Dale Purves

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Dale Purves
Born (1938-03-11)March 11, 1938
Fields Neuroscience
Alma mater Yale University
Harvard Medical School

Dale Purves (born March 11, 1938) is George Barth Geller Professor for Research in Neurobiology at Duke University. He was the Director of the Neuroscience and Behavioral Disorders program at Duke-NUS Graduate Medical School and Executive Director of the A*STAR Neuroscience Research Partnership from 2009 to 2014 in Singapore. From 2003 to 2009 he was Director of Center for Cognitive Neuroscience. After several years in clinical medicine as a surgical house officer at the Massachusetts General Hospital and as a Peace Corps Physician, he gave up medicine in favor of a career in neuroscience research. He received a Bachelor of Arts degree from Yale University in 1960 and a Doctor of Medicine from Harvard Medical School in 1964.[citation needed]Following a postdoctoral fellow in the Department of Neurobiology at Harvard from 1968 to 1971 and in the Department of Biophysics, University College London, from 1971 to 1973. He joined the faculty in the Department of Physiology and Biophysics at the Washington University in 1971, where he remained until 1990. During that time he studied the development of the nervous system, and was elected to the United States National Academy of Sciences in 1989.[citation needed] He came to Duke in 1990 as the founding chair of the Department of Neurobiology,where he became increasingly interested in cognitive neuroscience. Purves's work at Duke has focused on visual and auditory perception (including music), exploring the hypothesis that, as a means of contending with the inverse problem, percepts are generated by a neural strategy that depends on the empirical significance for reproductive success of stimuli created by sensory systems rather than the physical parameters of the real world (see empirical theory of perception).[citation needed]

Empirical theory of perception[edit]

According to the wholly empirical theory of perception developed by Purves, R. Beau Lotto and others, perception and sensory function generally must be understood as the outcome of a neural strategy whose goal is to generate appropriate behavior despite the absence of real world measurement. Since the inverse problem precludes direct analysis of objects, this strategy uses the history of the species and individual to associate sensory signals with successful behavior. For example, the perception of lightness is confounded by the fact that a visual image conflates illumination, reflection and transmittance. Because the eye receives only the final product, the visual system cannot logically determine the relative contributions of these factors. Successful behavior and reproduction nonetheless depend on the ability to discriminate these different factors. In an empirical account, the frequency with which stimuli occur determines what humans and other animals actually perceive. This strategy determines perceptual qualities of color, contrast, distance, size, line orientation and angles, and motion.

Published works[edit]

  • Purves, Dale (1985). Principles of Neural Development, Sinauer Associates, 433 pages. ISBN 978-0878937448
  • Purves D, Lotto RB (2003) Why we see what we do: An empirical theory of vision. Sunderland, MA: Sinauer Associates[1].
  • Purves et al. (2007) Principles of Cognitive Neuroscience. Sunderland,MA: Sinauer Associates, 2007[2]
  • Purves D, Augustine GA, Fitzpatrick D, Hall W, LaMantia A-S, McNamara JO, Williams SM (2008) Neuroscience, 4th edition. Sinauer Associates: Sunderland, MA[3]..
  • Purves D (2010) Brains: How they Seem to Work. Financial Times Press, New Jersey. [4]
  • Purves D, Lotto RB (2011) Why We See What We Do Redux: A Wholly Empirical Theory of Vision. Sinauer Associates, Inc, United States of America.[5]
  • Yang, Z.; Purves, D. (2003). Image/Source statistics in natural scenes. Network: Computation in Neural Systems 14: 371–390[6].
  • Yang, Z.; Purves, D. (2003). "A statistical explanation of visual space", Nature, Neuroscience 6: 632–640
  • Schwartz D, Howe CQ, Purves D (2003) The statistical structure of human speech sounds predicts musical universals. J Neurosci 23:7160–7168[7].
  • Howe Q, Purves D (2003) Size contrast explained by the statistics of scene geometry. J Cog Neurosci 16:90–102[8].
  • Long F, Purves D (2003) Natural scene statistics as a universal basis for color context effects. Proc Natl Acad Sci 100 (25): 15190–15193.[9]
  • Purves D, Williams MS, Nundy S, Lotto RB (2004) Perceiving the intensity of light. Psychological Rev 111(1): 142–158.
  • Yang Z, Purves D (2004) The statistical structure of natural light patterns determines perceived light intensity. Proc Natl Acad Sci 101: 8745–8750[10].
  • Schwartz D, Purves D (2004) Pitch is determined by naturally occurring periodic sounds. Hearing Research 194: 31–46[11].
  • Howe CQ, Purves D (2005) Natural scene geometry predicts the perception of angles and line orientation. Proc Natl Acad Sci 102: 1228–1233[12].
  • Howe CQ, Purves D (2005) The Müller-Lyer illusion explained by the statistics of image-source relationships. Proc Natl Acad Sci 102: 1234–1239[13].
  • Howe CQ, Yang Z, Purves D (2005) The Poggendorff illusion explained by natural scene statistics of image-source relationships. Proc Natl Acad Sci 102:7707–7712 [14].
  • Long F, Yang Z, Purves D (2006) Spectral statistics in natural scene predict hue, saturation, and brightness. Proc Natl Acad Sci 103: 6013–6018[15].
  • Howe CQ, Lotto RB, Purves D (2006) Comparison of bayesian and empirical ranking approaches to visual perception. J Theor Biol 241: 866–875[16].
  • Boots B, Nundy S, Purves D (2007) Evolution of visually-guided behavior in artificial agents. Network: Computation in Neural Systems 18 (1): 1–24[17].
  • Ross D, Choi J, Purves D (2007) Musical intervals in speech. Proc Natl Acad Sci 104(23): 9852–9857[18].
  • Wojtach WT, Sung K, Truong S, Purves D (2008) An empirical explanation of the flash-lag effect. Proc Natl Acad Sci 105(42): 16338–16343[19].
  • Sung K, Wojtach WT, Purves D (2009) An empirical explanation of aperture effects. Proc Natl Acad Sci 106: 298–303[20].
  • Wojtach WT, Sung K, Purves D (2009) An empirical explanation of the speed-distance effect. PLoS ONE 4(8): e6771[21].
  • Gill KZ and Purves D (2009) A biological rationale for musical scales. PLoS ONE 4: e8144[22].
  • Bowling DL, Gill KZ, Choi JD, Prinz J, and Purves D (2010) Major and minor music compared to excited and subdued speech. J Acoust Soc Am 127(1): 491–503.[23].
  • Purves D, Wojtach WT, Lotto RB (2011) Understanding vision in wholly empirical terms. Proc Natl Acad Sci Early Edition: 1-8. [24]
  • Han Se, Sundararajan J, Bowling DL, Lake J, Purves D (2011) Co-variation of tonality in the music and speech of different cultures. PLoS ONE 6(5):e20160. [25]
  • Bowling D, Sundararajan J, Han Se (2012) Expression of Emotion in Eastern and Western music mirrors vocalization. PLoS ONE 7(3): e31942. [26]
  • Ng C, Sundararajan J, Hogan M, Purves D (2013) Network Connections That Evolve to Circumvent the Inverse Optics Problem. PLoS ONE 8(3): e60490. 1. doi:10.1371/journal.pone.0060490 [27]
  • Monson BB, Han S, Purves D (2013) Are Auditory Percepts Determined by Experience? PLoS ONE 8(5): e63728. doi:10.1371/journal.pone.0063728 [28]
  • Purves D, Monson BB, Sundararajan J, Wojtach WT, (2014). How biological vision succeeds in the physical world. Proceedings of the National Academy of Sciences 111: 4750-4755

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