Instructors:
Dan Kersten (kersten@umn.edu)
Vikranth Rao
Guest Instructors:
Steven Engel
Shawn Green
Sheng He
Chad Marsolek
Paul Schrater
Adaptability is a fundamental aspect of behavior and of neural systems. Vision, for example, rapidly adapts to light level, color, contrast, orientation, blur, size, and motion. Sensorimotor behavior rapidly recalibrates for changing task requirements. Human perception also adapts to higher-level properties--even the appearance of a familiar face can change depending on the shapes of faces just seen. Further, the various adaptive processes cover a range of time scales, and mechanisms. Perceptual learning, for example, can involve much training, be highly specific to the training, and last weeks and longer. This seminar will take a bottom-up approach, first focusing on adaptation in early vision, and then moving on to perceptual learning, and higher-level processing. We will look carefully at what is known about early neural coding of image information, and how those codes might change with experience. What determines the specificity of adaptation and learning? How are neural and perceptual resources allocated? Are there common computational principles that apply across a range of behaviors, neural mechanisms, and time scales?
Meeting time : 3:00 to 4:30 Tuesdays.
(First meeting is Tuesday Jan 19th, 2010.)
Place: Elliott S204.
Format: Discussion of journal articles led by seminar members. Students will
prepare a final term paper or computer project on a related topic.
Tentative Schedule
Theory and Background
**Barlow, H. (1990). Conditions for versatile learning, Helmholtz's unconscious inference, and the task of perception. Vision Res, 30(11), 1561-1571.
**Barlow, H. B., & Foldiak, P. (1989). Adaptation and decorrelation in the cortex. In R. Durbin, C. Miall, & G. Mitchison (Ed.), The Computing Neuron (pp. 54-72). Wokingham, England: Addison-Wesley.
*Barraza, J. F., & Grzywacz, N. M. (2008). Speed adaptation as Kalman filtering. Vision Res, 48(23-24), 2485-2491.
***Clifford, C. W., Webster, M. A., Stanley, G. B., Stocker, A. A., Kohn, A., Sharpee, T. O., et al. (2007). Visual adaptation: neural, psychological and computational aspects. Vision Res, 47(25), 3125-3131.
*Cornsweet, T. N., & Yellott, J. I., Jr. (1985). Intensity-dependent spatial summation. J Opt Soc Am A, 2(10), 1769-1786.
*Frazor, R. A., & Geisler, W. S. (2006). Local luminance and contrast in natural images. Vision Res, 46(10), 1585-1598.
***Foldiak, P. (1990). Forming sparse representations by local anti-Hebbian learning. Biol Cybern, 64(2), 165-170.
Foldiak, P. (1991) Learning invariance from transformation sequences, Neural Computation, vol. 3, pp. 194-200, 1991.
Friston, K. (2003). Learning and inference in the brain. Neural Netw, 16(9), 1325-1352.
***Gepshtein, S., Tyukin, I., & Kubovy, M. (2007). The economics of motion perception and invariants of visual sensitivity. J Vis, 7(8), 1-18.
Haith, A., Miall C., Jackson C, & Vijayakumar S (2008) Unifying the Sensory and Motor Components of Sensorimotor Adaptation.
Proceedings of the Neural Information Processing Systems (NIPS 2008), Vancouver, Canada
Jacobs, R. A., & Dominguez, M. (2003). Visual development and the acquisition of motion velocity sensitivities. Neural Comput, 15(4), 761-781.
Jepson A. , D. Fleet, and T. El-Maraghi. (2003) Robust online appearance models for visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(10):1296–1311.
Lyu S and E P Simoncelli (2009) Nonlinear extraction of 'Independent Components' of natural images using radial Gaussianization, Neural Computation, vol.21(6), pp. 1485--1519.
*O'Regan, J. K., & Noe, A. (2001). A sensorimotor account of vision and visual consciousness. Behav Brain Sci, 24(5), 939-973; discussion 973-1031.
***Simoncelli, E. P., & Olshausen, B. A. (2001). Natural image statistics and neural representation. Annu Rev Neurosci, 24, 1193-1216.
**Series. P, Latham, P. and Pouget, A. (2004) Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations. Nature Neuroscience. 7(10):1129-1135.
Seriès P, A A Stocker, and E P Simoncelli (2009) Is the homunculus 'aware' of sensory adaptation?
Neural Computation, vol.21(12), pp. 3271--3304, Dec 2009.
*Schwartz, O., Sejnowski, T. J., & Dayan, P. (2009). Perceptual organization in the tilt illusion. J Vis, 9(4), 19 11-20.
Schwartz, O., & Simoncelli, E. P. (2001). Natural signal statistics and sensory gain control. Nat Neurosci, 4(8), 819-825.
***Schwartz, O., Hsu, A., & Dayan, P. (2007). Space and time in visual context. Nat Rev Neurosci, 8(7), 522-535.
Simoncelli, E P 2009. Optimal estimation in sensory systems. The Cognitive Neurosciences, IV,pages 525--535. MIT Press, Oct 2009.
***Stocker A A and E P Simoncelli, 2006. Sensory adaptation within a Bayesian framework for perception.
Adv. Neural Information Processing Systems (NIPS*05), vol.18 pp. 1291--1298.
*Webster Michael A. , John S. Werner, and David J. Field, (2005) Adaptation and the Phenomenology of Perception. Fitting the Mind to the World: Adaptation and Aftereffects in High Level Vision: Advances in Visual Cognition Series, Volume 2, C. Clifford and G. Rhodes (Eds.) Oxford University Press.
***Wainwright, M. J. (1999). Visual adaptation as optimal information transmission. Vision Research, 39, 3960--3974.
Wainwright Martin J., Odelia Schwartz, Eero P. Simoncelli (2001) Natural Image Statistics and Divisive Normalization: Modeling Nonlinearities and Adaptation in Cortical Neurons. Statistical Theories of the Brain eds. R Rao, B Olshausen and M Lewicki, MIT Press.
Vermaak J, Patrick P´erez, Michel Gangnet, and Andrew Blake (2002) Towards Improved Observation Models for Visual Tracking: Selective Adaptation. A. Heyden et al. (Eds.): ECCV 2002, LNCS 2350, pp. 645–660, 2002. Springer-Verlag Berlin Heidelberg.
*Yu, Y., Potetz, B., & Lee, T. S. (2005). The role of spiking nonlinearity in contrast gain control and information transmission. Vision Res, 45(5), 583-592.
Behavior
***Adams, W. J., Banks, M. S., & van Ee, R. (2001). Adaptation to three-dimensional distortions in human vision. Nat Neurosci, 4(11), 1063-1064.
Adams, W.J., Mamassian, P., 2002. Common mechanisms for 2D tilt and 3D slant after-effects. Vision Res. 42, 2563–2568.
*Arnold, D. H., Birt, A., & Wallis, T. S. (2008). Perceived size and spatial coding. J Neurosci, 28(23), 5954-5958.
*Bex, P. J., Mareschal, I., & Dakin, S. C. (2007). Contrast gain control in natural scenes. J Vis, 7(11), 12 11-12.
**Blakemore, C., & Campbell, F. W. (1969). On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images. J Physiol, 203(1), 237-260.
Blakemore, C., & Campbell, F. W. (1969). Adaptation to spatial stimuli. J Physiol, 200(1), 11P-13P.
*Bompas, A., & O'Regan, J. K. (2006). Evidence for a role of action in colour perception. Perception, 35(1), 65-78.
*Bradley, M. M., Lang, P. J., & Cuthbert, B. N. (1993). Emotion, novelty, and the startle reflex: habituation in humans. Behav Neurosci, 107(6), 970-980.
**Burge, J., Ernst, M. O., & Banks, M. S. (2008). The statistical determinants of adaptation rate in human reaching. J Vis, 8(4), 20 21-19.
Clifford, C. W. (2002). Perceptual adaptation: motion parallels orientation. Trends Cogn Sci, 6(3), 136-143.
Clifford, C. W., Wyatt, A. M., Arnold, D. H., Smith, S. T., & Wenderoth, P. (2001). Orthogonal adaptation improves orientation discrimination. Vision Res, 41(2), 151-159.
Falconbridge, M., Wozny, D., Shams, L., & Engel, S. A. (2009). Adapting to altered image statistics using processed video. Vision Res, 49(14), 1757-1764.
*Fine, I., & Jacobs, R. A. (2002). Comparing perceptual learning tasks: a review. J Vis, 2(2), 190-203.
Fox, C. J., & Barton, J. J. (2007). What is adapted in face adaptation? The neural representations of expression in the human visual system. Brain Res, 1127(1), 80-89.
**Greenlee, M. W., Georgeson, M. A., Magnussen, S., & Harris, J. P. (1991). The time course of adaptation to spatial contrast. Vision Res, 31(2), 223-236.
Harris, C. S. (1963). Adaptation to displaced vision: visual, motor, or proprioceptive change? Science, 140, 812-813.
Harris, C. S. (1965). Perceptual adaptation to inverted, reversed, and displaced vision. Psychol Rev, 72(6), 419-444.
He, S., Cohen, E. R., & Hu, X. (1998). Close correlation between activity in brain area MT/V5 and the perception of a visual motion aftereffect. Curr Biol, 8(22), 1215-1218.
**He, S., & MacLeod, D. I. (2001). Orientation-selective adaptation and
tilt after-effect from invisible patterns. Nature, 411(6836), 473-476.
He, S., & MacLeod, D. I. (2001). Orientation-selective adaptation and tilt after-effect from invisible patterns. Nature, 411(6836), 473-476.
**Hood, D. C. (1998). Lower-level visual processing and models of light adaptation. Annu Rev Psychol, 49, 503-535.
**Kording, K. P., & Wolpert, D. M. (2004). Bayesian integration in sensorimotor learning. Nature, 427(6971), 244-247.
***Kording, K. P., Tenenbaum, J. B., & Shadmehr, R. (2007). The dynamics of memory as a consequence of optimal adaptation to a changing body. Nat Neurosci, 10(6), 779-786.
*Langley, K., Lefebvre, V., & Anderson, S. J. (2009). Cascaded Bayesian processes: an account of bias in orientation perception. Vision Res, 49(20), 2453-2474.
**Leopold, D. A., O'Toole, A. J., Vetter, T., & Blanz, V. (2001). Prototype-referenced shape encoding revealed by high-level aftereffects. Nat Neurosci, 4(1), 89-94.
**MacLeod, D. I. (1978). Visual sensitivity. Annu Rev Psychol, 29, 613-645.
*Rhodes, G., Jeffery, L., Watson, T. L., Clifford, C. W., & Nakayama, K. (2003). Fitting the mind to the world: face adaptation and attractiveness aftereffects. Psychol Sci, 14(6), 558-566.
**Schrater, P. R., & Simoncelli, E. P. (1998). Local velocity representation: evidence from motion adaptation. Vision Res, 38(24), 3899-3912.
*Solomon, R. L. (1980). The opponent-process theory of acquired motivation: the costs of pleasure and the benefits of pain. Am Psychol, 35(8), 691-712.
Tolhurst, D. J. (1972). Adaptation to square-wave gratings: inhibition between spatial frequency channels in the human visual system. J Physiol, 226(1), 231-248.
*Stocker A A and E P Simoncelli, 2009. Visual motion aftereffects arise from a cascade of two isomorphic adaptation mechanisms
Journal of Vision, vol.9(9), pp. 1--14.
Watanabe, T., Nanez, J. E., & Sasaki, Y. (2001). Perceptual learning without perception. Nature, 413(6858), 844-848.
Webster, M. A., Georgeson, M. A., & Webster, S. M. (2002). Neural adjustments to image blur. Nat Neurosci, 5(9), 839-840.
**Webster, M. A., Kaping, D., Mizokami, Y., & Duhamel, P. (2004). Adaptation to natural facial categories. Nature, 428(6982), 557-561.
Webster, Michael A 1996. Human colour perception and its adaptation.Network: Computation in Neural Systems 7 (1996) 587–634.
Webster, M. A., & MacLin, O. H. (1999). Figural aftereffects in the perception of faces. Psychon Bull Rev, 6(4), 647-653.
Webster, M. A., & Miyahara, E. (1997). Contrast adaptation and the spatial structure of natural images. J Opt Soc Am A Opt Image Sci Vis, 14(9), 2355-2366.
Webster, M. A., & Mollon, J. D. (1997). Adaptation and the color statistics of natural images. Vision Res, 37(23), 3283-3298.
**Wu, J., Xu, H., Dayan, P., & Qian, N. (2009). The role of background statistics in face adaptation. J Neurosci, 29(39), 12035-12044.
Neurobiology and Imaging
***Bonin, V., Mante, V., & Carandini, M. (2006). The statistical computation underlying contrast gain control. J Neurosci, 26(23), 6346-6353.
Boynton, G. M., & Finney, E. M. (2003). Orientation-specific adaptation in human visual cortex. J Neurosci, 23(25), 8781-8787.
Carandini, M. (2000). Visual cortex: Fatigue and adaptation. Curr Biol, 10(16),
R605-607.
Carandini, M., Barlow, H. B., O'Keefe, L. P., Poirson, A. B., & Movshon, J. A. (1997). Adaptation to contingencies in macaque primary visual cortex. Philos Trans R Soc Lond B Biol Sci, 352(1358), 1149-1154.
Duong, T., & Freeman, R. D. (2007). Spatial frequency-specific contrast adaptation originates in the primary visual cortex. J Neurophysiol, 98(1), 187-195.
**Fairhall, A. L., Lewen, G. D., Bialek, W., & de Ruyter Van Steveninck, R. R. (2001). Efficiency and ambiguity in an adaptive neural code. Nature, 412(6849), 787-792.
*Fang, F., Murray, S. O., & He, S. (2007). Duration-dependent FMRI adaptation and distributed viewer-centered face representation in human visual cortex. Cereb Cortex, 17(6), 1402-1411.
Fang, F., Murray, S. O., Kersten, D., & He, S. (2005). Orientation-tuned FMRI adaptation in human visual cortex. J Neurophysiol, 94(6), 4188-4195.
*Furmanski, C. S., Schluppeck, D., & Engel, S. A. (2004). Learning strengthens the response of primary visual cortex to simple patterns. Curr Biol, 14(7), 573-578.
*Georgeson, M. A., & Sullivan, G. D. (1975). Contrast constancy: deblurring in human vision by spatial frequency channels. J Physiol, 252(3), 627-656.
*Hosoya, T., Baccus, S. A., & Meister, M. (2005). Dynamic predictive coding by the retina. Nature, 436(7047), 71-77.
Jin, D. Z., Dragoi, V., Sur, M., & Seung, H. S. (2005). Tilt aftereffect and adaptation-induced changes in orientation tuning in visual cortex. J Neurophysiol, 94(6), 4038-4050.
***Kohn, A. (2007). Visual adaptation: physiology, mechanisms, and functional benefits. J Neurophysiol, 97(5), 3155-3164.
Kohn, A., & Movshon, J. A. (2004). Adaptation changes the direction tuning of macaque MT neurons. Nat Neurosci, 7(7), 764-772.
Kohn, A., & Movshon, J. A. (2003). Neuronal adaptation to visual motion in area MT of the macaque. Neuron, 39(4), 681-691.=
*Koob, G. F., & Le Moal, M. (2008). Review. Neurobiological mechanisms for opponent motivational processes in addiction. Philos Trans R Soc Lond B Biol Sci, 363(1507), 3113-3123.
*Leknes, S., Brooks, J. C., Wiech, K., & Tracey, I. (2008). Pain relief as an opponent process: a psychophysical investigation. Eur J Neurosci, 28(4), 794-801.
Li, N., & DiCarlo, J. J. (2008). Unsupervised natural experience rapidly alters invariant object representation in visual cortex. Science, 321(5895), 1502-1507.
***Mante, V., Frazor, R. A., Bonin, V., Geisler, W. S., & Carandini, M. (2005). Independence of luminance and contrast in natural scenes and in the early visual system. Nat Neurosci, 8(12), 1690-1697.
Mohr, H. M., Linder, N. S., Linden, D. E., Kaiser, J., & Sireteanu, R. (2009). Orientation-specific adaptation to mentally generated lines in human visual cortex. Neuroimage, 47(1), 384-391.
*Muller, J. R., Metha, A. B., Krauskopf, J., & Lennie, P. (1999). Rapid adaptation in visual cortex to the structure of images. Science, 285(5432), 1405-1408.
*Sharpee, T. O., Sugihara, H., Kurgansky, A. V., Rebrik, S. P., Stryker, M. P., & Miller, K. D. (2006). Adaptive filtering enhances information transmission in visual cortex. Nature, 439(7079), 936-942.
Sengpiel, F., & Bonhoeffer, T. (2002). Orientation specificity of contrast adaptation in visual cortical pinwheel centres and iso-orientation domains. Eur J Neurosci, 15(5), 876-886.
*Vargas-Perez, H., Ting, A. K. R. A., Heinmiller, A., Sturgess, J. E., & van der Kooy, D. (2007). A test of the opponent-process theory of motivation using lesions that selectively block morphine reward. Eur J Neurosci, 25(12), 3713-3718.
Vul, E., & MacLeod, D. I. (2006). Contingent aftereffects distinguish conscious and preconscious color processing. Nat Neurosci, 9(7), 873-874.
**Vul, E., Krizay, E., & MacLeod, D. I. (2008). The McCollough effect reflects permanent and transient adaptation in early visual cortex. J Vis, 8(12), 4 1-12.
**Wark, B., Fairhall, A., & Rieke, F. (2009). Timescales of inference in visual adaptation. Neuron, 61(5), 750-761.
Yang, T., & Maunsell, J. H. (2004). The effect of perceptual learning on neuronal responses in monkey visual area V4. J Neurosci, 24(7), 1617-1626.
Yao, H., & Dan, Y. (2001). Stimulus timing-dependent plasticity in cortical processing of orientation. Neuron, 32(2), 315-323.
Yao, H., Shen, Y., & Dan, Y. (2004). Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning. Proc Natl Acad Sci U S A, 101(14), 5081-5086.