sui, Chiu, Chen, & Egner, et al., Reference Yin, Sui, Chiu, Chen and Egner2019; Zhang, Ding, Li, Zhang, & Chen, Reference Zhang, Ding, Li, Zhang and Chen2013). Automatically combining spoken language with graphic codes may be an important reason for the historical absence of ideography.

Chinese characters

To sum up, from a psychological perspective, people will combine spoken language with graphic codes. Although Morin supposes Chinese is a code for spoken language, this opinion is absolute and controversial (Li, Reference Li1996; Zhang, Reference Zhang2011; Zhang et al., Reference Zhang, Fang, Du, Kong, Zhang and Xing2012; Zhu, Reference Zhu1995). If all Chinese characters are the record or code for spoken language, they cannot explain the existence of words that describe the shape of things but have no pronunciation clues in Chinese. For example, the Chinese oracle bones use such forms as , , and to represent sun, moon, and mountains, respectively. In modern Chinese characters, sun is “日,” moon is “月,” and mountain is “山.” Only 26% of the characters in the earliest oracle bones are associated with sound clues. Therefore, Chinese is a graphic code combined with spoken language, and cannot be interpreted absolutely as a record or encoding of spoken language (Zhang, Reference Zhang2011; Zhang et al., Reference Zhang, Fang, Du, Kong, Zhang and Xing2012; Zhu, Reference Zhu1995).

Conclusion

In summary, from a psychological perspective, this article suggests that because of the advantages of learning and memory, people will be inclined to choose a graphic code that incorporates spoken language as opposed to one that does not, and this operation of combining may have become automatic over time. People always automatically want to combine spoken language with graphic codes, which may be the reason why ideography has been missing since ancient times, and Chinese is a script that combines spoken language with graphic codes.

Financial support

This work was supported by the National Natural Science Foundation of China (Grant No. 32171040).

Competing interest

None.

References

Bailey, L. M., Bodner, G. E., Matheson, H. E., Stewart, B. M., Roddick, K., O'Neil, K., … Newman, A. J. (2021). Neural correlates of the production effect: An fMRI study. Brain and Cognition, 152, 105757.CrossRefGoogle ScholarPubMed
Hopkins, R. H., & Edwards, R. E. (1972). Pronunciation effects in recognition memory. Journal of Verbal Learning and Verbal Behavior, 11(4), 534537.CrossRefGoogle Scholar
Hu, X. P., Wang, X. P., Gu, Y., Luo, P., Yin, S. H., Wang, L. J., … Chen, A. T. (2017). Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis. Brain and Language, 173, 6775.CrossRefGoogle ScholarPubMed
Li, G. Y. (1996). On the morphological and meaning systems of Chinese characters with morphemes. Social Science in China, 3, 186193.Google Scholar
Li, Q., Hu, N., Li, Y. L., Long, Q. S., Gu, Y., Tang, Y. C., & Chen, A. T. (2021). Error-induced adaptability: Behavioral and neural dynamics of response-stimulus interval modulations on posterror slowing. Journal of Experimental Psychology: General, 150(5), 851863.CrossRefGoogle ScholarPubMed
Li, Q., Wang, J., Li, Z. F., & Chen, A. T. (2022). Decoding the specificity of post-error adjustments using EEG-based multivariate pattern analysis. Journal of Neuroscience, 42(35), 68006809.CrossRefGoogle ScholarPubMed
MacLeod, C. M., Gopie, N., Hourihan, K. L., Neary, K. R., & Ozubko, J. D. (2010). The production effect: Delineation of a phenomenon. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(3), 671685.Google ScholarPubMed
Nairne, J. S., Thompson, S. R., & Pandeirada, J. N. S. (2007). Adaptive memory: Survival processing enhances retention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(2), 263273.Google ScholarPubMed
Tan, X. J., Li, X., & Bai, X. J. (2022). The influence of reading mode and learning frequency on production effect of Chinese written word. Studies of Psychology and Behavior, 20(5), 600606.Google Scholar
Yin, S., Sui, J., Chiu, Y. C., Chen, A., & Egner, T. (2019). Automatic prioritization of self-referential stimuli in working memory. Psychological Science, 30(3), 415423.CrossRefGoogle ScholarPubMed
Zhang, L., Ding, C., Li, H., Zhang, Q., & Chen, A. (2013). The influence of attentional control on stimulus processing is category specific in Stroop tasks. Psychological Research, 77(5), 599610.CrossRefGoogle ScholarPubMed
Zhang, X. X. (2011). Meaning–spelling theory of the Chinese characters: Insight into the nature of written Chinese from the perspective of cognitive psychology. Journal of South China Normal University (Social Science Edition), 4, 513.Google Scholar
Zhang, X. X., Fang, Z., Du, Y. C., Kong, L. Y., Zhang, Q., & Xing, Q. (2012). The centro-parietal N200: An event-related potential component specific to Chinese visual word recognition. China Science Bulletin, 57(1), 116.Google Scholar
Zhu, B. X. (1995). On the original relationship between Chinese characters and the Chinese language. Jianghan Forum, 3, 79–82.Google Scholar
Zormpa, E., Brehm, L. E., Hoedemaker, R. S., & Meyer, A. S. (2019). The production effect and the generation effect improve memory in picture naming. Memory (Hove, England), 27(3), 340352.CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. Error-driven standardization model of ideography supported by spoken language.