基于速度–准确性权衡的知觉学习研究综述
A Review of Perceptual Learning Based on Speed-Accuracy Tradeoff
DOI: 10.12677/AP.2021.116171, PDF,    科研立项经费支持
作者: 汪文怡：苏州大学教育学院，江苏 苏州
关键词: 知觉学习；知觉决策；速度准确性权衡；反应时；Perceptual Learning； Perceptual Decision； Speed-Accuracy Tradeoff； Response Time
摘要: 知觉任务的表现随着练习而提高。这种知觉学习发生在所有的感觉形式中，并且具有很大的理论意义和实际意义。在知觉学习研究中，研究人员通常把焦点放在正确率上，比如d’，忽略了反应时的作用。而知觉决策是将感觉信息转化为行为的过程，有大量的研究都表明了知觉学习中除感觉加工外的高级机制的重要性。要想充分地理解知觉学习必然要考虑到训练对决策过程的影响。因此，考虑到速度–准确性权衡(SAT)现象：在给定的可辨别性水平下，更快的反应往往会产生更多的错误，正确率和反应时对于知觉学习研究来说都很重要。本文对基于速度–准确性权衡的知觉学习研究现状进行了总结，结合知觉决策论述了知觉学习背后的发生机制。
Abstract: Performances on perceptual tasks improved with practice. This perceptual learning occurs in all sensory modalities and has great theoretical and practical significance. In the perceptual learning studies, researchers usually focus on accuracy, such as d’, and ignore the role of response time. Perceptual decision is the process that transfers sensory information into behavioral actions. A large number of studies have shown the importance of advanced mechanisms other than sensory processing in perceptual learning. To fully understand perceptual learning, it is necessary to consider the influence of training on decision process. Therefore, considering the speed-accuracy tradeoff (SAT) phenomenon: for a given level of discriminability, faster responses tend to produce more errors, accuracy and response time are both important for perceptual learning studies. This paper summarizes the research status of perceptual learning based on speed accuracy tradeoff, and discusses the mechanism behind perceptual learning with perceptual decision.
文章引用：汪文怡 (2021). 基于速度–准确性权衡的知觉学习研究综述. 心理学进展, 11(6), 1530-1538. https://doi.org/10.12677/AP.2021.116171

参考文献

[1] Aberg, K. C., Tartaglia, E. M., & Herzog, M. H. (2009). Perceptual Learning with Chevrons Requires a Minimal Number of Trials, Transfers to Untrained Directions, But Does Not Require Sleep. Vision Research, 49, 2087-2094.[CrossRef] [PubMed]
[2] Adini, Y., Sagi, D., & Tsodyks, M. (2002). Context-Enabled Learning in the Human Visual System. Nature, 415, 790-793.[CrossRef] [PubMed]
[3] Ahissar, M., & Hochstein, S. (1997). Task Difficulty and the Specificity of Perceptual Learning. Nature, 387, 401-406.[CrossRef] [PubMed]
[4] Ahissar, M., & Hochstein, S. (2004). The Reverse Hierarchy Theory of Visual Perceptual Learning. Trends in Cognitive Sciences, 8, 457-464.[CrossRef] [PubMed]
[5] Ball, K., & Sekuler, R. (1982). A Specific and Enduring Improvement in Visual Motion Discrimination. Science, 218, 697-698.[CrossRef] [PubMed]
[6] Ball, K., & Sekuler, R. (1987). Direction-Specific Improvement in Motion Discrimination. Vision Research, 27, 953-965.[CrossRef] [PubMed]
[7] Chen, N., Bi, T., Zhou, T., Li, S., Liu, Z., & Fang, F. (2015). Sharpened Cortical Tuning and Enhanced Cortico-Cortical Communication Contribute to the Long-Term Neural Mechanisms of Visual Motion Perceptual Learning. Neuroimage, 115, 17-29.[CrossRef] [PubMed]
[8] Crist, R., Li, W., & Gilbert, C. (2001). Learning to See: Experience and Attention in Primary Visual Cortex. Nature Neuroscience, 4, 519-525.[CrossRef] [PubMed]
[9] Ding, Y., Song, Y., Fan, S. L., Qu, Z., & Chen, L. (2003). Specificity and Generalization of Visual Perceptual Learning in Humans: An Event-Related Potential Study. Neuroreport, 14, 587-590.[CrossRef] [PubMed]
[10] Donovan, L., Szpiro, S., & Carrasco, M. (2015). Exogenous Attention Facilitates Location Transfer of Perceptual Learning. Journal of Vision, 15, 11.[CrossRef] [PubMed]
[11] Dosher, B. A., & Lu, Z. L. (2009). Hebbian Reweighting on Stable Representations in Perceptual Learning. Learning & Perception, 1, 37-58.[CrossRef] 
[12] Dosher, B. A., & Lu, Z.-L. (1998). Perceptual Learning Reflects External Noise Filtering and Internal Noise Reduction through Channel Reweighting. Proceedings of the National Academy of Sciences of the United States of America, 95, 13988-13993.[CrossRef] [PubMed]
[13] Dosher, B. A., & Lu, Z.-L. (1999). Mechanisms of Perceptual Learning. Vision Research, 39, 3197-3221.[CrossRef] 
[14] Dosher, B. A., Jeter, P., Liu, J. J., & Lu, Z. L. (2013). An Integrated Reweighting Theory of Perceptual Learning. Proceedings of the National Academy of Sciences, 110, 13678-13683.[CrossRef] [PubMed]
[15] Dutilh, G., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E. J. (2009). A Diffusion Model Decomposition of the Practice Effect. Psychonomic Bulletin & Review, 16, 1026-1036.[CrossRef] [PubMed]
[16] Fiorentini, A., & Berardi, N. (1980). Perceptual Learning Specific for Orientation and Spatial Frequency. Nature, 287, 43-44.[CrossRef] [PubMed]
[17] Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The Neural Basis of Perceptual Learning. Neuron, 31, 681-697.[CrossRef] 
[18] Green, C. S., Pouget, A., & Bavelier, D. (2010). Improved Probabilistic Inference as a General Learning Mechanism with Action Video Games. Current Biology, 20, 1573-1579.[CrossRef] [PubMed]
[19] Harris, H., Gliksberg, M., & Sagi, D. (2012). Generalized Perceptual Learning in the Absence of Sensory Adaptation. Current Biology, 22, 1813-1817.[CrossRef] [PubMed]
[20] Heekeren, H. R., Marrett, S., Bandettini, P. A., & Ungerleider, L. G. (2004). A General Mechanism for Perceptual Decision-Making in the Human Brain. Nature, 431, 859-862.[CrossRef] [PubMed]
[21] Herzog, M. H., & Fahle, M. (1997). The Role of Feedback in Learning a Vernier Discrimination Task. Vision Research, 37, 2133-2141.[CrossRef] 
[22] Hua, T. M., Bao, P. L., Huang, C. B., Wang, Z. H., Xu, J. W., Zhou, Y. F., & Lu, Z. L. (2010). Perceptual Learning Improves Contrast Sensitivity of V1 Neurons in Cats. Current Biology, 20, 887-894.[CrossRef] [PubMed]
[23] Jehee, J. F. M., Ling, S., Swisher, J. D., Bergen, R. S. V., & Tong, F. (2012). Perceptual Learning Selectively Refines Orientation Representations in Early Visual Cortex. The Journal of Neuroscience, 32, 16747-16753.[CrossRef] 
[24] Jeter, P. E., Dosher, B. A., Liu, S. H., & Lu, Z. L. (2010). Specificity of Perceptual Learning Increases with Increased Training. Vision Research, 50, 1928-1940.[CrossRef] [PubMed]
[25] Jeter, P. E., Dosher, B. A., Petrov, A., & Lu, Z. L. (2009). Task Precision at Transfer Determines Specificity of Perceptual Learning. Journal of Vision, 9, 11-13.[CrossRef] [PubMed]
[26] Jia, K., Xue, X., Lee, J. H., Fang, F., Zhang, J. X., & Li, S. (2018). Visual Perceptual Learning Modulates Decision Network in the Human Brain: The Evidence from Psychophysics, Modeling, and Functional Magnetic Resonance Imaging. Journal of Vision, 18, 9.[CrossRef] [PubMed]
[27] 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, 4966-4970.[CrossRef] [PubMed]
[28] Kayser, A. S., Buchsbaum, B. R., Erickson, D. T., & Esposito, M. D. (2010). The Functional Anatomy of a Perceptual Decision in the Human Brain. Journal of Neurophysiology, 103, 1179-1194.[CrossRef] [PubMed]
[29] Kim, J. N., & Shadlen, M. N. (1999). Neural Correlates of a Decision in the Dorsolateral Prefrontal Cortex of the Macaque. Nature Neuroscience, 2, 176-185.[CrossRef] [PubMed]
[30] 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, 505-513.[CrossRef] [PubMed]
[31] Liu, C. C., & Watanabe, T. (2012). Accounting for Speed-Accuracy Tradeoff in Perceptual Learning. Vision Research, 61, 107-114.[CrossRef] [PubMed]
[32] Liu, T., & Pleskac, T. J. (2011). Neural Correlates of Evidence Accumulation in a Perceptual Decision Task. Journal of Neurophysiology, 106, 2383-2398.[CrossRef] [PubMed]
[33] Liu, Z. (1999). Perceptual Learning in Motion Discrimination That Generalizes across Motion Directions. Proceedings of the National Academy of Sciences of the United States of America, 96, 14085-14087.[CrossRef] [PubMed]
[34] Liu, Z., & Weinshall, D. (2000). Mechanisms of Generalization in Perceptual Learning. Vision Research, 40, 97-109.[CrossRef] 
[35] Maniglia, M., & Seitz, A. R. (2018). Towards a Whole Brain Model of Perceptual Learning. Current Opinion in Behavioral Sciences, 20, 47-55.[CrossRef] [PubMed]
[36] Pachella, R. (1973). The Interpretation of Reaction Time in Information Processing Research. In B. H. Kantowitz (Ed.), Human Information Processing: Tutorials in Performance and Cognition (pp. 41-82). Hillsdale, NJ: Erlbaum.
[37] Petrov, A. A., Dosher, B. A., & Lu, Z. L. (2005). The Dynamics of Perceptual Learning: An Incremental Reweighting Model. Psychological Review, 112, 715-743.[CrossRef] 
[38] Petrov, A. A., Van Horn, N. M., & Ratcliff, R. (2011). Dissociable Perceptual-Learning Mechanisms Revealed by Diffusion-Model Analysis. Psychonomic Bulletin & Review, 18, 490-497.[CrossRef] [PubMed]
[39] Poggio, T., Fahle, M., & Edelman, S. (1992). Fast Perceptual Learning in Visual Hyperacuity. Science, 256, 1018-1021.[CrossRef] [PubMed]
[40] Ratcliff, R. (1978). A Theory of Memory Retrieval. Psychological Review, 85, 59-108.[CrossRef] 
[41] Ratcliff, R., & McKoon, G. (2008). The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks. Neural Computation, 20, 873-922.[CrossRef] [PubMed]
[42] Ratcliff, R., Gomez, P., & McKoon, G. (2004). A Diffusion Model Account of the Lexical Decision Task. Psychological Review, 111, 159-182.[CrossRef] 
[43] Ratcliff, R., Thapar, A., & McKoon, G. (2006). Aging, Practice, and Perceptual Tasks: A Diffusion Model Analysis. Psychology and Aging, 21, 353-371.[CrossRef] [PubMed]
[44] Romo, R., Hernández, A., & Zainos, A. (2004). Neuronal Correlates of a Perceptual Decision in Ventral Premotor Cortex. Neuron, 41, 165-173.[CrossRef] 
[45] Sagi, D. (2011). Perceptual Learning in Vision Research. Vision Research, 51, 1552-1566.[CrossRef] [PubMed]
[46] Schoups, A. A., Vogels, R., & Orban, G. A. (1995). Human Perceptual Learning in Identifying the Oblique Orientation: Retinotopy, Orientation Specificity and Monocularity. The Journal of Physiology, 483, 797-810.[CrossRef] [PubMed]
[47] Seitz, A. R., Nanez, J. E., Holloway, S., Tsushima, Y., & Watanabe, T. (2006). Two Cases Requiring External Reinforcement in Perceptual Learning. Journal of Vision, 6, 966-973.[CrossRef] [PubMed]
[48] Shibata, K., Sagi, D., & Watanabe, T. (2014). Two-Stage Model in Perceptual Learning: Toward a Unified Theory. Annals of the New York Academy of Sciences, 1316, 18-28.[CrossRef] [PubMed]
[49] Shibata, K., Watanabe, T., Sasaki, Y., & Kawato, M. (2011). Perceptual Learning Incepted by Decoded fMRI Neurofeedback without Stimulus Presentation. Science, 334, 1413-1415.[CrossRef] [PubMed]
[50] Smith, P. L. (1995). Psychophysically Principled Models of Visual Simple Reaction Time. Psychological Review, 102, 567-593.[CrossRef] 
[51] Szpiro, S. F., & Carrasco, M. (2015). Exogenous Attention Enables Perceptual Learning. Psychological Science, 26, 1854-1862.[CrossRef] [PubMed]
[52] Wang, R., Zhang, J. Y., Klein, S. A., Levi, D. M., & Yu, C. (2012). Task Relevancy and Demand Modulate Double-Training Enabled Transfer of Perceptual Learning. Vision Research, 61, 33-38.[CrossRef] [PubMed]
[53] Wang, R., Zhang, J. Y., Klein, S. A., Levi, D. M., & Yu, C. (2014). Vernier Perceptual Learning Transfers to Completely Untrained Retinal Locations after Double Training: A “Piggybacking” Effect. Journal of Vision, 14, 12.[CrossRef] [PubMed]
[54] Watanabe, T., & Sasaki, Y. (2015). Perceptual Learning: Toward a Comprehensive Theory. Annual Review of Psychology, 66, 197-221.[CrossRef] [PubMed]
[55] Watanabe, T., Náñez, J. E., & Sasaki, Y. (2001). Perceptual Learning without Perception. Nature, 413, 844-848.[CrossRef] [PubMed]
[56] Westheimer, G., Crist, R. E., Gorski, L., & Gilbert, C. D. (2001). Configuration Specificity in Bisection Acuity. Vision Research, 41, 1133-1138.[CrossRef] 
[57] 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, 1922-1926.[CrossRef] [PubMed]
[58] Xiong, Y. Z., Zhang, J. Y., & Yu, C. (2016). Bottom-Up and Top-Down Influences at Untrained Conditions Determine Perceptual Learning Specificity and Transfer. Elife, 5, e14614.[CrossRef] 
[59] Yashar, A., Chen, J. G., & Carrasco, M. (2015). Rapid and Long-Lasting Reduction of Crowding through Training. Journal of Vision, 15, 15.[CrossRef] [PubMed]
[60] Yotsumoto, Y., Chang, L. H., Ni, R., Pierce, R., Andersen, G. J., Watanabe, T., & Sasaki, Y. (2014). White Matter in the Older Brain Is More Plastic than in the Younger Brain. Nature Communications, 5, 5504.[CrossRef] [PubMed]
[61] Yu, C., Klein, S. A., & Levi, D. M. (2004). Perceptual Learning in Contrast Discrimination and the (Minimal) Role of Context. Journal of Vision, 4, 4.[CrossRef] [PubMed]
[62] 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, 12323-12328.[CrossRef] 
[63] Zhang, J., & Rowe, J. B. (2014). Dissociable Mechanisms of Speed-Accuracy Tradeoff during Visual Perceptual Learning Are Revealed by a Hierarchical Drift-Diffusion Model. Frontiers in Neuroscience, 8, 69.[CrossRef] [PubMed]