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20 Years of Learning About Vision: Questions Answered, Questions Unanswered, and Questions Not Yet Asked

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20 Years of Computational Neuroscience

Part of the book series: Springer Series in Computational Neuroscience ((NEUROSCI,volume 9))

Abstract

I have been asked to review the progress that computational neuroscience has made over the past 20 years in understanding how vision works. In reflecting on this question, I come to the conclusion that perhaps the most important advance we have made is in gaining a deeper appreciation of the magnitude of the problem before us. While there has been steady progress in our understanding—and I will review some highlights here—we are still confronted with profound mysteries about how visual systems work. These are not just mysteries about biology, but also about the general principles that enable vision in any system whether it be biological or machine. I devote much of this chapter to examining these open questions, as they are crucial in guiding and motivating current efforts. Finally, I shall argue that the biggest mysteries are likely to be ones we are not currently aware of, and that bearing this in mind is important as it encourages a more exploratory, as opposed to strictly hypothesis-driven, approach.

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Acknowledgments

I thank Jim Bower for encouraging me to write this article and for his patience in giving me the time to complete it, and Jim DiCarlo for providing the MIT AI Memo. Supported by funding from NSF (IIS-1111654), NIH (EY019965), NGA (HM1582-08-1-0007), and the Canadian Institute for Advanced Research.

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  1. Helen Wills Neuroscience Institute and School of Optometry, University of California—Berkeley, Berkeley, CA, USA

    Bruno A. Olshausen

  2. Redwood Center for Theoretical Neuroscience, UC Berkeley, 575A Evans Hall, MC 3198, Berkeley, CA, 94720-3198, USA

    Bruno A. Olshausen

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Olshausen, B.A. (2013). 20 Years of Learning About Vision: Questions Answered, Questions Unanswered, and Questions Not Yet Asked. In: Bower, J. (eds) 20 Years of Computational Neuroscience. Springer Series in Computational Neuroscience, vol 9. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1424-7_12

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