心理学报 ›› 2024, Vol. 56 ›› Issue (6): 689-700.doi: 10.3724/SP.J.1041.2024.00689 cstr: 32110.14.2024.00689
• 研究报告 • 下一篇
收稿日期:
2022-11-15
发布日期:
2024-04-08
出版日期:
2024-06-25
通讯作者:
张琪, E-mail: zq1892@mnnu.edu.cn作者简介:
第一联系人:张琪和王紫乐同为第一作者。
基金资助:
ZHANG Qi1,2,3(), WANG Zile4, WU Meijun1
Received:
2022-11-15
Online:
2024-04-08
Published:
2024-06-25
摘要:
非显著性刺激的知觉学习研究发现成人大脑具有可塑性, 但是知觉学习如何影响不同的视觉加工阶段仍不清楚。通过将眼动指标划分为3个视觉加工阶段来探究知觉学习的机制:搜索潜伏期(早期), 是指从搜索屏呈现到第一次眼跳离开初始注视点位置的时间, 代表了在搜索屏中选择第一个搜索位置的时间; 注视点个数和平均注视时间(中期), 代表搜索过程中注视加工的位置个数和平均加工时间; 确定时间(后期), 代表判断当前刺激是否为目标并做出反应的时间。结果发现对训练刺激的搜索正确率提高, 反应时变快, 同时搜索潜伏期显著增加, 注视点个数和平均注视时间减少, 且行为和眼动指标的变化都没有迁移至未训练刺激。说明知觉学习会影响早期和中期视觉加工阶段, 可能通过增长搜索潜伏期, 同时减少眼跳的次数和降低注视时间来提高搜索表现。
中图分类号:
张琪, 王紫乐, 吴美君. (2024). 知觉学习中非显著性刺激视觉加工的学习机制. 心理学报, 56(6), 689-700.
ZHANG Qi, WANG Zile, WU Meijun. (2024). The mechanism of visual processing for nonsalient stimuli in perceptual learning. Acta Psychologica Sinica, 56(6), 689-700.
[1] |
Ahissar, M., & Hochstein, S. (1996). Learning pop-out detection: Specificities to stimulus characteristics. Vision Research, 36(21), 3487-3500. https://doi.org/10.1016/0042-6989(96)00036-3
URL pmid: 8977015 |
[2] | Ahissar, M., & Hochstein, S. (1997). Task difficulty and the specificity of perceptual learning. Nature, 387(6631), 401-406. https://doi.org/10.1038/387401a0 |
[3] |
Bao, M., Yang, L., Rios, C., He, B., & Engel, S. A. (2010). Perceptual learning increases the strength of the earliest signals in visual cortex. Journal of Neuroscience, 30(45), 15080-15084. https://doi.org/10.1523/JNEUROSCI.5703-09.2010
doi: 10.1523/JNEUROSCI.5703-09.2010 URL pmid: 21068313 |
[4] |
Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433-436. https://doi.org/10.1163/156856897X00357
URL pmid: 9176952 |
[5] |
Campbell, J. I. D., & Thompson, V. A. (2012). MorePower 6.0 for ANOVA with relational confidence intervals and Bayesian analysis. Behavior Research Methods, 44(4), 1255-1265. https://doi.org/10.3758/s13428-012-0186-0
doi: 10.3758/s13428-012-0186-0 URL pmid: 22437511 |
[6] |
Casteau, S., & Smith, D. T. (2020). Covert attention beyond the range of eye-movements: Evidence for a dissociation between exogenous and endogenous orienting. Cortex, 122, 170-186. https://doi.org/10.1016/j.cortex.2018.11.007
doi: S0010-9452(18)30379-4 URL pmid: 30528427 |
[7] | Czerwinski, M., Lightfoot, N., & Shiffrin, R. M. (1992). Automatization and training in visual search. The American Journal of Psychology, 105(2), 271-315. https://doi.org/10.2307/1423030 |
[8] | Desimone, R., & Ungerleider, L. G. (1989). Neural mechanisms of visual processing in monkeys. Handbook of Neuropsychology, 2(1983), 267-299. |
[9] | Ding, Y., Li, T., & Qu, Z. (2023). Is a new feature learned behind a newly efficient color-orientation conjunction search? Psychonomic Bulletin and Review, 30(1), 250-260. https://doi.org/10.3758/s13423-022-02156-3 |
[10] |
Ding, Y., Song, Y., Fan, S., Qu, Z., & Chen, L. (2003). Specificity and generalization of visual perceptual learning in humans: An event-related potential study. NeuroReport, 14(4), 587-590. https://doi.org/10.1097/00001756-200303240-00012
URL pmid: 12657891 |
[11] |
Fahle, M. (2005). Perceptual learning: Specificity versus generalization. Current Opinion in Neurobiology, 15(2), 154-160. https://doi.org/10.1016/j.conb.2005.03.010
URL pmid: 15831396 |
[12] |
Fahle, M., & Edelman, S. (1993). Long-term learning in vernier acuity: Effects of stimulus orientation, range and of feedback. Vision Research, 33(3), 397-412. https://doi.org/10.1016/0042-6989(93)90094-D
URL pmid: 8447110 |
[13] | Fahle, M., Edelman, S., & Poggio, T. (1995). Fast perceptual learning in visual hyperacuity. Science, 35(21), 3003-3013. https://doi.org/10.1126/science.1589770 |
[14] |
Fang, F., Murray, S. O., Kersten, D., & He, S. (2005). Orientation-tuned fMRI adaptation in human visual cortex. Journal of Neurophysiology, 94(6), 4188-4195. https://doi.org/10.1152/jn.00378.2005
URL pmid: 16120668 |
[15] |
Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The neural basis of perceptual learning. Neuron, 31(5), 681-697. https://doi.org/10.1016/S0896-6273(01)00424-X
URL pmid: 11567610 |
[16] | Hu, L., Ding, Y., & Qu, Z. (2018). Perceptual learning induces active suppression of physically nonsalient shapes. Psychophysiology, 56(9), 1-17. https://doi.org/10.1111/psyp.13393 |
[17] |
Hubel, D. H., & Wiesel, T. N. (1965). Binocular interaction in striate cortex of kittens reared with artificial squint. Journal of Neurophysiology, 28(6), 1041-1059. https://doi.org/10.1152/jn.1965.28.6.1041
doi: 10.1152/jn.1965.28.6.1041 URL pmid: 5883731 |
[18] |
Kahnt, T., Grueschow, M., Speck, O., & Haynes, J. D. (2011). Perceptual learning and decision-making in human medial frontal cortex. Neuron, 70(3), 549-559. https://doi.org/10.1016/j.neuron.2011.02.054
doi: 10.1016/j.neuron.2011.02.054 URL pmid: 21555079 |
[19] |
Karni, A., & Sagi, D. (1991). Where practice makes perfect in texture discrimination: Evidence for primary visual cortex plasticity. Proceedings of the National Academy of Sciences of the United States of America, 88(11), 4966-4970. https://doi.org/10.1073/pnas.88.11.4966
doi: 10.1073/pnas.88.11.4966 URL pmid: 2052578 |
[20] | Karni, A., & Sagi, D. (1993). The time course of learning a visual skill. Nature, 365(6443), 250-252. https://doi.org/10.1038/365250a0 |
[21] |
Kowler, E., Anderson, E., Dosher, B., & Blaser, E. (1995). The role of attention in the programming of saccades. Vision Research, 35(13), 1897-1916. https://doi.org/10.1016/0042-6989(94)00279-u
doi: 10.1016/0042-6989(94)00279-u URL pmid: 7660596 |
[22] | Law, C. T., & Gold, J. I. (2008). Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area. Nature Neuroscience, 11(4), 505-513. https://doi.org/10.1038/nn2070 |
[23] | Law, C. T., & Gold, J. I. (2009). Reinforcement learning can account for associative and perceptual learning on a visual-decision task. Nature Neuroscience, 12(5), 655-663. https://doi.org/10.1038/nn.2304 |
[24] | Lin, Z., Ma, Q., & Zhang, Y. (2023). Psycalibrator: An open-source package for display gamma calibration and luminance and color measurement. Advances in Methods and Practices in Psychological Science, 6(2), 1-14. https://doi.org/10.1177/25152459221151151 |
[25] |
Liu, Z., & Weinshall, D. (2000). Mechanisms of generalization in perceptual learning. Vision Research, 40(1), 97-109. https://doi.org/10.1016/S0042-6989(99)00140-6
doi: 10.1016/s0042-6989(99)00140-6 URL pmid: 10768045 |
[26] | Ma, X. L., Yang, B., Zhong, X., & Song, Y. (2009). The neural mechanism of perceptual learning. Advances in Psychological Science, 17(4), 653-658. |
[马小丽, 杨彬, 钟翔, 宋艳. (2009). 知觉学习的神经机制. 心理科学进展, 17(4), 653-658.] | |
[27] |
Maertens, M., & Pollmann, S. (2005). fMRI reveals a common neural substrate of illusory and real contours in V1 after perceptual learning. Journal of Cognitive Neuroscience, 17(10), 1553-1564. https://doi.org/10.1162/089892905774597209
URL pmid: 16269096 |
[28] | Malcolm, G. L., & Henderson, J. M. (2009). The effects of target template specificity on visual search in real-world scenes: Evidence from eye movements. Journal of Vision, 9(11), 1-13. https://doi.org/10.1167/9.11.8 |
[29] | Malcolm, G. L., & Henderson, J. M. (2010). Combining top-down processes to guide eye movements during real-world scene search. Journal of Vision, 10(2), 1-11. https://doi.org/10.1167/10.2.4 |
[30] | Qu, Z., Hillyard, S. A., & Ding, Y. (2017). Perceptual learning induces persistent attentional capture by nonsalient shapes. Cerebral Cortex, 27(2), 1512-1523. https://doi.org/10.1093/cercor/bhv342 |
[31] |
Saffell, T., & Matthews, N. (2003). Task-specific perceptual learning on speed and direction discrimination. Vision Research, 43(12), 1365-1374. https://doi.org/10.1016/S0042-6989(03)00137-8
URL pmid: 12742106 |
[32] |
Sagi, D., & Tanne, D. (1994). Perceptual learning: Learning to see. Current Opinion in Neurobiology, 4(2), 195-199. https://doi.org/10.1016/0959-4388(94)90072-8
URL pmid: 8038576 |
[33] | Shibata, K., Sasaki, Y., Kawato, M., & Watanabe, T. (2016). Neuroimaging evidence for 2 types of plasticity in association with visual perceptual learning. Cerebral Cortex, 26(9), 3681-3689. https://doi.org/10.1093/cercor/bhw176 |
[34] |
Sigman, M., & Gilbert, C. D. (2000). Learning to find a shape. Nature Neuroscience, 3(3), 264-269. https://doi.org/10.1038/72979
URL pmid: 10700259 |
[35] |
Su, Y., Lai, Y., Huang, W., Tan, W., Qu, Z., & Ding, Y. (2014). Short-term perceptual learning in visual conjunction search. Journal of Experimental Psychology: Human Perception and Performance, 40(4), 1415-1424. https://doi.org/10.1037/a0036337
doi: 10.1037/a0036337 URL pmid: 24730740 |
[36] | Talcott, T. N., & Gaspelin, N. (2021). Eye movements are not mandatorily preceded by the N2pc component. Psychophysiology, 58(6), e13821. https://doi.org/10.1111/psyp.13821 |
[37] | Wagenmakers, E. J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J.,... Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin and Review, 25(1), 35-57. https://doi.org/10.3758/s13423-017-1343-3 |
[38] | Wasserstein, R. L., & Lazar, N. A. (2016). The ASA’s statement on p-values: Context, process, and purpose. American Statistician, 70(2), 129-133. https://doi.org/10.1080/00031305.2016.1154108 |
[39] |
Watanabe, T., & Sasaki, Y. (2015). Perceptual learning: Toward a comprehensive theory. Annual Review of Psychology, 66, 197-221. https://doi.org/10.1146/annurev-psych-010814-015214
doi: 10.1146/annurev-psych-010814-015214 URL pmid: 25251494 |
[40] | Xiao, L. Q., Zhang, J. Y., Wang, R., Klein, S. A., Levi, D. M., & Yu, C. (2008). Complete transfer of perceptual learning across retinal locations enabled by double training. Current Biology, 18(24), 1922-1926. https://doi.org/10.1016/j.cub.2008.10.030 |
[41] | Zhang, J. Y., Zhang, G. L., Xiao, L. Q., Klein, S. A., Levi, D. M., & Yu, C. (2010). Rule-based learning explains visual perceptual learning and its specificity and transfer. Journal of Neuroscience, 30(37), 12323-12328. https://doi.org/10.1523/JNEUROSCI.0704-10.2010 |
[42] | Zhang, Q., Huang, Z., Li, L., & Li, S. (2022). Visual search training benefits from the integrative effect of enhanced covert attention and optimized overt eye movements. Journal of Vision, 22(8), 1-52. https://doi.org/10.1167/jov.22.8.7 |
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