fNIRS evidence for left middle frontal gyrus involved in visual-spatial analysis of Chinese characters

doi:10.3724/SP.J.1041.2023.00685

Abstract

Abstract:

The left middle frontal gyrus (MFG) is a typical brain region identified in studies of Chinese character reading brain mechanisms, it exhibits specific activation in Chinese character reading. A common interpretation suggests that it is responsible for the unique visual-spatial processing of Chinese characters. However, this interpretation is not supported by direct evidence. This study manipulated the spatial frequency of visually presented Chinese character materials and explored this issue by using functional Near-Infrared Spectroscopy (fNIRS) techniques. By constructing a 3 (character type: Real character, Pseudo character, and Artificial character) × 3 (spatial frequency: Full spatial frequency, Low spatial frequency, and High spatial frequency) repeated-measures experimental design, The blood oxygen concentration changes in the left MFG were recorded as participants completed a one-back task with repeated stimulus detection. It was found that the left MFG showed a significant main effect of character type, that was, Pseudo characters required more MFG activation than Real and Artificial characters. Moreover, the left MFG also showed a significant interaction effect of character type and spatial frequency, with Pseudo characters more activated MFG than Real and Artificial characters in the Low spatial frequency condition, while no significant activation difference of character types was found under the other two spatial frequency conditions. The results suggested that the left MFG was indeed sensitive to the spatial information of Chinese characters, more MFG activation was required especially in the Pseudo characters condition that required more graphemic/orthographic processing and in the processing of low spatial frequency information. The findings provided direct evidence that the left MFG was involved in the visuospatial processing of Chinese characters.

Key words: Chinese character reading, middle frontal gyrus, spatial frequency, fNIRS

CHEN Fakun, CHEN Tian, CAI Wenqi, WANG Xiaojuan, YANG Jianfeng. (2023). fNIRS evidence for left middle frontal gyrus involved in visual-spatial analysis of Chinese characters. Acta Psychologica Sinica, 55(5), 685-695.

Figures/Tables 11

References 51

[1]	Allen, P. A., Smith, A. F., Lien, M.-C., Kaut, K. P., & Canfield, A. (2009). A multistream model of visual word recognition. Attention Perception & Psychophysics, 71(2), 281-296. doi: 10.3758/APP.71.2.281 URL
[2]	Ashtiani, M. N., Kheradpisheh, S. R., Masquelier, T., & Ganjtabesh, M. (2017). Object categorization in finer levels relies more on higher spatial frequencies and takes longer. Frontiers in Psychology, 8, 1261. doi: 10.3389/fpsyg.2017.01261 pmid: 28790954
[3]	Brigadoi, S., Ceccherini, L., Cutini, S., Scarpa, F., Scatturin, P., Selb, J., ... Cooper, R. J. (2014). Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data. Neuroimage, 85(Pt. 1), 181-191. doi: 10.1016/j.neuroimage.2013.04.082 URL
[4]	Calderone, D. J., Hoptman, M. J., Martinez, A., Nair-Collins, S., Mauro, C. J., Bar, M., ... Butler, P. D. (2013). Contributions of low and high spatial frequency processing to impaired object recognition circuitry in schizophrenia. Cerebral Cortex, 23(8), 1849-1858. doi: 10.1093/cercor/bhs169 URL
[5]	Cao, F., & Perfetti, C. A. (2016). Neural signatures of the reading-writing connection: Greater involvement of writing in Chinese reading than English reading. Plos One, 11(12), e0168414.
[6]	Cui, X., Bray, S., Bryant, D. M., Glover, G. H., & Reiss, A. L. (2011). A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. Neuroimage, 54(4), 2808-2821. doi: 10.1016/j.neuroimage.2010.10.069 pmid: 21047559
[7]	Defenderfer, J., Kerr-German, A., Hedrick, M., & Buss, A. T. (2017). Investigating the role of temporal lobe activation in speech perception accuracy with normal hearing adults: An event-related fNIRS study. Neuropsychologia, 106, 31-41. doi: S0028-3932(17)30330-5 pmid: 28888891
[8]	Feng, X. X., Altarelli, I., Monzalvo, K., Ding, G. S., Ramus, F., Shu, H., ... Dehaene-Lambertz, G. (2020). A universal reading network and its modulation by writing system and reading ability in French and Chinese children. eLife, 9, e54591.
[9]	Fiset, D., Blais, C., Ethier-Majcher, C., Arguin, M., Bub, D., & Gosselin, F. (2008). Features for identification of uppercase and lowercase letters. Psychological Science, 19(11), 1161-1168. doi: 10.1111/j.1467-9280.2008.02218.x pmid: 19076489
[10]	Guo, X. C. (1999). Effects of spatial frequency, strokes and word frequency on Chinese character recognition. Chinese Journal of Ergonomics, 5(4), 5-11.
[11]	Horie, S., Yamasaki, T., Okamoto, T., Kan, S., Ogata, K., Miyauchi, S., & Tobimatsu, S. (2012). Distinct role of spatial frequency in dissociative reading of ideograms and phonograms: An fMRI study. Neuroimage, 63(2), 979-988. doi: 10.1016/j.neuroimage.2012.03.046 pmid: 22480729
[12]	Horie, S., Yamasaki, T., Okamoto, T., Nakashima, T., Ogata, K., & Tobimatsu, S. (2012). Differential roles of spatial frequency on reading processes for ideograms and phonograms: A high-density ERP study. Neuroscience Research, 72(1), 68-78. doi: 10.1016/j.neures.2011.10.003 pmid: 22020307
[13]	Huppert, T. J., Franceschini, M. A., Diamond, S. G., & Boas, D. A. (2009). HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain. Applied Optics, 48(10), D280-D298.
[14]	Jordan, T. R., Dixon, J., McGowan, V. A., Kurtev, S., & Paterson, K. B. (2016). Fast and slow readers and the effectiveness of the spatial frequency content of text: Evidence from reading times and eye movements. Journal of Experimental Psychology. Human Perception and Performance, 42(8), 1066-1071. doi: 10.1037/xhp0000234 URL
[15]	Kuo, W. J., Yeh, T. C., Lee, J. R., Chen, L. F., Lee, P. L., Chen, S. S., ... Hsieh, J. C. (2004). Orthographic and phonological processing of Chinese characters: An fMRI study. Neuroimage, 21(4), 1721-1731. doi: 10.1016/j.neuroimage.2003.12.007 URL
[16]	Kveraga, K., Boshyan, J., & Bar, M. (2007). Magnocellular projections as the trigger of top-down facilitation in recognition. Journal of Neuroscience, 27(48), 13232-13240. doi: 10.1523/JNEUROSCI.3481-07.2007 pmid: 18045917
[17]	Kwon, H., Reiss, A. L., & Menon, V. (2002). Neural basis of protracted developmental changes in visuo-spatial working memory. Proceedings of the National Academy of Sciences of the United States of America, 99(20), 13336-13341. doi: 10.1073/pnas.162486399 pmid: 12244209
[18]	Kwon, M., & Legge, G. E. (2012). Spatial-frequency requirements for reading revisited. Vision Research, 62, 139-147. doi: 10.1016/j.visres.2012.03.025 pmid: 22521659
[19]	Leonova, A., Pokorny, J., & Smith, V. C. (2003). Spatial frequency processing in inferred PC- and MC-pathways. Vision Research, 43(20), 2133-2139. pmid: 12855249
[20]	Liu, C., Zhang, W. T., Tang, Y. Y., Mai, X. Q., Chen, H.-C., Tardif, T., & Luo, Y. J. (2008). The Visual Word Form Area: Evidence from an fMRI study of implicit processing of Chinese characters. Neuroimage, 40(3), 1350-1361. doi: 10.1016/j.neuroimage.2007.10.014 pmid: 18272399
[21]	Liu, J. Q., Zhang, R. Q., Geng, B. B., Zhang, T. Y., Yuan, D., Otani, S., & Li, X. (2019). Interplay between prior knowledge and communication mode on teaching effectiveness: Interpersonal neural synchronization as a neural marker. Neuroimage, 193, 93-102. doi: S1053-8119(19)30171-5 pmid: 30851445
[22]	Liu, Y., Dunlap, S., Fiez, J., & Perfettil, C. A. (2007). Evidence for neural accommodation to a writing system following learning. Human Brain Mapping, 28(11), 1223-1234. doi: 10.1002/hbm.20356 pmid: 17274024
[23]	Mercure, E., Dick, F., Halit, H., Kaufman, J., & Johnson, M. H. (2008). Differential lateralization for words and faces: Category or psychophysics? Journal of Cognitive Neuroscience, 20(11), 2070-2087. doi: 10.1162/jocn.2008.20137 pmid: 18416685
[24]	Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46-59. doi: 10.1002/hbm.20131 pmid: 15846822
[25]	Perfetti, C., Cao, F., & Booth, J. (2013). Specialization and universals in the development of reading skill: How Chinese research informs a universal science of reading. Scientific Studies of Reading, 17(1), 5-21. doi: 10.1080/10888438.2012.689786 pmid: 24744605
[26]	Perfetti, C. A., Liu, Y., Fiez, J., Nelson, J., Bolger, D. J., & Tan, L. H. (2007). Reading in two writing systems: Accommodation and assimilation of the brain’s reading network. Bilingualism: Language and Cognition, 10(2), 131-146. doi: 10.1017/S1366728907002891 URL
[27]	Perfetti, C. A., Liu, Y., & Tan, L. H. (2005). The lexical constituency model: Some implications of research on Chinese for general theories of reading. Psychological Review, 112(1), 43-59. pmid: 15631587
[28]	Petras, K., Ten Oever, S., Jacobs, C., & Goffaux, V. (2019). Coarse-to-fine information integration in human vision. Neuroimage, 186, 103-112. doi: S1053-8119(18)32070-6 pmid: 30403971
[29]	Peyrin, C., Michel, C. M., Schwartz, S., Thut, G., Seghier, M., Landis, T., ... Vuilleumier, P. (2010). The neural substrates and timing of top-down processes during coarse-to-fine categorization of visual scenes a combined fMRI and ERP study. Journal of Cognitive Neuroscience, 22(12), 2768-2780. doi: 10.1162/jocn.2010.21424 URL
[30]	Pinti, P., Tachtsidis, I., Hamilton, A., Hirsch, J., Aichelburg, C., Gilbert, S., & Burgess, P. W. (2020). The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Annals of the New York Academy of Sciences, 1464(1), 5-29.
[31]	Roberts, D. J., Woollams, A. M., Kim, E., Beeson, P. M., Rapcsak, S. Z., & Ralph, M. A. L. (2013). Efficient visual object and word recognition relies on high spatial frequency coding in the left posterior fusiform gyrus: Evidence from a case-series of patients with ventral occipito-temporal cortex damage. Cerebral Cortex, 23(11), 2568-2580. doi: 10.1093/cercor/bhs224 URL
[32]	Sato, H., Kiguchi, M., Maki, A., Fuchino, Y., Obata, A., Yoro, T., & Koizumi, H. (2006). Within-subject reproducibility of near-infrared spectroscopy signals in sensorimotor activation after 6 months. Journal of Biomedical Optics, 11(1), 014021.
[33]	Siok, W. T., Niu, Z., Jin, Z., Perfetti, C. A., & Tan, L. H. (2008). A structural-functional basis for dyslexia in the cortex of Chinese readers. Proceedings of the National Academy of Sciences of the United States of America, 105(14), 5561-5566. doi: 10.1073/pnas.0801750105 pmid: 18391194
[34]	Siok, W. T., Perfetti, C. A., Jin, Z., & Tan, L. H. (2004). Biological abnormality of impaired reading is constrained by culture. Nature, 431(7004), 71-76. doi: 10.1038/nature02865 URL
[35]	Stoeckel, M. C., & Binkofski, F. (2010). The role of ipsilateral primary motor cortex in movement control and recovery from brain damage. Experimental Neurology, 221(1), 13-17. doi: 10.1016/j.expneurol.2009.10.021 pmid: 19896482
[36]	Sun, Y. F., Yang, Y. H., Desroches, A. S., Liu, L., & Peng, D. L. (2011). The role of the ventral and dorsal pathways in reading Chinese characters and English words. Brain and Language, 119(2), 80-88. doi: 10.1016/j.bandl.2011.03.012 pmid: 21546073
[37]	Tan, L. H., Laird, A. R., Li, K., & Fox, P. T. (2005). Neuroanatomical correlates of phonological processing of Chinese characters and alphabetic words: A meta-analysis. Human Brain Mapping, 25(1), 83-91. pmid: 15846817
[38]	Tan, L. H., Liu, H. L., Perfetti, C. A., Spinks, J. A., Fox, P. T., & Gao, J. H. (2001). The neural system underlying Chinese logograph reading. Neuroimage, 13(5), 836-846. doi: 10.1006/nimg.2001.0749 pmid: 11304080
[39]	Tan, L. H., Spinks, J. A., Feng, C. M., Siok, W. T., Perfetti, C. A., Xiong, J. H., ... Gao, J. H. (2003). Neural systems of second language reading are shaped by native language. Human Brain Mapping, 18(3), 158-166. pmid: 12599273
[40]	Tan, L. H., Spinks, J. A., Gao, J. H., Liu, H. L., Perfetti, C. A., Xiong, J. H., ... Fox, P. T. (2000). Brain activation in the processing of Chinese characters and words: A functional MRI study. Human Brain Mapping, 10(1), 16-27. pmid: 10843515
[41]	Tian, F. H., Lin, Z.-J., & Liu, H. L. (2013). EasyTopo: A toolbox for rapid diffuse optical topography based on a standard template of brain atlas. Proceedings of the Society of Photo-Optical Instrumentation Engineers, 8578, 85782J.
[42]	Wang, H., & Legge, G. E. (2018). Comparing the minimum spatial-frequency content for recognizing Chinese and alphabet characters. Journal of Vision, 18(1), 1-13. doi: 10.1167/18.1.1 pmid: 29297056
[43]	Wang, X., Yang, J., Shu, H., & Zevin, J. D. (2011). Left fusiform BOLD responses are inversely related to word-likeness in a one-back task. Neuroimage, 55(3), 1346-1356. doi: 10.1016/j.neuroimage.2010.12.062 pmid: 21216293
[44]	Winsler, K., Holcomb, P. J., Midgley, K. J., & Grainger, J. (2017). Evidence for separate contributions of high and low spatial frequencies during visual word recognition. Frontiers in Human Neuroscience, 11, 324. doi: 10.3389/fnhum.2017.00324 pmid: 28690505
[45]	Woodhead, Z. V., Wise, R. J., Sereno, M., & Leech, R. (2011). Dissociation of sensitivity to spatial frequency in word and face preferential areas of the fusiform gyrus. Cerebral Cortex, 21(10), 2307-2312. doi: 10.1093/cercor/bhr008 URL
[46]	Wu, C.-Y., Ho, M.-H. R., & Chen, S.-H. A. (2012). A meta-analysis of fMRI studies on Chinese orthographic, phonological, and semantic processing. Neuroimage, 63(1), 381-391. doi: 10.1016/j.neuroimage.2012.06.047 URL
[47]	Yang, J. F., Wang, X. J., Shu, H., & Zevin, J. D. (2011). Brain networks associated with sublexical properties of Chinese characters. Brain and Language, 119(2), 68-79. doi: 10.1016/j.bandl.2011.03.004 pmid: 21600637
[48]	Ye, J. C., Tak, S., Jang, K. E., Jung, J., & Jang, J. (2009). NIRS-SPM: Statistical parametric mapping for near-infrared spectroscopy. Neuroimage, 44(2), 428-447. doi: 10.1016/j.neuroimage.2008.08.036 pmid: 18848897
[49]	Zhao, J., Bi, H. Y., & Qian, Y. (2013). The influence of visual magnocellular pathway on the recognition of Chinese character. Progress in Biochemistry and Biophysics, 40(2), 141-146.
[50]	Zhao, J., Qian, Y., Bi, H. Y., & Coltheart, M. (2014). The visual magnocellular-dorsal dysfunction in Chinese children with developmental dyslexia impedes Chinese character recognition. Scientific Reports, 4, 7068. doi: 10.1038/srep07068 pmid: 25412386
[51]	Zhao, R., Fan, R., Liu, M. X., Wang, X. J., & Yang, J. F. (2017). Rethinking the function of brain regions for reading Chinese characters in a meta-analysis of fMRI studies. Journal of Neurolinguistics, 44, 120-133. doi: 10.1016/j.jneuroling.2017.04.001 URL

Effect type	Accuracy			Response Time
Effect type	F	p	η2 p	F	p	η2 p
Character type	F (2, 54) = 12.88	0.001	0.323	F (2, 54) = 7.02	0.002	0.206
Spatial frequency	F (2, 54) = 0.04	0.964	0.001	F (2, 54) = 1.00	0.373	0.036
Interaction	F (4, 108) = 3.72	0.007	0.121	F (4, 108) = 0.98	0.419	0.035

Effect type	Accuracy			Response Time
Effect type	F	p	η2 p	F	p	η2 p
Character type	F (2, 54) = 12.88	0.001	0.323	F (2, 54) = 7.02	0.002	0.206
Spatial frequency	F (2, 54) = 0.04	0.964	0.001	F (2, 54) = 1.00	0.373	0.036
Interaction	F (4, 108) = 3.72	0.007	0.121	F (4, 108) = 0.98	0.419	0.035

Condition	Channel 10			Channel 13
Condition	t(27)	p	Cohen d	t(27)	p	Cohen d
FSF
Real-Pseudo	-2.23	0.034	0.42	-1.16	0.255	0.22
Real-Artificial	-0.37	0.712	0.07	1.12	0.275	0.21
Pseudo-Artificial	1.80	0.083	0.35	2.33	0.027	0.44
LSF
Real-Pseudo	-3.17	0.004	0.60	-2.30	0.030	0.44
Real-Artificial	-1.41	0.169	0.27	0.03	0.978	0.01
Pseudo-Artificial	2.46	0.020	0.47	3.70	0.001	0.70
HSF
Real-Pseudo	0.92	0.365	0.18	1.54	0.134	0.29
Real-Artificial	-0.79	0.436	0.15	0.07	0.942	0.01
Pseudo-Artificial	-1.13	0.268	0.21	-0.64	0.528	0.12

Condition	Channel 10			Channel 13
Condition	t(27)	p	Cohen d	t(27)	p	Cohen d
FSF
Real-Pseudo	-2.23	0.034	0.42	-1.16	0.255	0.22
Real-Artificial	-0.37	0.712	0.07	1.12	0.275	0.21
Pseudo-Artificial	1.80	0.083	0.35	2.33	0.027	0.44
LSF
Real-Pseudo	-3.17	0.004	0.60	-2.30	0.030	0.44
Real-Artificial	-1.41	0.169	0.27	0.03	0.978	0.01
Pseudo-Artificial	2.46	0.020	0.47	3.70	0.001	0.70
HSF
Real-Pseudo	0.92	0.365	0.18	1.54	0.134	0.29
Real-Artificial	-0.79	0.436	0.15	0.07	0.942	0.01
Pseudo-Artificial	-1.13	0.268	0.21	-0.64	0.528	0.12

Channel	Character type			Interaction
Channel	F(2,54)	p	η2 p	F(4,108)	p	η2 p
8(PreCG)	3.23	0.047	0.107	/	/	/
23(SFG)	4.15	0.021	0.133	/	/	/
18(PostCG)	4.09	0.022	0.131	/	/	/
41(MOG)	/	/	/	2.73	0.033	0.092