Stochastic characterization of small-scale algorithms for human sensory processing

Chaos

Volumn 20, Issue 4, 2010, Pages

  Neri, Peter ^a  

^a UNIVERSITY OF ABERDEEN   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; HUMAN; KINETICS; NONLINEAR SYSTEM; PERCEPTION; PHYSIOLOGY; SENSATION; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; HUMANS; KINETICS; LINEAR MODELS; MODELS, BIOLOGICAL; NONLINEAR DYNAMICS; PERCEPTION; SENSATION; STOCHASTIC PROCESSES;

EID: 78650696144     PISSN: 10541500     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.3524305     Document Type: Article

References (89)

1. Abbey C.K. Eckstein M.P. Classification image analysis: Estimation and statistical inference for two-alternative forced-choice experiments. J. Vision 2002, 2:66-78. ZZZZZZ, 1534-7362, 10.1167/2.1.5.
2. Afraz S.R. Kiani R. Esteky H. Microstimulation of inferotemporal cortex influences face categorization. Nature (London) 2006, 442:692-695. NATUAS, 0028-0836, 10.1038/nature04982.
3. Ahumada A.J. Classification image weights and internal noise level estimation. J. Vision 2002, 2:121-131. ZZZZZZ, 1534-7362, 10.1167/2.1.8.
4. Ahumada A.J. Marken R. Sandusky A. Time and frequency analyses of auditory signal detection. J. Opt. Soc. Am. A Opt. Image Sci. Vis 1975, 57:385-390. ZZZZZZ, 1084-7529.
5. Barlow H.B. Levick W.R. Yoon M. Responses to single quanta of light in retinal ganglion cells of the cat. Vision Res. 1971, 11:87-101. VISRAM, 0042-6989, 10.1016/0042-6989(71)90033-2.
6. Benardete E.A. Kaplan E. The dynamics of primate M retinal ganglion cells. Visual Neurosci. 1999, 16:355-368. VNEUEY, 0952-5238, 10.1017/S0952523899162151.
7. Bergen J.R. Landy M.S. Computational models of visual texture segregation. Computational Models of Visual Processing 1991, 253-271. M. Landy, J. Movshon, and in edited by and (MIT, Cambridge, MA), pp.
8. Born R.T. Bradley D.C. Structure and function of visual area MT. Annu. Rev. Neurosci. 2005, 28:157-189. ARNSD5, 0147-006X, 10.1146/annurev.neuro.26.041002.131052.
9. Borst A. Flanagin V.L. Sompolinsky H. Adaptation without parameter change: Dynamic gain control in motion detection. Proc. Natl. Acad. Sci. U.S.A. 2005, 102:6172-6176. PNASA6, 0027-8424, 10.1073/pnas.0500491102.
10. Burgess A.E. Colborne B. Visual signal detection. IV. Observer inconsistency. J. Opt. Soc. Am. A 1988, 5:617-627. JOAOD6, 0740-3232, 10.1364/JOSAA.5.000617.
11. Busse L. Katzner S. Tillmann C. Treue S. Effects of attention on perceptual direction tuning curves in the human visual system. J. Vision 2008, 8:1-13. ZZZZZZ, 1534-7362, 10.1167/8.9.2.
12. Bussgang J.J. Cross-correlation functions of amplitude-distorted Gaussian signals. 1952, MIT Research Laboratory Electricity Technical Report No. 216, August.
13. Citron M.C. Marmarelis V.Z. Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics. Biol. Cybern. 1987, 57:241-247. BICYAF, 0340-1200, 10.1007/BF00338817.
14. Falmagne J.-C. Elements of Psychophysical Theory 1985, (Oxford University Press, New York).
15. Franz M.O. Schölkopf B. A unifying view of Wiener and Volterra theory and polynomial kernel regression. Neural Comput. 2006, 18:3097-3118. NEUCEB, 0899-7667, 10.1162/neco.2006.18.12.3097.
16. French A.S. Korenberg M.J. Jarvilehto M. Kouvalainen E. Juusola M. Weckstrom M. The dynamic nonlinear behavior of fly photoreceptors evoked by a wide range of light intensities. Biophys. J. 1993, 65:832-839. BIOJAU, 0006-3495, 10.1016/S0006-3495(93)81116-0.
17. Geisler W.S. Ideal observer theory in psychophysics and physiology. Phys. Scr. 1989, 39:153-160. PHSTBO, 0031-8949, 10.1088/0031-8949/39/1/025.
18. Gold J.I. Shadlen M.N. The neural basis of decision making. Annu. Rev. Neurosci. 2007, 30:535-574. ARNSD5, 0147-006X, 10.1146/annurev.neuro.29.051605.113038.
19. Gosselin F. Schyns P.G. Superstitious perceptions reveal properties of internal representations. Psychol. Sci. 2003, 14:505-509. ZZZZZZ, 0956-7976, 10.1111/1467-9280.03452.
20. Green D.M. Swets J.A. Signal Detection Theory and Psychophysics 1966, and (Wiley, New York).
21. Gregson R.A. Britton L.A. The size-weight illusion in 2-D nonlinear psychophysics. Percept. Psychophys. 1990, 48:343-356. PEPSBJ, 0031-5117.
22. Guastello S.J. Nonlinear dynamics in psychology. Discrete Dyn. Nat. Soc. 2001, 6:11-29. DDNSFA, 1026-0226, 10.1155/S1026022601000024.
23. Heath R.A. Nonlinear Dynamics: Techniques and Applications in Psychology 2000, (Lawrence Erlbaum Associates, New Jersey).
24. Heath R.A. Fulham R. Applications of system identification and adaptive filtering techniques in human information processing. Cognition, Information Processing and Motivation 1985, 117-147. G. d'Ydewalle, and in edited by (Elsevier Science, Amsterdam), pp.
25. Heeger D.J. Simoncelli E.P. Movshon J.A. Computational models of cortical visual processing. Proc. Natl. Acad. Sci. U.S.A. 1996, 93:623-627. PNASA6, 0027-8424, 10.1073/pnas.93.2.623.
26. Hunter I.W. Korenberg M.J. The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biol. Cybern. 1986, 55:135-144. BICYAF, 0340-1200.
27. James A.C. Nonlinear operator network models of processing in the fly lamina. Nonlinear Vision 1992, 39-73. R. B. Pinter, B. Nabet, in edited by and (CRC, Boca Raton, FL), pp.
28. Kelly A. Heathcote A. Heath R. Longstaff M. Response-time dynamics: Evidence for linear and low-dimensional nonlinear structure in human choice sequences. Q. J. Exp. Psychol. A 2001, 54:805-840. ZZZZZZ, 0272-4987, 10.1080/02724980042000327.
29. Kohn A. Visual adaptation: Physiology, mechanisms, and functional benefits. J. Neurophysiol. 2007, 97:3155-3164. JONEA4, 0022-3077, 10.1152/jn.00086.2007.
30. Korenberg M.J. Parallel cascade identification and kernel estimation for nonlinear systems. Ann. Biomed. Eng. 1991, 19:429-455. ABMECF, 0090-6964, 10.1007/BF02584319.
31. Korenberg M.J. Hunter I.W. The identification of nonlinear biological systems: LNL cascade models. Biol. Cybern. 1986, 55:125-134. BICYAF, 0340-1200.
32. Landy M.S. Graham N. Visual perception of texture. The Visual Neurosciences 2004, 1106-1118. L. M. Chalupa, J. S. Werner, and in edited by and (MIT, Cambridge, MA), pp.
33. Lasley D.J. Cohn T.E. Why luminance discrimination may be better than detection. Vision Res. 1981, 21:273-278. VISRAM, 0042-6989, 10.1016/0042-6989(81)90121-8.
34. Lennie P. Single units and visual cortical organization. Perception 1998, 27:889-935. ZZZZZZ, 0301-0066, 10.1068/p270889.
35. Luce R.D. Four tensions concerning mathematical modeling in psychology. Annu. Rev. Psychol. 1995, 46:1-27. ARPSAC, 0066-4308, 10.1146/annurev.ps.46.020195.000245.
36. Luce R.D. Response Times: Their Role in Inferring Elementary Mental Organization 1986, (Oxford University Press, New York).
37. Maljkovic V. Martini P. Implicit short-term memory and event frequency effects in visual search. Vision Res. 2005, 45:2831-2846. VISRAM, 0042-6989, 10.1016/j.visres.2005.05.019.
38. Maloney L.T. Zhang H. Decision-theoretic models of visual perception and action. Vision Res. 2010, 50:2362-2374. VISRAM, 0042-6989, 10.1016/j.visres.2010.09.031.
39. Marmarelis P.Z. Identification of nonlinear biological systems using Laguerre expansions of kernels. Ann. Biomed. Eng. 1993, 21:573-589. ABMECF, 0090-6964, 10.1007/BF02368639.
40. Marmarelis P.Z. Marmarelis V.Z. Analysis of Physiological Systems: The White-Noise Approach 1978, and (Plenum, New York).
41. Marmarelis V.Z. Nonlinear Dynamic Modeling of Physiological Systems 2004, (Wiley IEEE, Piscataway, NJ).
42. Mather G. Pavan A. Campana G. Casco C. The motion after-effect reloaded. Trends Cogn. Sci. 2008, 12:481-487. TCSCFK, 1364-6613, 10.1016/j.tics.2008.09.002
43. Metzger M.A. Theisz M.F. Forecast: Program to obtain forecasts from subjects for successive values of chaotic time series. Behav. Res. Methods Instrum. Comput. 1994, 26:387-394. BRMCEW, 0743-3808.
44. Mountcastle V.B. LaMotte R.H. Carli G. Detection thresholds for stimuli in humans and monkeys: Comparison with threshold events in mechanoreceptive afferent nerve fibers innervating the monkey hand. J. Neurophysiol. 1972, 35:122-136. JONEA4, 0022-3077.
45. Murdock B.B. Human Memory: Theory and Data 1974, (Lawrence Erlbaum Associates, MD).
46. Murray R.F. Bennett P.J. Sekuler A.B. Optimal methods for calculating classification images: Weighted sums. J. Vision 2002, 2:79-104. ZZZZZZ, 1534-7362, 10.1167/2.1.6.
47. Neri P. Estimation of nonlinear psychophysical kernels. J. Vision 2004, 4:82-91. ZZZZZZ, 1534-7362, 10.1167/4.2.2.
48. Neri P. Fast-scale adaptive changes of directional tuning in fly tangential cells are explained by a static nonlinearity. J. Exp. Biol. 2007, 210:3199-3208. JEBIAM, 0022-0949, 10.1242/jeb.006726.
49. Neri P. How inherently noisy is human sensory processing?. Psychon. Bull. Rev. 2010, 17:802-808. PBUREN, 1069-9384.
50. Neri P. Nonlinear characterization of a simple process in human vision. J. Vision 2009, 9:1-29. ZZZZZZ, 1534-7362, 10.1167/9.12.1.
51. Neri P. Visual detection under uncertainty operates via an early static, not late dynamic, non-linearity. Front. Comput. Neurosci. 2010, 4:151. 10.3389/fncom.2010.00151.
52. Neri P. Heeger D.J. Spatiotemporal mechanisms for detecting and identifying image features in human vision. Nat. Neurosci. 2002, 5:812-816. NANEFN, 1097-6256.
53. Neri P. Levi D. Temporal dynamics of directional selectivity in human vision. J. Vision 2008, 8:1-11. ZZZZZZ, 1534-7362, 10.1167/8.1.22.
54. Neri P. Levi D.M. Evidence for joint encoding of motion and disparity in human visual perception. J. Neurophysiol. 2008, 100:3117-3133. JONEA4, 0022-3077, 10.1152/jn.90271.2008.
55. Neri P. Levi D.M. Receptive versus perceptive fields from the reverse-correlation viewpoint. Vision Res. 2006, 46:2465-2474. VISRAM, 0042-6989, 10.1016/j.visres.2006.02.002.
56. Neuringer A. Voss C. Approximating chaotic behavior. Psychol. Sci. 1993, 4:113-119. ZZZZZZ, 0956-7976, 10.1111/j.1467-9280.1993.tb00471.x.
57. Newsome W.T. Visual attention: Spotlights, highlights and visual awareness. Curr. Biol. 1996, 6:357-360. CUBLE2, 0960-9822, 10.1016/S0960-9822(02)00494-3.
58. Newsome W.T. Britten K.H. Movshon J.A. Neuronal correlates of a perceptual decision. Nature (London) 1989, 341:52-54. NATUAS, 0028-0836, 10.1038/341052a0.
59. Newsome W.T. Shadlen M.N. Zohary E. Britten K.H. Visual motion: Linking neuronal activity to psychophysical performance. The Cognitive Neurosciences 1995, 401-414. M. S. Gazzaniga, and in edited by (MIT, Cambridge), pp.
60. Palm G. On representation and approximation of nonlinear systems. Part II: Discrete time. Biol. Cybern. 1979, 34:49-52. BICYAF, 0340-1200, 10.1007/BF00336857.
61. Paninski L. Convergence properties of three spike-triggered analysis techniques. Network 2003, 14:437-464. NWRKEA, 0269-3089, 10.1088/0954-898X/14/3/304.
62. Parker A.J. Newsome W.T. Sense and the single neuron: Probing the physiology of perception. Annu. Rev. Neurosci. 1998, 21:227-277. ARNSD5, 0147-006X, 10.1146/annurev.neuro.21.1.227.
63. Paulin M.G. A method for constructing data-based models of spiking neurons using a dynamic linear-static nonlinear cascade. Biol. Cybern. 1993, 69:67-76. BICYAF, 0340-1200, 10.1007/BF00201409.
64. Pelli D.G. Noise in the visual system may be early. Computational Models of Visual Processing 1991, 147-152. M. Landy, A. J. Movshon, in edited by and (MIT, Cambridge), pp.
65. Pelli D.G. Uncertainty explains many aspects of visual contrast detection and discrimination. J. Opt. Soc. Am. A 1985, 2:1508-1532. JOAOD6, 0740-3232, 10.1364/JOSAA.2.001508.
66. Ringach D.L. Tuning of orientation detectors in human vision. Vision Res. 1998, 38:963-972. VISRAM, 0042-6989, 10.1016/S0042-6989(97)00322-2.
67. Sakai H.M. Wang J.L. Naka K. Contrast gain control in the lower vertebrate retinas. J. Gen. Physiol. 1995, 105:815-835. JGPLAD, 0022-1295, 10.1085/jgp.105.6.815.
68. Schetzen M. The Volterra and Wiener Theories of Nonlinear Systems 1980, (Wiley, New York).
69. Schneider K.A. Komlos M. Attention biases decisions but does not alter appearance. J. Vision 2008, 8:1-10. ZZZZZZ, 1534-7362, 10.1167/8.15.3.
70. Schölkopf B. Smola A.J. Learning with Kernels 2002, and (MIT, Cambridge, MA).
71. Shapley R. Enroth-Cugell C. Visual adaptation and retinal gain controls. Prog. Retinal Res. 1984, 3:263-346. PRRRDH, 0278-4327, 10.1016/0278-4327(84)90011-7.
72. Shub D.E. Richards V.M. Psychophysical spectro-temporal receptive fields in an auditory task. Hear. Res. 2009, 251:1-9. HERED3, 0378-5955, 10.1016/j.heares.2009.02.007.
73. Simpson W.A. Braun W.J. Bargen C. Newman A.J. Identification of the eye-brain-hand system with point processes: A new approach to simple reaction time. J. Exp. Psychol. Hum. Percept. Perform. 2000, 26:1675-1690. JPHPDH, 0096-1523, 10.1037/0096-1523.26.6.1675.
74. Smithson M. Judgment under chaos. Org. Behav. Hum. Decis. Process 1997, 69:58-66. OBDPFO, 0749-5978, 10.1006/obhd.1996.2672.
75. Solomon J.A. Noise reveals visual mechanisms of detection and discrimination. J. Vision 2002, 2:105-120. ZZZZZZ, 1534-7362, 10.1167/2.1.7.
76. Spekreijse H. Oosting H. Linearizing: A method for analysing and synthesizing nonlinear systems. Kybernetik 1970, 7:22-31. KYBEAP, 0023-5946, 10.1007/BF00270331.
77. Spillmann L. Foveal perceptive fields in the human visual system measured with simultaneous contrast in grids and bars. Pfluegers Arch. 1971, 326:281-299. PFLABK, 0031-6768, 10.1007/BF00586993.
78. Stewart I.N. Peregoy P.L. Catastrophe theory modeling in psychology. Psychol. Bull. 1983, 94:336-362. PSBUAI, 0033-2909, 10.1037/0033-2909.94.2.336.
79. Ta'edd L.K. Ta'eed O. Wright J.E. Determinants involved in the perception of the Necker cube: An application of catastrophe theory. Behav. Sci. 1988, 33:97-115. BEHSAS, 0005-7940, 10.1002/bs.3830330203.
80. Tanner W.P. Physiological implications of psychophysical data. Ann. N.Y. Acad. Sci. 1961, 89:752-765. ANYAA9, 0077-8923, 10.1111/j.1749-6632.1961.tb20176.x.
81. Thelen E. Smith L.B. H Dynamic Systems Approach to the Development of Cognition and Action 1995, and (MIT, Cambridge, MA).
82. Thomas J.P. Knoblauch K. Frequency and phase contributions to the detection of temporal luminance modulation. J. Opt. Soc. Am. A Opt. Image Sci. Vis 2005, 22:2257-2261. ZZZZZZ, 1084-7529, 10.1364/JOSAA.22.002257.
83. Tjan B.S. Nandy A.S. Classification images with uncertainty. J. Vision 2006, 6:387-413. ZZZZZZ, 1534-7362, 10.1167/6.4.8.
84. van Hateren J.H. Snippe H.P. Information theoretical evaluation of parametric models of gain control in blowfly photoreceptor cells. Vision Res. 2001, 41:1851-1865. VISRAM, 0042-6989, 10.1016/S0042-6989(01)00052-9.
85. von der Malsburg C. The what and why of binding: The modeler's perspective. Neuron 1999, 24:95-104. NERNET, 0896-6273, 10.1016/S0896-6273(00)80825-9.
86. Westwick D.T. Kearney R.E. Identification of Nonlinear Physiological Systems 2003, 10.1002/0471722960, and (Wiley IEEE, Piscataway, NJ).
87. Wiener N. Cybernetics or Control and Communication in the Animal and the Machine 1948, (Wiley, New York).
88. Wilson H.R. Non-Fourier cortical processes in texture, form, and motion perception. Cerebral Cortex 1999, 14:445-477. P. S. Ulinski, E. G. Jones, A. Peters, in edited by and (Plenum, New York), Vol. pp.
89. Yeshurun Y. Carrasco M. Maloney L.T. Bias and sensitivity in two-interval forced choice procedures: Tests of the difference model. Vision Res. 2008, 48:1837-1851. VISRAM, 0042-6989, 10.1016/j.visres.2008.05.008.