The Antipriming Effect of Chinese Character Identification

Abstract

Abstract: The antipriming effect of Chinese character identification was explored by three serious experiments using the priming experimental paradigm including a baseline measurement to test the theory of superimposed representations of memory. The results of Experiment 1 showed that compared to baseline, priming increased accuracy rates of identifying primed characters; however, it decreased significantly accuracy rates of identifying unprimed characters which had the same parts of character shapes as primed characters. The results of Experiments 2 and 3 indicated that the antipriming effect was not caused by attention bias or participants' fatigue. In conclusion, antipriming effect existed in identifying Chinese characters, and it provided new evidence to support superimposed representation theory.

Key words: antipriming, Chinese character identification, superimposed representation

摘要： 为验证记忆的重叠表征理论，采用包括基线测量的启动实验范式，通过三个系列实验探讨了汉字识别的反启动效应。实验一结果表明，与基线条件相比，启动显著提高了启动的汉字的识别正确率，但却显著降低了与该汉字部分字形相同的未启动的汉字的识别正确率；实验二和三结果显示，反启动效应不是源于注意偏向和疲劳因素。因此，汉字识别中存在反启动效应，这为重叠表征理论提供了新的支持证据。

关键词: 反启动, 汉字识别, 重叠表征

CLC Number:

B842

ZHANG Feng. The Antipriming Effect of Chinese Character Identification[J]. Studies of Psychology and Behavior, 2018, 16(4): 458-463.

张锋. 汉字识别的反启动效应[J]. 心理与行为研究, 2018, 16(4): 458-463.

References

陈宝国, 王立新, 彭聃龄. (2006). 高、低频汉字形音义激活的时间进程. 心理与行为研究, 4(4), 252-257.
国家语言文字工作委员会, 国家标准局. (1992). 现代汉语字频统计表. 北京:语文出版社.
金志成, 李广平. (1995). 在汉字视觉识别中字形和字音作用的实验研究. 心理科学, 18(3), 129-133.
李宁, 梁宁建. (2014). 多层次格式塔双向加工模型:汉字输入中形码的认知加工机制. 心理与行为研究, 12(4), 441-446.
李平. (2002). 语言习得的联结主义模式. 当代语言学, 4(3), 164-175.
沈模卫, 李忠平, 朱祖祥. (1997). 部件启动对合体汉字字形识别的影响. 心理科学, 20(3), 206-211.
张锋, 黄希庭, 郭秀艳. (2008). 重复启动对时序知觉的影响. 心理学报, 40(7), 766-773.
张锋, 黄希庭, 郭秀艳. (2009). 时序知觉重复启动效应的作用机制. 心理学报, 41(3), 233-241.
Deason, R. G. (2008). Masked antipriming:A behavioral and event-related potential examination of short-term antipriming effects (Unpublished doctoral dissertation). University of Minnesota.
Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425-2430.
Ishai, A., Ungerleider, L. G., Martin, A., Schouten, J. L., & Haxby, J. V. (1999). Distributed representation of objects in the human ventral visual pathway. Proceedings of the National Academy of Sciences of the United States of America, 96, 9379-9384.
Kobatake, E., Wang, G., & Tanaka, K. (1998). Effects of shape-discrimination training on the selectivity of inferotemporal cells in adult monkeys. Journal of Neurophysiology, 80(1), 324-330.
Marsolek, C. J. (2008). What antipriming reveals about priming. Trends in Cognitive Sciences, 12(5), 176-181.
Marsolek, C. J., Deason, R. G., Ketz, N. A., Ramanathan, P., Bernat, E. M., Steele, V. R., … Schnyer, D. M. (2010). Identifying objects impairs knowledge of other objects:A relearning explanation for the neural repetition effect. NeuroImage, 49(2), 1919-1932.
Marsolek, C. J., Schnyer, D. M., Deason, R. G., Ritchey, M., & Verfaellie, M. (2006). Visual antipriming:Evidence for ongoing adjustments of superimposed visual object representations. Cognitive, Affective, & Behavioral Neuroscience, 6(3), 163-174.
Masson, M. E. J. (1995). A distributed memory model of semantic priming. Journal of Experimental Psychology:Learning, Memory, & Cognition, 21, 3-23.
McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995). Why there are complementary learning systems in the hippocampus and neocortex:Insights from the successes and failures of connectionist models of learning and memory. Psychological Review, 102, 419-457.
McCloskey, M., & Cohen, N. J. (1989). Catastrophic interference in connectionist networks:The sequential learning problem. Psychology of Learning & Motivation, 24, 109-165.
Milin, P., Feldman, L. B., Ramscar, M., Hendrix, P., & Baayen, R. H. (2017). Discrimination in lexical decision. PLoS One, 12(2), e0171935.
Morton, J. (1979). Facilitation in word recognition:Experiments causing change in the logogen model. In P. A. Kolers, M. E. Wrolstad, & H. Bouma (Eds.), Processing of visible language (Vol. 13, pp. 259-268). Boston, MA:Springer.
Ramanathan, P., Kennedy M. R. T., & Marsolek, C. J. (2014). Implicit memory influences on metamemory during verbal learning after traumatic brain injury. Journal of Speech, Language, and Hearing Research, 57, 1817-1830.
Roediger, H. L. (2003). Reconsidering implicit memory. In J. S. Bowers & C. J. Marsolek (Eds.), Rethinking implicit memory (pp. 3-18). Oxford:Oxford University Press.
Rouder, J. N., Ratcliff, R., & McKoon, G. (2000). A neural network model of implicit memory for object recognition. Psychological Science, 11, 13-19.
Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523-568.
Shiffrin, R. M., & Steyvers, M. (1997). A model for recognition memory:REM-retrieving effectively from memory. Psychonomic Bulletin & Review, 4(2), 145-166.
Sigala, N., & Logothetis, N. K. (2002). Visual categorization shapes feature selectivity in the primate temporal cortex. Nature, 415, 318-320.