Acta Psychologica Sinica ›› 2023, Vol. 55 ›› Issue (8): 1207-1219.doi: 10.3724/SP.J.1041.2023.01207
• Reports of Empirical Studies • Next Articles
CAI Wenqi, ZHANG Xiangyang, WANG Xiaojuan(), YANG Jianfeng()
Received:
2022-06-15
Published:
2023-08-25
Online:
2023-05-12
Contact:
WANG Xiaojuan,YANG Jianfeng
E-mail:wangxj@snnu.edu.cn;yangjf@snnu.edu.cn
Supported by:
CAI Wenqi, ZHANG Xiangyang, WANG Xiaojuan, YANG Jianfeng. (2023). Time course of the integration of the morpho-semantics and the meaning of two-character Chinese compound words. Acta Psychologica Sinica, 55(8), 1207-1219.
Properties of the experimental stimulus | Transparent compound words | Opaque compound words | Mono- morphemic words |
---|---|---|---|
1st character transparency | 5.59(0.59) | 2.58(0.64) | / |
2nd character transparency | 5.66(0.72) | 2.76(0.75) | / |
Word transparency | 11.25(1.21) | 5.34(0.98) | / |
1st character number of radicals | 2.97(1.00) | 2.87(1.01) | 3.23(0.82) |
2nd character number of radicals | 3.03(0.72) | 3.00(0.98) | 3.13(0.78) |
Word number of radicals | 6.00(1.08) | 5.87(1.31) | 6.37(0.96) |
1st character number of strokes | 9.57(2.99) | 9.07(3.05) | 9.70(2.26) |
2nd character number of strokes | 9.80(2.44) | 9.70(2.84) | 10.07(2.21) |
Word number of strokes | 19.37(3.58) | 18.77(4.17) | 19.77(2.82) |
Word frequency | 3.17(3.35) | 4.66(9.43) | 1.90(2.01) |
Table 1 Relevant properties of the experimental stimulus
Properties of the experimental stimulus | Transparent compound words | Opaque compound words | Mono- morphemic words |
---|---|---|---|
1st character transparency | 5.59(0.59) | 2.58(0.64) | / |
2nd character transparency | 5.66(0.72) | 2.76(0.75) | / |
Word transparency | 11.25(1.21) | 5.34(0.98) | / |
1st character number of radicals | 2.97(1.00) | 2.87(1.01) | 3.23(0.82) |
2nd character number of radicals | 3.03(0.72) | 3.00(0.98) | 3.13(0.78) |
Word number of radicals | 6.00(1.08) | 5.87(1.31) | 6.37(0.96) |
1st character number of strokes | 9.57(2.99) | 9.07(3.05) | 9.70(2.26) |
2nd character number of strokes | 9.80(2.44) | 9.70(2.84) | 10.07(2.21) |
Word number of strokes | 19.37(3.58) | 18.77(4.17) | 19.77(2.82) |
Word frequency | 3.17(3.35) | 4.66(9.43) | 1.90(2.01) |
Figure 1. A. The average ERP waveforms induced by the different types of two-character words in the first character processing; B. effect of word type (top); morphological effect (middle); semantic transparency effect (bottom).
Source of variation | 300~400 ms | 460~700 ms | ||||
---|---|---|---|---|---|---|
F | p | η2 | F | p | η2 | |
Word type (2, 62) | 5.12 | 0.009 | 0.142 | 8.91 | 0.000 | 0.223 |
Region (2, 62) | 0.01 | 0.951 | 0.000 | 5.58 | 0.016 | 0.153 |
Hemisphere (2, 62) | 4.51 | 0.015 | 0.127 | 5.51 | 0.006 | 0.151 |
Region × Hemisphere (4, 124) | 5.38 | 0.002 | 0.148 | 11.45 | 0.000 | 0.270 |
Word type × Region (4, 124) | 1.80 | 0.154 | 0.055 | 3.13 | 0.036 | 0.092 |
Word type × Hemisphere (4, 124) | 2.00 | 0.123 | 0.061 | 1.83 | 0.150 | 0.056 |
Word type × Region × Hemisphere (8, 248) | 1.62 | 0.120 | 0.050 | 1.42 | 0.223 | 0.044 |
Table 2 Repeated-measures ANOVA result of the mean amplitude induced in the first character processing
Source of variation | 300~400 ms | 460~700 ms | ||||
---|---|---|---|---|---|---|
F | p | η2 | F | p | η2 | |
Word type (2, 62) | 5.12 | 0.009 | 0.142 | 8.91 | 0.000 | 0.223 |
Region (2, 62) | 0.01 | 0.951 | 0.000 | 5.58 | 0.016 | 0.153 |
Hemisphere (2, 62) | 4.51 | 0.015 | 0.127 | 5.51 | 0.006 | 0.151 |
Region × Hemisphere (4, 124) | 5.38 | 0.002 | 0.148 | 11.45 | 0.000 | 0.270 |
Word type × Region (4, 124) | 1.80 | 0.154 | 0.055 | 3.13 | 0.036 | 0.092 |
Word type × Hemisphere (4, 124) | 2.00 | 0.123 | 0.061 | 1.83 | 0.150 | 0.056 |
Word type × Region × Hemisphere (8, 248) | 1.62 | 0.120 | 0.050 | 1.42 | 0.223 | 0.044 |
Main effect | Post hoc analysis | 300~400 ms | 460~700 ms | ||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Region | Anterior - Posterior | / | / | / | 0.30 | 1.000 | 0.053 |
Anterior - Central | / | / | / | -4.02 | 0.001 | -0.726 | |
Posterior - Central | / | / | / | -3.26 | 0.008 | -0.579 | |
Hemisphere | Left - Right | -2.57 | 0.046 | -0.454 | -2.22 | 0.102 | -0.392 |
Left - Midline | 0.12 | 1.000 | 0.022 | -3.31 | 0.007 | -0.604 | |
Midline - Right | -2.79 | 0.027 | -0.523 | 0.83 | 1.000 | 0.150 |
Appendix Table 1 Results of post hoc analysis with the significant effect of region/hemisphere in the first character processing
Main effect | Post hoc analysis | 300~400 ms | 460~700 ms | ||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Region | Anterior - Posterior | / | / | / | 0.30 | 1.000 | 0.053 |
Anterior - Central | / | / | / | -4.02 | 0.001 | -0.726 | |
Posterior - Central | / | / | / | -3.26 | 0.008 | -0.579 | |
Hemisphere | Left - Right | -2.57 | 0.046 | -0.454 | -2.22 | 0.102 | -0.392 |
Left - Midline | 0.12 | 1.000 | 0.022 | -3.31 | 0.007 | -0.604 | |
Midline - Right | -2.79 | 0.027 | -0.523 | 0.83 | 1.000 | 0.150 |
Condition | 300~400 ms | 460~700 ms | |||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Anterior | Left - Right | / | / | / | / | / | / |
Left - Midline | / | / | / | / | / | / | |
Midline - Right | / | / | / | / | / | / | |
Central | Left - Right | -3.28 | 0.008 | -0.581 | -3.90 | 0.001 | -0.690 |
Left - Midline | 1.17 | 0.755 | 0.208 | -1.46 | 0.460 | -0.260 | |
Midline - Right | -5.24 | 0.000 | -0.581 | -2.43 | 0.063 | -0.434 | |
Posterior | Left - Right | / | / | / | -0.86 | 1.000 | -0.953 |
Left - Midline | / | / | / | -5.23 | 0.000 | -0.155 | |
Right - Midline | / | / | / | -3.90 | 0.001 | -0.690 |
Appendix Table 2 Pairwise comparison results of main effects of hemisphere in different regions in the first character processing
Condition | 300~400 ms | 460~700 ms | |||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Anterior | Left - Right | / | / | / | / | / | / |
Left - Midline | / | / | / | / | / | / | |
Midline - Right | / | / | / | / | / | / | |
Central | Left - Right | -3.28 | 0.008 | -0.581 | -3.90 | 0.001 | -0.690 |
Left - Midline | 1.17 | 0.755 | 0.208 | -1.46 | 0.460 | -0.260 | |
Midline - Right | -5.24 | 0.000 | -0.581 | -2.43 | 0.063 | -0.434 | |
Posterior | Left - Right | / | / | / | -0.86 | 1.000 | -0.953 |
Left - Midline | / | / | / | -5.23 | 0.000 | -0.155 | |
Right - Midline | / | / | / | -3.90 | 0.001 | -0.690 |
Figure 2. A. The average ERP waveforms induced by the different types of two-character words in the second character processing; B. effect of word type (top); morphological effect (middle); semantic transparency effect (bottom).
Source of variation | 260~420 ms | 480~700 ms | ||||
---|---|---|---|---|---|---|
F | p | η2 | F | p | η2 | |
Word type (2, 62) | 17.00 | 0.000 | 0.354 | 14.04 | 0.000 | 0.312 |
Region (2, 62) | 33.25 | 0.000 | 0.517 | 40.00 | 0.000 | 0.563 |
Hemisphere (2, 62) | 16.09 | 0.000 | 0.342 | 11.27 | 0.000 | 0.267 |
Region × Hemisphere (4, 124) | 3.18 | 0.030 | 0.093 | 2.13 | 0.111 | 0.064 |
Word type × Region (4, 124) | 8.37 | 0.000 | 0.213 | 7.40 | 0.000 | 0.193 |
Word type × Hemisphere (4, 124) | 2.03 | 0.095 | 0.061 | 5.49 | 0.000 | 0.150 |
Word type × Region ×Hemisphere (8, 248) | 0.95 | 0.449 | 0.030 | 0.51 | 0.746 | 0.016 |
Table 3 Repeated-measures ANOVA result of the mean amplitude induced in the second character processing
Source of variation | 260~420 ms | 480~700 ms | ||||
---|---|---|---|---|---|---|
F | p | η2 | F | p | η2 | |
Word type (2, 62) | 17.00 | 0.000 | 0.354 | 14.04 | 0.000 | 0.312 |
Region (2, 62) | 33.25 | 0.000 | 0.517 | 40.00 | 0.000 | 0.563 |
Hemisphere (2, 62) | 16.09 | 0.000 | 0.342 | 11.27 | 0.000 | 0.267 |
Region × Hemisphere (4, 124) | 3.18 | 0.030 | 0.093 | 2.13 | 0.111 | 0.064 |
Word type × Region (4, 124) | 8.37 | 0.000 | 0.213 | 7.40 | 0.000 | 0.193 |
Word type × Hemisphere (4, 124) | 2.03 | 0.095 | 0.061 | 5.49 | 0.000 | 0.150 |
Word type × Region ×Hemisphere (8, 248) | 0.95 | 0.449 | 0.030 | 0.51 | 0.746 | 0.016 |
Main effect | Post hoc analysis | 260~420 ms | 480~700 ms | ||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Region | Anterior - Posterior | -6.25 | 0.000 | -1.106 | -7.02 | 0.000 | -1.270 |
Anterior - Central | -6.75 | 0.000 | -1.204 | -7.98 | 0.000 | -1.410 | |
Central - Posterior | -3.76 | 0.002 | -0.665 | -1.90 | 0.199 | -0.353 | |
Hemisphere | Left - Right | -4.81 | 0.000 | -0.850 | -2.47 | 0.058 | -0.437 |
Left - Midline | -5.09 | 0.000 | -0.996 | -4.39 | 0.000 | -0.790 | |
Midline - Right | -0.14 | 1.000 | -0.026 | 2.50 | 0.053 | 0.470 |
Appendix Table 3 Results of post hoc analysis with the significant effect of region/hemisphere in the second character processing
Main effect | Post hoc analysis | 260~420 ms | 480~700 ms | ||||
---|---|---|---|---|---|---|---|
t | p | Cohen’s d | t | p | Cohen’s d | ||
Region | Anterior - Posterior | -6.25 | 0.000 | -1.106 | -7.02 | 0.000 | -1.270 |
Anterior - Central | -6.75 | 0.000 | -1.204 | -7.98 | 0.000 | -1.410 | |
Central - Posterior | -3.76 | 0.002 | -0.665 | -1.90 | 0.199 | -0.353 | |
Hemisphere | Left - Right | -4.81 | 0.000 | -0.850 | -2.47 | 0.058 | -0.437 |
Left - Midline | -5.09 | 0.000 | -0.996 | -4.39 | 0.000 | -0.790 | |
Midline - Right | -0.14 | 1.000 | -0.026 | 2.50 | 0.053 | 0.470 |
Condition | 260~420 ms | |||
---|---|---|---|---|
t | p | Cohen’s d | ||
Anterior | Left - Right | -2.21 | 0.105 | -0.390 |
Left - Midline | -5.02 | 0.000 | -0.920 | |
Midline - Right | 1.17 | 0.756 | 0.208 | |
Central | Left - Right | -5.13 | 0.000 | -0.909 |
Left - Midline | -3.15 | 0.011 | -0.581 | |
Midline - Right | -1.96 | 0.177 | -0.389 | |
Posterior | Left - Right | -3.43 | 0.005 | -0.614 |
Left - Midline | -4.42 | 0.000 | -0.850 | |
Midline - Right | 0.78 | 1.000 | 0.142 |
Appendix Table 4 Pairwise comparison results of main effects of hemisphere in different regions in the second character processing
Condition | 260~420 ms | |||
---|---|---|---|---|
t | p | Cohen’s d | ||
Anterior | Left - Right | -2.21 | 0.105 | -0.390 |
Left - Midline | -5.02 | 0.000 | -0.920 | |
Midline - Right | 1.17 | 0.756 | 0.208 | |
Central | Left - Right | -5.13 | 0.000 | -0.909 |
Left - Midline | -3.15 | 0.011 | -0.581 | |
Midline - Right | -1.96 | 0.177 | -0.389 | |
Posterior | Left - Right | -3.43 | 0.005 | -0.614 |
Left - Midline | -4.42 | 0.000 | -0.850 | |
Midline - Right | 0.78 | 1.000 | 0.142 |
[1] |
Bai C., Bornkessel-Schlesewsky I., Wang L. M., Hung Y., C, Schlesewsky M., & Burkhardt P. (2008). Semantic composition engenders an N400: Evidence from Chinese compounds. Neuroreport, 19(6), 695-699.
doi: 10.1097/WNR.0b013e3282fc1eb7 pmid: 18382290 |
[2] |
Bemis D. K., & Pylkkänen L. (2011). Simple composition: A magnetoencephalography investigation into the comprehension of minimal linguistic phrases. Journal of Neuroscience, 31(8), 2801-2814.
doi: 10.1523/JNEUROSCI.5003-10.2011 pmid: 21414902 |
[3] |
Beyersmann E., Iakimova G., Ziegler J. C., & Colé P. (2014). Semantic processing during morphological priming: An ERP study. Brain Research, 1579, 45-55.
doi: 10.1016/j.brainres.2014.07.010 pmid: 25020124 |
[4] |
Binder J. R., Desai R. H., Graves W. W., & Conant L. L. (2009). Where is the semantic system? a critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 2767-2796.
doi: 10.1093/cercor/bhp055 URL |
[5] |
Boylan C., Trueswell J. C., & Thompson-Schill S. L. (2017). Relational vs. attributive interpretation of nominal compounds differentially engages angular gyrus and anterior temporal lobe. Brain and Language, 169, 8-21.
doi: S0093-934X(15)30147-4 pmid: 28236762 |
[6] |
Brooks T. L., & Cid de Garcia D. (2015). Evidence for morphological composition in compound words using MEG. Frontiers in Human Neuroscience, 9, 215.
doi: 10.3389/fnhum.2015.00215 pmid: 25972798 |
[7] |
Cavalli E., Colé P., Badier J.-M., Zielinski C., Chanoine V., & Ziegler J. C. (2016). Spatiotemporal dynamics of morphological processing in visual word recognition. Journal of Cognitive Neuroscience, 28(8), 1228-1242.
doi: 10.1162/jocn_a_00959 pmid: 27027543 |
[8] | Chinese Linguistic Data Consortium. (2003). 现代汉语通用词表[Chinese lexicon] (CLDC-LAC 2003-001). Beijing, China: Tsinghua University, State Key Laboratory of Intelligent Technology and Systems, and Chinese Academy of Sciences, Institute of Automation. |
[9] | Coch D., Bares J., & Landers A. (2012). ERPs and morphological processing: The N400 and semantic composition. Cognitive, Affective, & Behavioral Neuroscience, 13(2), 355-370. |
[10] |
Cohen J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
doi: 10.1037//0033-2909.112.1.155 pmid: 19565683 |
[11] |
El-Bialy R., Gagné C. L., & Spalding T. L. (2013). Processing of English compounds is sensitive to the constituents’ semantic transparency. The Mental Lexicon, 8(1), 75-95.
doi: 10.1075/ml URL |
[12] |
El Yagoubi R., Chiarelli V., Mondini S., Perrone G., Danieli M., & Semenza C. (2008). Neural correlates of Italian nominal compounds and potential impact of headedness effect: An ERP study. Cognitive Neuropsychology, 25(4), 559-581.
doi: 10.1080/02643290801900941 pmid: 19086202 |
[13] |
Faul F., Erdfelder E., Buchner A., & Lang A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149-1160.
doi: 10.3758/BRM.41.4.1149 pmid: 19897823 |
[14] |
Flick G., Oseki Y., Kaczmarek A. R., Al Kaabi M., Marantz A., & Pylkkänen L. (2018). Building words and phrases in the left temporal lobe. Cortex, 106, 213-236
doi: S0010-9452(18)30190-4 pmid: 30007863 |
[15] |
Fiorentino R., Naito-Billen Y., Bost J., & Fund-Reznicek E. (2014). Electrophysiological evidence for the morpheme-based combinatoric processing of English compounds. Cognitive Neuropsychology, 31(1-2), 123-146.
doi: 10.1080/02643294.2013.855633 pmid: 24279696 |
[16] |
Fiorentino R., & Poeppel D. (2007). Processing of compound words: An MEG study. Brain and Language, 103(1), 18-19.
doi: 10.1016/j.bandl.2007.07.009 URL |
[17] |
Forgács B., Bohrn I., Baudewig J., Hofmann M. J., Pléh C., & Jacobs A. M. (2012). Neural correlates of combinatorial semantic processing of literal and figurative noun noun compound words. Neuroimage, 63(3), 1432-1442.
doi: 10.1016/j.neuroimage.2012.07.029 pmid: 22836179 |
[18] |
Frisson S., Niswander-Klement E., & Pollatsek A. (2008). The role of semantic transparency in the processing of English compound words. British Journal of Psychology, 99(1), 87-107.
doi: 10.1348/000712607X181304 URL |
[19] |
Gagné C. L., & Spalding T. L. (2016). Effects of morphology and semantic transparency on typing latencies in English compound and pseudocompound words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(9), 1489-1495.
doi: 10.1037/xlm0000258 URL |
[20] |
Gao F., Wang R., Armada-da-Silva P., Wang M., Lu H., Leong C., & Yuan Z. (2022). How the brain encodes morphological constraints during Chinese word reading: An EEG-fNIRS study. Cortex, 154, 184-196.
doi: 10.1016/j.cortex.2022.05.016 pmid: 35780754 |
[21] |
Han Y.-J., Huang S., Lee C.-Y., Kuo W.-J., & Cheng S. (2014). The modulation of semantic transparency on the recognition memory for two-character Chinese words. Memory & Cognition, 42(8), 1315-1324.
doi: 10.3758/s13421-014-0430-1 URL |
[22] |
Huang H. W., Lee C. Y., Tsai J. L., & Tzeng O. J. (2011). Sublexical ambiguity effect in reading Chinese disyllabic compounds. Brain and Language, 117(2), 77-87.
doi: 10.1016/j.bandl.2011.01.003 URL |
[23] |
Hsu C.-H., Pylkkänen L., & Lee C.-Y. (2019). Effects of morphological complexity in left temporal cortex: An MEG study of reading Chinese disyllabic words. Journal of Neurolinguistics, 49, 168-177.
doi: 10.1016/j.jneuroling.2018.06.004 URL |
[24] |
Ji H., Gagné C. L., & Spalding T. L. (2011). Benefits and costs of lexical decomposition and semantic integration during the processing of transparent and opaque English compounds. Journal of Memory and Language, 65(4), 406-430.
doi: 10.1016/j.jml.2011.07.003 URL |
[25] |
Kim J., Kang J., Kim J., & Nam K. (2022). Temporal dynamics of form and meaning in morphologically complex word processing: An ERP study on Korean inflected verbs. Journal of Neurolinguistics, 64, 101098.
doi: 10.1016/j.jneuroling.2022.101098 URL |
[26] |
Kim S., & Pylkkänen L. (2019). Composition of event concepts: Evidence for distinct roles for the left and right anterior temporal lobes. Brain and Language, 188, 18-27.
doi: S0093-934X(18)30133-0 pmid: 30530286 |
[27] |
Koester D., & Schiller N. O. (2008). Morphological priming in overt language production: Electrophysiological evidence from Dutch. Neuroimage, 42(4), 1622-1630.
doi: 10.1016/j.neuroimage.2008.06.043 pmid: 18674626 |
[28] |
Koester D., & Schiller N. O. (2011). The functional neuroanatomy of morphology in language production. Neuroimage, 55(2), 732-741.
doi: 10.1016/j.neuroimage.2010.11.044 pmid: 21109010 |
[29] |
Kuo L., & Anderson R. C. (2006). Morphological awareness and learning to read: A cross-language perspective. Educational Psychologist, 41, 161-180.
doi: 10.1207/s15326985ep4103_3 URL |
[30] |
Kwon Y., Nam K., & Lee Y. (2012). ERP index of the morphological family size effect during word recognition. Neuropsychologia, 50(14), 3385-3391.
doi: 10.1016/j.neuropsychologia.2012.09.041 pmid: 23036281 |
[31] |
Lavric A., Clapp A., & Rastle K. (2007). ERP evidence of morphological analysis from orthography: A masked priming study. Journal of Cognitive Neuroscience, 19(5), 866-877.
pmid: 17488210 |
[32] | Lee H.-J., Cheng S., Lee C.-Y., & Kuo W.-J. (2021). The neural basis of compound word processing revealed by varying semantic transparency and morphemic neighborhood size. Brain and Language, 221, 104985. |
[33] |
Leminen A., Smolka E., Duñabeitia J. A., Pliatsikas C. (2019). Morphological processing in the brain: The good (inflection), the bad (derivation) and the ugly (compounding). Cortex, 116, 4-44.
doi: S0010-9452(18)30266-1 pmid: 30268324 |
[34] | Libben G., Gagné C. L., & Dressler W. U. (2020). The representation and processing of compounds words. In V. Pirrelli, I. Plag & W. Dressler (Eds.), Word knowledge and word usage: A cross-disciplinary guide to the mental lexicon (pp. 336-352). Berlin, Boston: De Gruyter Mouton. |
[35] |
Liu P. D., & Mcbride-Chang C. (2010). Morphological processing of Chinese compounds from a grammatical view. Applied PsychoLinguistics, 31(4), 605-617.
doi: 10.1017/S0142716410000159 URL |
[36] |
Lo J. C. M., McBride C., Ho C. S., & Maurer U. (2019). Event- related potentials during Chinese single-character and two-character word reading in children. Brain and Cognition, 136, 103589.
doi: 10.1016/j.bandc.2019.103589 URL |
[37] |
Maurer U., Schulz E., Brem S., der Mark S. van, Bucher K., Martin E., & Brandeis D. (2011). The development of print tuning in children with dyslexia: Evidence from longitudinal ERP data supported by fMRI. Neuroimage, 57(3), 714-722.
doi: 10.1016/j.neuroimage.2010.10.055 pmid: 21040695 |
[38] |
Momenian M., Radman N., Rafipoor H., Barzegar M., & Weekes B. (2021). Compound words are decomposed regardless of semantic transparency and grammatical class: An fMRI study in Persian. Lingua, 259, 103120.
doi: 10.1016/j.lingua.2021.103120 URL |
[39] | Peng D., Ding G., Wang C., Taft M., & Zhu X. (1999). The processing of Chinese reversible words——the role of morphemes in lexical access. Acta Psychologica Sinica, 31(1), 36-46. |
[40] | Pollatsek A., Hyönä J., & Bertram R. (2000). The role of morphological constituents in reading Finnish compound words. Journal of Experimental Psychology Human Perception & Performance, 26(2), 820-833. |
[41] |
Rastle K., Davis M. H., & New B. (2004). The broth in my brother’s brothel: Morpho-orthographic segmentation in visual word recognition. Psychonomic Bulletin & Review, 11(6), 1090-1098.
doi: 10.3758/BF03196742 URL |
[42] |
Seghier M. L. (2013). The angular gyrus: Multiple functions and multiple subdivisions. Neuroscientist, 19(1), 43-61.
doi: 10.1177/1073858412440596 pmid: 22547530 |
[43] | Taft M. (2003). Morphological representation as a correlation between form and meaning. In E. Assink & D. Sandra (Eds.), Reading complex words (pp. 113-137). Amsterdam: Kluwer. |
[44] |
Taft M. (2004). Morphological decomposition and the reverse base frequency effect. The Quarterly Journal of Experimental Psychology Section A, 57(4), 745-765.
doi: 10.1080/02724980343000477 URL |
[45] |
Taft M., & Nguyen-Hoan M. (2010). A sticky stick? The locus of morphological representation in the lexicon. Language and Cognitive Processes, 25(2), 277-296.
doi: 10.1080/01690960903043261 URL |
[46] | Tsai C.-H. (1994). Effects of semantic transparency on the recognition of Chinese two-character words: Evidence for a dual-process model ( Unpublished master's thesis). National Chung Cheng University, Taiwan. |
[47] |
Tsang Y.-K., & Chen H.-C. (2013). Early morphological processing is sensitive to morphemic meanings: Evidence from processing ambiguous morphemes. Journal of Memory and Language, 68(3), 223-239.
doi: 10.1016/j.jml.2012.11.003 URL |
[48] |
Tsang Y.-K., & Chen H.-C. (2014). Activation of morphemic meanings in processing opaque words. Psychonomic Bulletin & Review, 21(5), 1281-1286.
doi: 10.3758/s13423-014-0589-2 URL |
[49] | Tsang Y. -K., & Zou Y. (2022). An ERP megastudy of Chinese word recognition. Psychophysiology, 59(11), e14111. |
[50] |
Tsang Y.-K., Zou Y., & Tse C.-Y. (2022). Semantic transparency in Chinese compound word processing: Evidence from mismatch negativity. Neuroscience, 490, 216-223.
doi: 10.1016/j.neuroscience.2022.03.007 URL |
[51] |
Wu J., Chang J., Qiu Y., & Joseph D. (2020). The temporal process of visual word recognition of Chinese compound: Behavioral and ERP evidences based on homographic morphemes. Acta Psychologica Sinica, 52(2), 113-127.
doi: 10.3724/SP.J.1041.2020.00113 |
[52] |
Wu Y., Duan R., Zhao S., & Tsang Y.-K. (2020). Processing ambiguous morphemes in Chinese compound word recognition: Behavioral and ERP evidence. Neuroscience, 446, 249-260.
doi: S0306-4522(20)30511-X pmid: 32795558 |
[53] | Wu Y., Tsang Y.-K., Wong A. W.-K., & Chen H.-C. (2017). The processing of homographic morphemes in Chinese: An ERP study. Language, Cognition and Neuroscience, 32(1), 102-116. |
[54] |
Yen M.-H., Tsai J.-L., Tzeng O. J.-L., & Huang D. L. (2008). Eye movements and parafoveal word processing in reading Chinese. Memory & Cognition, 36(5), 1033-1045.
doi: 10.3758/MC.36.5.1033 URL |
[55] |
Zhang L., & Pylkkänen L. (2015). The interplay of composition and concept specificity in the left anterior temporal lobe: An MEG study. Neuroimage, 111, 228-240.
doi: 10.1016/j.neuroimage.2015.02.028 pmid: 25703829 |
[56] |
Zhang R., ang Z., Wang X., & Yang J. (2021). N170 adaptation effect of the sub-lexical phonological and semantic processing in Chinese character reading. Acta Psychologica Sinica, 53(8), 807-820.
doi: 10.3724/SP.J.1041.2021.00807 |
[57] |
Zhao S., Wu Y., Li T., & Guo Q. (2017). Morpho-semantic processing in Chinese word recognition: An ERP study. Acta Psychologica Sinica, 49(3), 296-306.
doi: 10.3724/SP.J.1041.2017.00296 |
[58] |
Zhao S., Wu Y., Tsang Y.-K., Sui X., & Zhu Z. (2021). Morpho-semantic analysis of ambiguous morphemes in Chinese compound word recognition: An fMRI study. Neuropsychologia, 157, 107862.
doi: 10.1016/j.neuropsychologia.2021.107862 URL |
[59] | Zhou X. L., & Marslen-Wilson W. (1995). Morphological structure in the Chinese mental lexicon. Language, Cognition and Neuroscience, 10(6), 545-600 |
[60] |
Zhou X. L., Marslen-Wilson W., Taft M., & Shu H. (1999). Morphology, orthography, and phonology in reading Chinese compound words. Language and Cognitive Processes, 14(5-6), 525-565.
doi: 10.1080/016909699386185 URL |
[61] |
Ziegler J., & Pylkkänen L. (2016). Scalar adjectives and the temporal unfolding of semantic composition: An MEG investigation. Neuropsychologia, 89, 161-171.
doi: S0028-3932(16)30209-3 pmid: 27297726 |
[62] | Zou L., Packard J. L., Xia Z., Liu Y., & Shu H. (2016). Neural correlates of morphological processing: Evidence from Chinese. Frontiers in Human Neuroscience, 9, 714. |
[63] |
Zou L., Packard J. L., Xia Z., Liu Y., & Shu H. (2019). Morphological and whole-word semantic processing are distinct: Event related potentials evidence from spoken word recognition in Chinese. Frontiers in Human Neuroscience, 13, 133.
doi: 10.3389/fnhum.2019.00133 pmid: 31057382 |
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