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[13] Cowan, J. (1967), Nature 213: 237.
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[14] Minsky, M. and Papert, S. (1969), Perceptrons: An Introduction to Computational Geometry (Cambridge, MA: MIT Press); Boden (2006), vol. 2, p. 915.
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[15] Olazaran, M. (1996), Social Studies of Science 26: 611–59认为，明斯基和佩珀特的评论的影响力被夸大了。
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[16] Marr (1982), pp. 13–14.
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[17] Ibid., p. xvii.
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[18] Glennerster, A. (2007), Current Biology 17: R397–R399; Frisby, J. and Stone, J. (2012), Perception 41: 1040–52; Stevens, K. (2012), Perception 41: 1061–72.
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[19] Marr (1982), p. 361.
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[20] Frisby, J. and Stone, J. (2010)，见：The Computational Approach to Biological Vision (Cambridge, MA: MIT Press), p. 548。当我还在谢菲尔德大学心理学专业读书时，约翰·弗里斯比曾试图向我讲解马尔的想法，但没有成功，问题在我。
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[21] 马尔关于鸟的翅膀的这段表述在神经科学家中很有名，这实际上是马尔在借机抨击巴洛所持的观点。巴洛更支持功能的神经元中心论，他在1961年指出，如果不全面了解鸟类的肌肉组织、羽毛的强度和轻盈程度，那么就不可能理解鸟类为什么会飞。见：Barlow, H. (1961), in W. Rosenblith (ed.), Sensory Communication (Cambridge, MA: MIT Press), pp. 217–34。
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[22] Marr (1982), p. 27.
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[23] Marr, D. (1976), Cold Spring Harbor Symposia on Quantitative Biology 40: 647–62, p. 653; Marr, D. and Hildreth, E. (1980), Proceedings of the Royal Society: Biological Sciences 207: 187–217; Martinez-Conde, S., et al. (2018), Trends in Neurosciences 41: 163–5.
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[24] Greene, M. and Hansen, B. (2018), PLoS Computational Biology 14: e1006327.
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[25] Stevens (2012), p. 1071.
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[26] Chang, L. and Tsao, D. (2017), Cell 169: 1013–28.
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[27] Landi, S. and Freiwald, W. (2017), Science 357: 591–5.
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[28] Abbott, A. (2018), Nature 564: 176–9, p. 179.
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[30] Ponce, C., et al. (2019), Cell 177: 999–1009.
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[31] Bashivan, P., et al. (2019), Science 364: eaav9436.
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[32] Carrillo-Reid, L., et al. (2019), Cell 178: 447–57; Marshel, J., et al. (2019), Science 365: eaaw5202.
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[33] Rumelhart, D., et al. (eds.) (1986), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1: Foundations; vol. 2: Psychological and Biological Models (Cambridge, MA: MIT Press); Anderson, J. and Rosenfeld, E. (eds.) (1998), Talking Nets: An Oral History of Neural Networks (Cambridge, MA
:MIT Press).
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[34] Sejnowski, T. (2018), The Deep Learning Revolution (London: MIT Press), p. 118.
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[35] 杰弗里·辛顿，加拿大计算机科学家，对人工智能的深度学习领域有重要贡献，与加拿大计算机科学家约书亚·本吉奥和法国计算机科学家杨立昆并称“人工智能教父”“深度学习教父”，三人也因为在这些领域的贡献于2018年获计算机科学界的最高奖“图灵奖”。——译者注
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[36] Crick, F. (1989), Nature 337: 129–32, p. 130.
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[37] Crick, F. (1994), The Astonishing Hypothesis: The Scientific Search for the Soul (New York: Charles Scribner’s Sons), p. 186.
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