词条 | David Heeger |
释义 |
| name = David J. Heeger | birth_date = {{Birth year and age|1961}} | birth_place = Berkeley, CA | residence = New York City, United States | nationality = American | field = Neuroscience (Visual Neuroscience, Computational Neuroscience, Systems Neuroscience, perceptual psychology, cognitive neuroscience, image processing, computer vision, computer graphics | work_institution = New York University (professor) | prizes = David Marr Prize 1987, Alfred P. Sloan Research Fellowship 1994, Troland Research Award 2002, National Academy of Sciences 2013. }} David J. Heeger (born 1961) is an American professor of psychology and neural science at New York University whose research spans a cross-section of engineering, psychology, and neuroscience. In the fields of perceptual psychology, systems neuroscience, cognitive neuroscience, and computational neuroscience, Heeger has developed computational theories of neuronal processing in the visual system, and he has performed psychophysics (perceptual psychology) and neuroimaging (functional magnetic resonance imaging, fMRI)[1][2][3] experiments on human vision. His contributions to computational neuroscience include theories for how the brain can sense optic flow[4][5] and egomotion,[6] and a theory of neural processing called the normalization model.[7][8][9][10] His empirical research has contributed to our understanding of the topographic organization of visual cortex (retinotopy),[11][12][13][14][15] visual awareness,[16][17][18] visual pattern detection/discrimination,[19][20] visual motion perception,[21][22][23] stereopsis (depth perception),[24] attention,[25][26][27][28] working memory, the control of eye and hand movements, neural processing of complex audio-visual and emotional experiences (movies, music, narrative),[29][30] abnormal visual processing in dyslexia,[31][32] and neurophysiological characteristics of autism.[33][34][35] In the fields of image processing, computer vision, and computer graphics, Heeger worked on motion estimation and image registration, wavelet image representations,[36] anisotropic diffusion (edge-preserving noise reduction),[37] image fidelity metrics (for evaluating image data compression algorithms), and texture analysis/synthesis.[38] Heeger holds a bachelor's degree in mathematics as well as a master's degree and doctorate in computer science—all from the University of Pennsylvania.{{citation needed|date=January 2019}} He was a postdoctoral fellow at MIT, a research scientist at the NASA-Ames Research Center, and an associate professor at Stanford before joining NYU. Heeger was awarded the David Marr Prize in computer vision in 1987, an Alfred P. Sloan Research Fellowship in neuroscience in 1994, the Troland Research Award in psychology from the National Academy of Sciences in 2002, and the Margaret and Herman Sokol Faculty Award in the Sciences from New York University in 2006.{{citation needed|date=January 2019}} He was elected to the National Academy of Sciences in 2013. His father is the Nobel laureate physicist Alan J. Heeger.{{citation needed|date=January 2019}} References1. ^Boynton, G.M., et al., Linear systems analysis of functional magnetic resonance imaging in human V1. J Neurosci, 1996. 16(13): p. 4207-21. 2. ^Heeger, D.J. and D. Ress, What does fMRI tell us about neuronal activity? Nat Rev Neurosci, 2002. 3(2): p. 142-51. 3. ^Heeger, D.J., et al., Spikes versus BOLD: what does neuroimaging tell us about neuronal activity? Nat Neurosci, 2000. 3(7): p. 631-3. 4. ^Heeger, D.J., Model for the extraction of image flow. J Opt Soc Am [A], 1987. 4(8): p. 1455-71. 5. ^Simoncelli, E.P. and D.J. Heeger, A model of neuronal responses in visual area MT. Vision Res, 1998. 38(5): p. 743-61. 6. ^Heeger, D.J. and A.D. Jepson, Subspace methods for recovering rigid motion I: Algorithm and implementation. International Journal of Computer Vision, 1992. 7: p. 95-117. 7. ^Carandini, M., D.J. Heeger, and J.A. Movshon, Linearity and normalization in simple cells of the macaque primary visual cortex. J Neurosci, 1997. 17(21): p. 8621-44. 8. ^Carandini, M. and D.J. Heeger, Normalization as a canonical neural computation. Nat Rev Neurosci, 2012. 13(1): p. 51-62. 9. ^Carandini, M. and D.J. Heeger, Summation and division by neurons in primate visual cortex. Science, 1994. 264(5163): p. 1333-6. 10. ^Heeger, D.J., Normalization of cell responses in cat striate cortex. Vis Neurosci, 1992. 9(2): p. 181-197. 11. ^Gardner, J.L., et al., Maps of visual space in human occipital cortex are retinotopic, not spatiotopic. J Neurosci, 2008. 28(15): p. 3988-99. 12. ^Larsson, J. and D.J. Heeger, Two retinotopic visual areas in human lateral occipital cortex. J Neurosci, 2006. 26(51): p. 13128-42. 13. ^Schluppeck, D., P. Glimcher, and D.J. Heeger, Topographic organization for delayed saccades in human posterior parietal cortex. J Neurophysiol, 2005. 94(2): p. 1372-84. 14. ^Silver, M.A., D. Ress, and D.J. Heeger, Topographic maps of visual spatial attention in human parietal cortex. J Neurophysiol, 2005. 94(2): p. 1358-71. 15. ^Huk, A.C., R.F. Dougherty, and D.J. Heeger, Retinotopy and functional subdivision of human areas MT and MST. J Neurosci, 2002. 22(16): p. 7195-7205. 16. ^Polonsky, A., et al., Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry. Nat Neurosci, 2000. 3(11): p. 1153-9. 17. ^Lee, S.H., R. Blake, and D.J. Heeger, Traveling waves of activity in primary visual cortex during binocular rivalry. Nat Neurosci, 2005. 8(1): p. 22-3. 18. ^Lee, S.H., R. Blake, and D.J. Heeger, Hierarchy of cortical responses underlying binocular rivalry. Nat Neurosci, 2007. 10(8): p. 1048-54. 19. ^Ress, D. and D.J. Heeger, Neuronal correlates of perception in early visual cortex. Nat Neurosci, 2003. 10: p. 10. 20. ^Boynton, G.M., et al., Neuronal basis of contrast discrimination. Vision Res, 1999. 39(2): p. 257-69. 21. ^Huk, A.C., D. Ress, and D.J. Heeger, Neuronal basis of the motion aftereffect reconsidered. Neuron, 2001. 32(1): p. 161-72. 22. ^Huk, A.C. and D.J. Heeger, Pattern-motion responses in human visual cortex. Nat Neurosci, 2002. 5(1): p. 72-5. 23. ^Heeger, D.J., et al., Motion opponency in visual cortex. J Neurosci, 1999. 19(16): p. 7162-74. 24. ^Backus, B.T., et al., Human cortical activity correlates with stereoscopic depth perception. J Neurophysiol, 2001. 86(4): p. 2054-68. 25. ^Reynolds, J.H. and D.J. Heeger, The normalization model of attention. Neuron, 2009. 61(2): p. 168-85. 26. ^Herrmann, K., et al., When size matters: attention affects performance by contrast or response gain. Nat Neurosci, 2010. 13(12): p. 1554-9. 27. ^Ress, D., B.T. Backus, and D.J. Heeger, Activity in primary visual cortex predicts performance in a visual detection task. Nat Neurosci, 2000. 3(9): p. 940-945. 28. ^Gandhi, S.P., D.J. Heeger, and G.M. Boynton, Spatial attention affects brain activity in human primary visual cortex. Proc Natl Acad Sci U S A, 1999. 96(6): p. 3314-9. 29. ^Hasson, U., et al., A hierarchy of temporal receptive windows in human cortex. J Neurosci, 2008. 28(10): p. 2539-50. 30. ^Hasson, U., R. Malach, and D.J. Heeger, Reliability of cortical activity during natural stimulation. Trends Cogn Sci, 2010. 14(1): p. 40-8. 31. ^Demb, J.B., G.M. Boynton, and D.J. Heeger, Brain activity in visual cortex predicts individual differences in reading performance. Proc Natl Acad Sci U S A, 1997. 94(24): p. 13363-6. 32. ^Demb, J.B., G.M. Boynton, and D.J. Heeger, Functional magnetic resonance imaging of early visual pathways in dyslexia. J Neurosci, 1998. 18(17): p. 6939-51. 33. ^Dinstein, I., et al., A mirror up to nature. Curr Biol, 2008. 18(1): p. R13-8. 34. ^Dinstein, I., et al., Normal movement selectivity in autism. Neuron, 2010. 66(3): p. 461-9. 35. ^Dinstein, I., et al., Unreliable evoked responses in autism. Neuron, 2012. 75(6): p. 981-91. 36. ^Simoncelli, E.P., et al., Shiftable multi-scale transforms. IEEE Transactions on Information Theory, Special Issue on Wavelets, 1992. 38: p. 587-607. 37. ^Black, M., et al., Robust anisotropic diffusion. IEEE Transactions on Image Processing, 1998. 7: p. 421-432. 38. ^Heeger, D.J. and J.R. Bergen. Pyramid-Based Texture Analysis/Synthesis. in Computer Graphics, SIGGRAPH Proceedings. 1995. External links
6 : Members of the United States National Academy of Sciences|American neuroscientists|Jewish American scientists|New York University faculty|Living people|1960 births |
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