心理学报 ›› 2020, Vol. 52 ›› Issue (8): 958-970.doi: 10.3724/SP.J.1041.2020.00958
刘洁1,2,3, 李瑾琪1,2, 申超然4, 胡小惠1,2, 赵庭浩5, 关青1,2, 罗跃嘉1,2,3()
收稿日期:
2019-09-12
发布日期:
2020-06-28
出版日期:
2020-08-25
通讯作者:
罗跃嘉
E-mail:luoyj@szu.edu.cn
基金资助:
LIU Jie1,2,3, LI Jinqi1,2, SHEN Chaoran4, HU Xiaohui1,2, ZHAO Tinghao5, GUAN Qing1,2, LUO Yuejia1,2,3()
Received:
2019-09-12
Online:
2020-06-28
Published:
2020-08-25
Contact:
LUO Yuejia
E-mail:luoyj@szu.edu.cn
摘要:
近似数量加工是对大数目物体数量在不依赖逐个数数前提下的估计。行为学研究提示高数学焦虑人群近似数量加工能力下降, 但神经机制未明。本研究探讨高数学焦虑个体近似数量加工的神经机制, 比较高低数学焦虑脑电活动的差异:(1)行为上无显著组间差异; (2)高数学焦虑组的P2p成分波幅增加; (3) δ频段ERS及β频段ERD无显著数量比例效应, 而低数学焦虑组在上述指标的数量比例效应显著。本研究为高数学焦虑人群近似数量加工能力下降提供了电生理学的证据。
中图分类号:
刘洁, 李瑾琪, 申超然, 胡小惠, 赵庭浩, 关青, 罗跃嘉. (2020). 数学焦虑个体近似数量加工的神经机制:一项EEG研究. 心理学报, 52(8), 958-970.
LIU Jie, LI Jinqi, SHEN Chaoran, HU Xiaohui, ZHAO Tinghao, GUAN Qing, LUO Yuejia. (2020). The neural mechanism of approximate number processing for mathematical anxious individuals: An EEG study. Acta Psychologica Sinica, 52(8), 958-970.
组别 | 年龄(岁) | 性别(男/女) | 数学焦虑 | 一般焦虑 | 视觉加工速度 | 视觉注意广度 | 智力 |
---|---|---|---|---|---|---|---|
高数学焦虑 (High math anxious, HMA) | 20.68 (1.62) | 15/16 | 94.35 (7.37) | 44.70 (5.35) | 74.06 (17.24) | 58.71 (18.78) | 5.03 (1.38) |
低数学焦虑 (Low math anxious, LMA) | 20.69 (1.85) | 17/12 | 41.86 (6.56) | 44.45 (4.84) | 75.86 (16.19) | 63.96 (18.91) | 5.14 (0.88) |
t | -- | -- | 29.07 | 0.2 | -0.42 | -1.08 | -0.35 |
p | -- | -- | <.001 | 0.84 | 0.68 | 0.28 | 0.72 |
表1 高低数学焦虑组的年龄、性别、数学焦虑、一般焦虑、视觉加工速度、视觉注意广度及的平均得分及标准差
组别 | 年龄(岁) | 性别(男/女) | 数学焦虑 | 一般焦虑 | 视觉加工速度 | 视觉注意广度 | 智力 |
---|---|---|---|---|---|---|---|
高数学焦虑 (High math anxious, HMA) | 20.68 (1.62) | 15/16 | 94.35 (7.37) | 44.70 (5.35) | 74.06 (17.24) | 58.71 (18.78) | 5.03 (1.38) |
低数学焦虑 (Low math anxious, LMA) | 20.69 (1.85) | 17/12 | 41.86 (6.56) | 44.45 (4.84) | 75.86 (16.19) | 63.96 (18.91) | 5.14 (0.88) |
t | -- | -- | 29.07 | 0.2 | -0.42 | -1.08 | -0.35 |
p | -- | -- | <.001 | 0.84 | 0.68 | 0.28 | 0.72 |
指标 | 组别 | 主动-大比例 | 主动小比例 | 被动-大比例 | 被动-小比例 |
---|---|---|---|---|---|
ACC | HMA | 0.91 (0.04) | 0.75 (0.05) | 0.80 (0.07) | 0.78 (0.07) |
LMA | 0.92 (0.05) | 0.76 (0.06) | 0.78 (0.07) | 0.74 (0.07) | |
RT | HMA | 620 (112) | 736 (132) | 619 (116) | 648 (110) |
LMA | 622 (120) | 752 (133) | 642 (103) | 662 (101) |
表2 各条件下不同组别的平均准确率和反应时
指标 | 组别 | 主动-大比例 | 主动小比例 | 被动-大比例 | 被动-小比例 |
---|---|---|---|---|---|
ACC | HMA | 0.91 (0.04) | 0.75 (0.05) | 0.80 (0.07) | 0.78 (0.07) |
LMA | 0.92 (0.05) | 0.76 (0.06) | 0.78 (0.07) | 0.74 (0.07) | |
RT | HMA | 620 (112) | 736 (132) | 619 (116) | 648 (110) |
LMA | 622 (120) | 752 (133) | 642 (103) | 662 (101) |
[1] | Alexander, L., & Martray, C. (1989). The development of an abbreviated version of the Mathematics Anxiety Rating Scale. Measurement and Evaluation in Counseling and Development, 22(3), 143-150. |
[2] | Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions in Psychological Science, 11 (5), 181-185. |
[3] | Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety, and performance. Journal of Experimental Psychology: General, 130(2), 224-237. |
[4] |
Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14(2), 243-248.
doi: 10.3758/bf03194059 URL pmid: 17694908 |
[5] |
Bates, M. E., & Lemay, E. P. (2004). The d2 test of attention: construct validity and extensions in scoring techniques. Journal of the International Neuropsychological Society, 10(3), 392-400.
URL pmid: 15147597 |
[6] |
Brannon, E. M. (2006). The representation of numerical magnitude. Current Opinion in Neurobiology, 16(2), 222-229.
doi: 10.1016/j.conb.2006.03.002 URL pmid: 16546373 |
[7] | Brannon, E. M., Jordan, K. E., & Jones, S. M., (2010). Behavioral signatures of numerical cognition. In M. L. Platt, A. A. Ghazanfa (Eds.).Primate neuroethology (pp.144-159), Oxford University Press. |
[8] |
Carey, E., Hill, F., Devine, A., & Szücs, D. (2016). The chicken or the egg? The direction of the relationship between mathematics anxiety and mathematics performance. Frontiers in Psychology, 6, 1987.
doi: 10.3389/fpsyg.2015.01987 URL pmid: 26779093 |
[9] | Cohen, M. X. (2014). Analyzing neural time series data: Theory and practice. Cambrige, Massachusetts, the MIT press. |
[10] | Colomé, À. (2019). Representation of numerical magnitude in math-anxious individuals. Quarterly Journal of Experimental Psychology, 72(3), 424-435. |
[11] |
Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21.
doi: 10.1016/j.jneumeth.2003.10.009 URL pmid: 15102499 |
[12] |
Dietrich, J. F., Huber, S., Moeller, K., & Klein, E. (2015). The influence of math anxiety on symbolic and non-symbolic magnitude processing. Frontiers in Psychology, 6, 1621.
doi: 10.3389/fpsyg.2015.01621 URL pmid: 26579012 |
[13] |
Di Russo, F., Martínez, A., Sereno, M. I., Pitzalis, S., & Hillyard, S. A. (2002). Cortical sources of the early components of the visual evoked potential. Human Brain Mapping, 15 (2), 95-111.
doi: 10.1002/hbm.10010 URL pmid: 11835601 |
[14] | Ekstrom, R. B., Dermen, D., & Harman, H. H. (1976). Manual for kit of factor-referenced cognitive tests (Vol. 102). Princeton, NJ: Educational Testing Service. |
[15] |
Engel, A. K., Fries, P., & Singer, W. (2001). Dynamic predictions: Oscillations and synchrony in top-down processing. Nature Reviews Neuroscience, 2 (10), 704-716.
doi: 10.1038/35094565 URL pmid: 11584308 |
[16] |
Engel, A. K., & Fries, P. (2010). Beta-band oscillations-signalling the status quo? Current Opinion in Neurobiology, 20(2), 156-165.
doi: 10.1016/j.conb.2010.02.015 URL pmid: 20359884 |
[17] |
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191.
doi: 10.3758/BF03193146 URL |
[18] |
Fornaciai, M., Brannon, E. M., Woldorff, M. G., & Park, J. (2017). Numerosity processing in early visual cortex. NeuroImage, 157, 429-438.
doi: 10.1016/j.neuroimage.2017.05.069 URL pmid: 28583882 |
[19] |
Halberda, J., Mazzocco, M. M., & Feigenson, L. (2008). Individual differences in non-verbal number acuity correlate with maths achievement. Nature, 455(7213), 665-668.
doi: 10.1038/nature07246 URL pmid: 18776888 |
[20] | Hauser, M. D., Tsao, F., Garcia, P., & Spelke, E. S. (2003). Evolutionary foundations of number: spontaneous representation of numerical magnitudes by cotton-top tamarins. Proceedings of the Royal Society of London B: Biological Sciences, 270(1523), 1441-1446. |
[21] |
Hyde, D. C., & Spelke, E. S. (2009). All numbers are not equal: an electrophysiological investigation of small and large number representations. Journal of Cognitive Neuroscience, 21(6), 1039-1053.
doi: 10.1162/jocn.2009.21090 URL pmid: 18752403 |
[22] |
Hyde, D. C., & Spelke, E. S. (2012). Spatiotemporal dynamics of processing nonsymbolic number: An event‐related potential source localization study. Human Brain Mapping, 33(9), 2189-2203.
doi: 10.1002/hbm.21352 URL |
[23] |
Hyde, D. C., & Wood, J. N. (2011). Spatial attention determines the nature of nonverbal number representation. Journal of Cognitive Neuroscience, 23 (9), 2336-2351.
doi: 10.1162/jocn.2010.21581 URL pmid: 20961170 |
[24] | Izard, V., Sann, C., Spelke, E. S., & Streri, A. (2009). Newborn infants perceive abstract numbers. Proceedings of the National Academy of Sciences, 106(25), 10382-10385. |
[25] |
Libertus, M. E., & Brannon, E. M. (2009). Behavioral and neural basis of number sense in infancy. Current Directions in Psychological Science, 18(6), 346-351.
doi: 10.1111/j.1467-8721.2009.01665.x URL pmid: 20419075 |
[26] | Libertus, M. E., Woldorff, M. G., & Brannon, E. M. (2007). Electrophysiological evidence for notation independence in numerical processing. Behavioral and Brain Functions, 3(1), 1. |
[27] |
Lindskog, M., Winman, A., & Poom, L. (2017). Individual differences in nonverbal number skills predict math anxiety. Cognition, 159, 156-162.
URL pmid: 27960118 |
[28] |
Liu, J., Li, J., Peng, W., Feng, M., & Luo, Y. (2019). EEG correlates of math anxiety during arithmetic problem solving: Implication for attention deficits. Neuroscience Letters, 703, 191-197.
doi: 10.1016/j.neulet.2019.03.047 URL pmid: 30928479 |
[29] |
Lyons, I. M., & Beilock, S. L. (2011). Mathematics anxiety: separating the math from the anxiety. Cerebral Cortex, 22 (9), 2102-2110.
doi: 10.1093/cercor/bhr289 URL pmid: 22016480 |
[30] | Maloney, E. A., Ansari, D., & Fugelsang, J. A. (2011). Rapid communication: the effect of mathematics anxiety on the processing of numerical magnitude. Quarterly Journal of Experimental Psychology, 64(1), 10-16. |
[31] |
Maloney, E. A., Risko, E. F., Ansari, D., & Fugelsang, J. (2010). Mathematics anxiety affects counting but not subitizing during visual enumeration. Cognition, 114 (2), 293-297.
doi: 10.1016/j.cognition.2009.09.013 URL pmid: 19896124 |
[32] |
Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG and MEG data. Journal of Neuroscience Methods, 164 (1), 177-190.
doi: 10.1016/j.jneumeth.2007.03.024 URL pmid: 17517438 |
[33] | Núñez-Peña, M. I., & Suárez-Pellicioni, M. (2014). Less precise representation of numerical magnitude in high math-anxious individuals: An ERP study of the size and distance effects. Biological Psychology, 103, 1767-183. |
[34] |
Núñez-Peña, M. I., & Suárez-Pellicioni, M. (2015). Processing of multi-digit additions in high math-anxious individuals: psychophysiological evidence. Frontiers in Psychology, 6, 1268.
doi: 10.3389/fpsyg.2015.01268 URL pmid: 26347705 |
[35] | OECD, . (2013). PISA 2012 Results: Ready to learn: Students' engagement drive and self-beliefs (Volume III). PISA, OECD Publishing. |
[36] |
Park, J. (2018). A neural basis for the visual sense of number and its development: A steady-state visual evoked potential study in children and adults. Developmental Cognitive Neuroscience, 30, 333-343.
doi: 10.1016/j.dcn.2017.02.011 URL pmid: 28342780 |
[37] |
Park, J., DeWind, N. K., Woldorff, M. G., & Brannon, E. M. (2015). Rapid and direct encoding of numerosity in the visual stream. Cerebral Cortex, 26(2), 748-763.
doi: 10.1093/cercor/bhv017 URL pmid: 25715283 |
[38] | Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Raven's Progressive Matrices and Vocabulary Scales. Section 3, The Standard Progressive Matrices. Oxford, England: Oxford Psychologists Press/San Antonio, TX: The Psychological Corporation. |
[39] | Sorvo, R., Koponen, T., Viholainen, H., Aro, T., Räikkönen, E., Peura, P., … Aro, M. (2019). Development of math anxiety and its longitudinal relationships with arithmetic achievement among primary school children. Learning and Individual Differences, 69, 173-181. |
[40] | Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983) Manual for the state-trait anxiety scale. CA: Consulting Psychologists Press. |
[41] | Sullivan, J., Frank, M. C., & Barner, D. (2016). Intensive math training does not affect approximate number acuity: Evidence from a three-year longitudinal curriculum intervention. Journal of Numerical Cognition, 2 (2), 57-76. |
[42] |
Wang, Z., Hart, S. A., Kovas, Y., Lukowski, S., Soden, B., Thompson, L. A., … Petrill, S. A. (2014). Who is afraid of math? Two sources of genetic variance for mathematical anxiety. Journal of Child Psychology and Psychiatry, 55 (9), 1056-1064.
doi: 10.1111/jcpp.12224 URL pmid: 24611799 |
[43] |
Xu, F., Spelke, E. S., & Goddard, S. (2005). Number sense in human infants. Developmental Science, 8(1), 88-101.
doi: 10.1111/j.1467-7687.2005.00395.x URL pmid: 15647069 |
[44] |
Young, C. B., Wu, S. S., & Menon, V. (2012). The neurodevelopmental basis of math anxiety. Psychological Science, 23(5), 492-501.
doi: 10.1177/0956797611429134 URL pmid: 22434239 |
[45] |
Zhang, Z. G., Hu, L., Hung, Y. S., Mouraux, A., & Iannetti, G. D. (2012). Gamma-band oscillations in the primary somatosensory cortex—a direct and obligatory correlate of subjective pain intensity. Journal of Neuroscience, 32 (22), 7429-7438.
doi: 10.1523/JNEUROSCI.5877-11.2012 URL pmid: 22649223 |
[46] |
Zhou, X., Wei, W., Zhang, Y., Cui, J., & Chen, C. (2015). Visual perception can account for the close relation between numerosity processing and computational fluency. Frontiers in Psychology, 6, 1364.
doi: 10.3389/fpsyg.2015.01364 URL pmid: 26441740 |
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