Abstract

A neural network model of visual motion perception and speed discrimination is developed to simulate data concerning the conditions under which components of moving stimuli cohere or not into a global direction of motion, as in barberpole and plaid patterns (both type 1 and type 2). The model also simulates how the perceived speed of lines moving in a prescribed direction depends on their orientation, length, duration, and contrast. Motion direction and speed both emerge as part of an interactive motion grouping or segmentation process. The model proposes a solution to the global aperture problem by showing how information from feature tracking points, namely, locations from which unambiguous motion directions can be computed, can propagate to ambiguous motion direction points and capture the motion signals there. The model does this without computing intersections of constraints or parallel Fourier and non-Fourier pathways. Instead, the model uses orientationally unselective cell responses to activate directionally tuned transient cells. These transient cells, in turn, activate spatially short-range filters and competitive mechanisms over multiple spatial scales to generate speed-tuned and directionally tuned cells. Spatially long-range filters and top–down feedback from grouping cells are then used to track motion of featural points and to select and propagate correct motion directions to ambiguous motion points. Top–down grouping can also prime the system to attend a particular motion direction. The model hereby links low-level automatic motion processing with attention-based motion processing. Homologs of model mechanisms have been used in models of other brain systems to simulate data about visual grouping, figure–ground separation, and speech perception. Earlier versions of the model have simulated data about short-range and long-range apparent motion, second-order motion, and the effects of parvocellular and magnocellular lateral geniculate nucleus lesions on motion perception.

© 1997 Optical Society of America

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1997 (3)

S. Grossberg, “Cortical dynamics of 3-D figure–ground perception of 2-D pictures,” Psychol. Rev. 104, 618–658 (1997).
[CrossRef] [PubMed]

K. M. O'Craven, B. R. Rosen, K. K. Kwong, A. Treisman, R. L. Savoy, “Voluntary attention modulates fMRI activity in human MT-MST,” Neuron 18, 591–598 (1997).
[CrossRef] [PubMed]

S. Grossberg, I. Boardman, M. Cohen, “Neural dynamics of variable-rate speech categorization,” J. Exp. Psychol. Hum. Percept. Perf. 23, 481–503 (1997).

1996 (5)

G. Francis, S. Grossberg, “Cortical dynamics of boundary segmentation and reset: persistence, afterimages, and residual traces,” Perception 26, 543–567 (1996).

L. Bowns, “Evidence for a feature tracking explanation of why Type II plaids movein the vector sum direction at short durations,” Vision Res. 36, 3685–3694 (1996).
[CrossRef] [PubMed]

S. Treue, J. H. R. Maunsell, “Attentional modulation of visual motion processing in cortical areasMT and MST,” Nature (London) 382, 539–541 (1996).
[CrossRef]

G. Francis, S. Grossberg, “Cortical dynamics of form and motion integration: persistence, apparentmotion and illusory contours,” Vision Res. 36, 149–173 (1996).
[CrossRef] [PubMed]

A. Baloch, S. Grossberg, “Neural dynamics of morphing motion,” Invest. Ophthalmol. Visual Sci. 37, 3419 (1996).

1995 (7)

S. Grossberg, , “The attentive brain,” Am. Scientist 83, 438–449 (1995).

J. Faubert, M. von Grünau, “The influence of two spatially distinct primers and attribute primingon motion induction,” Vision Res. 35, 3119–3130 (1995).
[CrossRef] [PubMed]

P. Tse, P. Cavanagh, “Line motion occurs after surface parsing,” Invest. Ophthalmol. Visual Sci. 36, 1919 (1995).

D. C. Bradley, N. Qian, R. A. Anderson, “Integration of motion and stereopsis in middle temporal cortical areaof macaques,” Nature (London) 373, 609–611 (1995).
[CrossRef]

A. Gove, S. Grossberg, E. Mingolla, “Brightness perception, illusory contours, and corticogeniculate feedback,” Visual Neurosci. 12, 1027–1052 (1995).
[PubMed]

M. Shiffrar, X. Li, J. Lorenceau, “Motion integration across differing image features,” Vision Res. 35, 2137–2146 (1995).
[CrossRef] [PubMed]

R. J. Douglas, C. Koch, M. Mahowald, K. A. C. Martin, H. H. Suarez, “Recurrent excitation in neocortical circuits,” Science 269, 981–985 (1995).
[CrossRef] [PubMed]

1994 (5)

G. Francis, S. Grossberg, E. Mingolla, “Cortical dynamics of feature binding and reset: control of visual persistence,” Vision Res. 34, 1089–1104 (1994).
[CrossRef] [PubMed]

M. von Grünau, J. Faubert, “Intraattribute and interattribute motion induction,” Perception 23, 913–928 (1994).

S. Grossberg, “3-D vision and figure–ground separation by visual cortex,” Percept. Psychophys. 55, 48–120 (1994).
[CrossRef] [PubMed]

S. Grossberg, E. Mingolla, W. D. Ross, “A neural theory of attentive visual search: interactions of boundary,surface, spatial, and object recognition,” Psychol. Rev. 101, 470–489 (1994).
[CrossRef] [PubMed]

L. B. Stelmach, C. M. Herdman, R. McNeil, “Attentional modulation of visual processes in motion perception,” J. Exp. Psychol. 20, 108–121 (1994).

1993 (11)

N. Rubin, S. Hochstein, “Isolating the effect of one-dimensional motion signals on the perceiveddirection of moving two-dimensional objects,” Vision Res. 33, 1385–1396 (1993).
[CrossRef] [PubMed]

J. Lorenceau, M. Shiffrar, N. Wells, E. Castet, “Different motion sensitive units are involved in recovering the directionof moving lines,” Vision Res. 33, 1207–1217 (1993).
[CrossRef] [PubMed]

S. N. J. Watamaniuk, N. M. Grzywacz, A. L. Yuille, “Dependence of speed and direction perception on cinematogram dot density,” Vision Res. 33, 849–859 (1993).
[CrossRef] [PubMed]

O. Hikosaka, S. Miyauchi, S. Shimojo, “Focal visual attention produces illusory temporal order and motionsensation,” Vision Res. 33, 1219–1240 (1993).
[CrossRef] [PubMed]

O. Hikosaka, S. Miyauchi, S. Shimojo, “Voluntary and stimulus-induced attention detected as motion sensation,” Perception 22, 517–526 (1993).
[PubMed]

K. Tanaka, Y. Sugita, M. Moriya, H. A. Saito, “Analysis of object motion in the ventral part of the medial superiortemporal area of the macaque visual cortex,” J. Neurosci. 69, 128–142 (1993).

J. C. Trueswell, M. M. Hayhoe, “Surface segmentation mechanisms and motion perception,” Vision Res. 33, 313–328 (1993).
[CrossRef] [PubMed]

C. A. M. Nogueira, E. Mingolla, S. Grossberg, “Computation of first order and second order motion by a model of magnocellulardynamics,” Invest. Ophthalmol. Visual Sci. 34, 1029 (1993).

S. Grossberg, E. Mingolla, “Neural dynamics of motion perception: direction fields, apertures,and resonant grouping,” Percept. Psychophys. 53, 243–278 (1993).
[CrossRef] [PubMed]

E. Castet, J. Lorenceau, M. Shiffrar, C. Bonnet, “Perceived speed of moving lines depends on orientation, length, speedand luminance,” Vision Res. 33, 1921–1936 (1993).
[CrossRef] [PubMed]

J. Kim, H. R. Wilson, “Dependence of plaid motion coherence on component grating directions,” Vision Res. 33, 2479–2490 (1993).
[CrossRef] [PubMed]

1992 (11)

J. Allik, “Competing motion paths in sequences of random dot patterns,” Vision Res. 32, 157–165 (1992).
[CrossRef] [PubMed]

R. P. Power, B. Moulden, “Spatial gating effects on judged motion of gratings in apertures,” Perception 21, 449–463 (1992).
[PubMed]

C. Yo, H. R. Wilson, “Perceived direction of moving two-dimensional patterns depends on duration,contrast and eccentricity,” Vision Res. 32, 135–147 (1992).
[CrossRef] [PubMed]

G. R. Stoner, T. D. Albright, “The influence of foreground/background assignment on transparency andmotion coherency in plaid patterns,” Invest. Ophthalmol. Visual Sci. 33, 1050 (1992).

H. R. Wilson, V. P. Ferrera, C. Yo, “A psychophysically motivated model for two-dimensional motion perception,” Visual Neurosci. 9, 79 (1992).

J. Faubert, M. von Grünau, “The extent of split attention and attribute priming in motion induction,” Perception 21, 105b (1992).

E. Mingolla, J. T. Todd, J. F. Norman, “The perception of globally coherent motion,” Vision Res. 32, 1015–1031 (1992).
[CrossRef] [PubMed]

J. Lorenceau, M. Shiffrar, “The influence of terminators on motion integration across space,” Vision Res. 32, 263–273 (1992).
[CrossRef] [PubMed]

P. Cavanagh, “Attention-based motion perception,” Science 257, 1563–1565 (1992).
[CrossRef] [PubMed]

S. Grossberg, M. E. Rudd, “Cortical dynamics of visual motion perception: short-range and long-rangeapparent motion,” Psychol. Rev. 99, 78–121 (1992).
[CrossRef] [PubMed]

L. S. Stone, P. Thompson, “Human speed perception is contrast dependent,” Vision Res. 32, 1535–1549 (1992).
[CrossRef] [PubMed]

1991 (2)

S. Grossberg, “Why do parallel cortical systems exist for the perception of staticform and moving form?” Percept. Psychophys. 49, 117–141 (1991).
[CrossRef] [PubMed]

V. P. Ferrera, H. R. Wilson, “Perceived speed of moving two-dimensional patterns,” Vision Res. 31, 877–893 (1991).
[CrossRef] [PubMed]

1990 (5)

L. S. Stone, A. B. Watson, J. B. Mulligan, “Effect of contrast on the perceived direction of a moving plaid,” Vision Res. 30, 1049–1067 (1990).
[CrossRef] [PubMed]

V. P. Ferrera, H. R. Wilson, “Perceived direction of moving two-dimensional patterns,” Vision Res. 30, 273–287 (1990).
[CrossRef] [PubMed]

P. H. Schiller, N. K. Logothetis, E. R. Charles, “Functions of the colour-opponent and broad-band channels of the visualsystem,” Science 343, 68–70 (1990).

G. R. Stoner, T. D. Albright, V. S. Ramachandran, “Transparency and coherence in human motion perception,” Nature (London) 344, 153–155 (1990).
[CrossRef]

N. K. Logothetis, P. H. Schiller, E. R. Charles, A. C. Hurlbert, “Perceptual deficits and the activity of the color-opponent and broad-bandpathways at isoluminance,” Science 247, 214–217 (1990).
[CrossRef] [PubMed]

1989 (1)

S. Grossberg, M. E. Rudd, “A neural architecture for visual motion perception: group and elementapparent motion,” Neural Networks 2, 421–450 (1989).
[CrossRef]

1988 (2)

K. Nakayama, G. H. Silverman, “The aperture problem. II: Spatial integration of velocity informationalong contours,” Vision Res. 28, 747–753 (1988).
[CrossRef]

B. de Bruyn, G. A. Orban, “Human velocity and direction discrimination measured with random dotpatterns,” Vision Res. 28, 1323–1335 (1988).
[CrossRef]

1987 (4)

S. Grossberg, “Cortical dynamics of three-dimensional form, color, and brightnessperception. II: Binocular theory,” Percept. Psychophys. 41, 117–158 (1987).
[CrossRef] [PubMed]

G. A. Carpenter, S. Grossberg, “A massively parallel architecture for a self-organizing neural patternrecognition machine,” Comput. Vision Graphics Image Process. 37, 54–115 (1987).
[CrossRef]

V. P. Ferrera, H. R. Wilson, “Direction specific masking and the analysis of motion in two dimensions,” Vision Res. 27, 1783–1796 (1987).
[CrossRef] [PubMed]

S. J. Anderson, D. C. Burr, “Receptive field size of human motion detection units,” Vision Res. 27, 621–635 (1987).
[CrossRef] [PubMed]

1986 (3)

D. C. Burr, J. Ross, M. C. Morrone, “Smooth and sampled motion,” Vision Res. 26, 643–652 (1986).
[CrossRef] [PubMed]

M. Cohen, S. Grossberg, “Neutral dynamics of speech and language coding: developmental programs,perceptual grouping, and competition for short term memory,” Human Neurobiol. 5, 1–22 (1986).

G. A. Orban, H. Kennedy, J. Bulier, “Velocity sensitivity and direction selectivity of neurons in areasV1 and V2 of the monkey: influence of eccentricity,” J. Neurophysiol. 56, 462–480 (1986).
[PubMed]

1985 (2)

J. Allman, F. Miezin, E. McGuinness, “Direction and velocity-specific responses from beyond the classical receptive field in the middle temporal visual area (MT),” Perception 14, 105–126 (1985).

K. Nakayama, G. H. Silverman, “Detection and discrimination of sinusoidal grating displacements,” J. Opt. Soc. Am. A 2, 267–273 (1985).
[CrossRef] [PubMed]

1984 (6)

K. Nakayama, G. H. Silverman, “Temporal and spatial characteristics of the upper displacement limitsfor motion in random dots,” Vision Res. 24, 293–299 (1984).
[CrossRef]

T. D. Albright, R. Desimone, C. G. Gross, “Columnar organization of directionally sensitive cells in visual areaMT of the macaque,” J. Neurophysiol. 51, 16–31 (1984).
[PubMed]

L. Ganz, “Visual cortical mechanisms responsible for direction selectivity,” Vision Res. 24, 3–11 (1984).
[CrossRef] [PubMed]

P. Heggelund, “Direction asymmetry by moving stimuli and static receptive field plotsfor simple cells in cat striate cortex,” Vision Res. 24, 13–16 (1984).
[CrossRef]

G. A. Orban, J. D. de Wolf, H. Maes, “Factors influencing velocity coding in the human visual system,” Vision Res. 24, 33–39 (1984).
[CrossRef] [PubMed]

D. W. Williams, R. Sekuler, “Coherent global motion percepts from stochastic local motions,” Vision Res. 24, 55–62 (1984).
[CrossRef] [PubMed]

1983 (5)

J. H. R. Maunsell, D. C. van Essen, “Functional properties of neurons in middle temporal visual area ofthe macaque monkey. I. Selectivity for stimulus duration, speed, and orientation,” J. Neurophysiol. 49, 1127–1147 (1983).
[PubMed]

J. H. R. Maunsell, D. C. van Essen, “Functional properties of neurons in middle temporal visual area ofthe macaque monkey. II. Binocular interactions and sensitivity to binoculardisparity,” J. Neurophysiol. 49, 1148–1167 (1983).
[PubMed]

J. T. Petersik, R. Pufahl, E. Krasnoff, “Failure to find an absolute retinal limit of a putative short-rangeprocess in apparent motion,” Vision Res. 23, 1663–1670 (1983).
[CrossRef]

S. Grossberg, , “The quantized geometry of visual space: the coherent computation ofdepth, form, and lightness,” Behav. Brain Sci. 6, 625–657 (1983).
[CrossRef]

W. T. Newsome, M. S. Gizzi, J. A. Movshon, “Spatial and temporal properties of neurons in macaque MT,” Invest. Ophthalmol. Visual Sci. 24, 106 (1983).

1982 (5)

P. H. Schiller, “Central connections on the retinal ON- and OFF-pathways,” Nature (London) 297, 580–583 (1982).
[CrossRef]

M. Ariel, N. W. Daw, “Pharmacological analysis of directionally sensitive rabbit retinalganglion cells,” J. Physiol. (London) 324, 161–185 (1982).

P. Thompson, “Perceived rate of movement depends on contrast,” Vision Res. 22, 377–380 (1982).
[CrossRef] [PubMed]

P. D. Tynan, R. Sekuler, “Motion processing in peripheral vision: reaction time and perceivedvelocity,” Vision Res. 22, 61–68 (1982).
[CrossRef]

E. H. Adelson, J. A. Movshon, “Phenomenal coherence of moving visual patterns,” Nature (London) 300, 523–525 (1982).
[CrossRef]

1980 (3)

K. Brown, R. Sekuler, “Models of stimulus uncertainty in motion perception,” Psychol. Rev. 87, 435–469 (1980).
[CrossRef]

O. J. Braddick, “Low-level and high-level processes in apparent motion,” Philos. Trans. R. Soc. London Ser. B 290, 137–151 (1980).
[CrossRef]

S. Grossberg, “How does a brain build a cognitive code?” Psychol. Rev. 87, 1–51 (1980).
[CrossRef] [PubMed]

1977 (2)

R. C. Emerson, G. L. Gerstein, “Simple striate neurons in the cat: II. Mechanisms underlying directionalasymmetry and directional selectivity,” J. Neurophysiol. 40, 136–155 (1977).
[PubMed]

R. Sekuler, K. Ball, “Mental set alters visibility of moving targets,” Science 198, 60–62 (1977).
[CrossRef] [PubMed]

1976 (3)

H. C. Diener, E. R. Wist, J. Dichgans, T. Brandt, “The spatial frequency effect on perceived velocity,” Vision Res. 16, 169–176 (1976).
[CrossRef] [PubMed]

S. Hochstein, R. Shapley, “Quantitative analysis of retinal ganglion cell classifications,” J. Physiol. (London) 262, 237–264 (1976).

S. Hochstein, R. Shapley, “Linear and nonlinear spatial subunits in Y cat retina ganglion cells,” J. Physiol. (London) 262, 265–284 (1976).

1975 (1)

A. W. Goodwin, G. H. Henry, P. O. Bishop, “Direction selectivity of simple striate cells: properties and mechanisms,” J. Neurophysiol. 38, 1500–1523 (1975).
[PubMed]

1974 (2)

S. M. Zeki, “Functional organization of a visual area in the posterior bank of thesuperior temporal sulcus of the rhesus monkey,” J. Physiol. (London) 236, 546–573 (1974).

O. J. Braddick, “A short-range process in apparent motion,” Vision Res. 14, 519–527 (1974).
[CrossRef] [PubMed]

1966 (1)

C. Enroth-Cugell, J. Robson, “The contrast sensitivity of retinal ganglion cells of the cat,” J. Physiol. (London) 187, 517–552 (1966).

1965 (1)

H. B. Barlow, W. R. Levick, “The mechanism of directionally selective units in rabbit's retina,” J. Physiol. (London) 178, 477–504 (1965).

1962 (1)

D. H. Hubel, T. N. Wiesel, “Receptive fields, binocular interaction and functional architecturein the cat's visual cortex,” J. Physiol. (London) 160, 106–154 (1962).

1959 (1)

D. H. Hubel, T. N. Wiesel, “Receptive fields of single cells in the cat's striate cortex,” J. Physiol. (London) 148, 574–591 (1959).

1953 (1)

S. W. Kuffler, “Discharge patterns and functional organization of the mammalian retina,” J. Neurophysiol. 16, 37–68 (1953).
[PubMed]

1948 (1)

J. A. Gengerelli, “Apparent movement in relation to homonymous and heteronymous stimulationof the cerebral hemispheres,” J. Exp. Psychol. 38, 592–599 (1948).
[CrossRef] [PubMed]

Adelson, E. H.

E. H. Adelson, J. A. Movshon, “Phenomenal coherence of moving visual patterns,” Nature (London) 300, 523–525 (1982).
[CrossRef]

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, Vol. 11 of Experimental Brain Research Supplementum, C. Chagas, R. Gattass, C. Gross, eds. (Springer-Verlag, Berlin, 1985), pp. 117–151.

Albright, T. D.

G. R. Stoner, T. D. Albright, “The influence of foreground/background assignment on transparency andmotion coherency in plaid patterns,” Invest. Ophthalmol. Visual Sci. 33, 1050 (1992).

G. R. Stoner, T. D. Albright, V. S. Ramachandran, “Transparency and coherence in human motion perception,” Nature (London) 344, 153–155 (1990).
[CrossRef]

T. D. Albright, R. Desimone, C. G. Gross, “Columnar organization of directionally sensitive cells in visual areaMT of the macaque,” J. Neurophysiol. 51, 16–31 (1984).
[PubMed]

Allik, J.

J. Allik, “Competing motion paths in sequences of random dot patterns,” Vision Res. 32, 157–165 (1992).
[CrossRef] [PubMed]

Allman, J.

J. Allman, F. Miezin, E. McGuinness, “Direction and velocity-specific responses from beyond the classical receptive field in the middle temporal visual area (MT),” Perception 14, 105–126 (1985).

Anderson, R. A.

D. C. Bradley, N. Qian, R. A. Anderson, “Integration of motion and stereopsis in middle temporal cortical areaof macaques,” Nature (London) 373, 609–611 (1995).
[CrossRef]

Anderson, S. J.

S. J. Anderson, D. C. Burr, “Receptive field size of human motion detection units,” Vision Res. 27, 621–635 (1987).
[CrossRef] [PubMed]

Ariel, M.

M. Ariel, N. W. Daw, “Pharmacological analysis of directionally sensitive rabbit retinalganglion cells,” J. Physiol. (London) 324, 161–185 (1982).

Ball, K.

R. Sekuler, K. Ball, “Mental set alters visibility of moving targets,” Science 198, 60–62 (1977).
[CrossRef] [PubMed]

Baloch, A.

A. Baloch, S. Grossberg, “Neural dynamics of morphing motion,” Invest. Ophthalmol. Visual Sci. 37, 3419 (1996).

A. Baloch, S. Grossberg, “A neural model of high-level motion processing: linemotion and formation dynamics,” (Boston U.,Boston, Mass., 1996); Vision Res. (to be published).

A. Baloch, S. Grossberg, E. Mingolla, C. A. M. Nogueira, “A neural model of first-order and second-order motion perception and magnocellular dynamics,” , 1996 (Boston U., Boston, Mass.).

Barlow, H. B.

H. B. Barlow, W. R. Levick, “The mechanism of directionally selective units in rabbit's retina,” J. Physiol. (London) 178, 477–504 (1965).

Bishop, P. O.

A. W. Goodwin, G. H. Henry, P. O. Bishop, “Direction selectivity of simple striate cells: properties and mechanisms,” J. Neurophysiol. 38, 1500–1523 (1975).
[PubMed]

Boardman, I.

S. Grossberg, I. Boardman, M. Cohen, “Neural dynamics of variable-rate speech categorization,” J. Exp. Psychol. Hum. Percept. Perf. 23, 481–503 (1997).

Bonnet, C.

E. Castet, J. Lorenceau, M. Shiffrar, C. Bonnet, “Perceived speed of moving lines depends on orientation, length, speedand luminance,” Vision Res. 33, 1921–1936 (1993).
[CrossRef] [PubMed]

Bowns, L.

L. Bowns, “Evidence for a feature tracking explanation of why Type II plaids movein the vector sum direction at short durations,” Vision Res. 36, 3685–3694 (1996).
[CrossRef] [PubMed]

Braddick, O. J.

O. J. Braddick, “Low-level and high-level processes in apparent motion,” Philos. Trans. R. Soc. London Ser. B 290, 137–151 (1980).
[CrossRef]

O. J. Braddick, “A short-range process in apparent motion,” Vision Res. 14, 519–527 (1974).
[CrossRef] [PubMed]

Bradley, D. C.

D. C. Bradley, N. Qian, R. A. Anderson, “Integration of motion and stereopsis in middle temporal cortical areaof macaques,” Nature (London) 373, 609–611 (1995).
[CrossRef]

Brandt, T.

H. C. Diener, E. R. Wist, J. Dichgans, T. Brandt, “The spatial frequency effect on perceived velocity,” Vision Res. 16, 169–176 (1976).
[CrossRef] [PubMed]

Brown, K.

K. Brown, R. Sekuler, “Models of stimulus uncertainty in motion perception,” Psychol. Rev. 87, 435–469 (1980).
[CrossRef]

Bulier, J.

G. A. Orban, H. Kennedy, J. Bulier, “Velocity sensitivity and direction selectivity of neurons in areasV1 and V2 of the monkey: influence of eccentricity,” J. Neurophysiol. 56, 462–480 (1986).
[PubMed]

Burr, D. C.

S. J. Anderson, D. C. Burr, “Receptive field size of human motion detection units,” Vision Res. 27, 621–635 (1987).
[CrossRef] [PubMed]

D. C. Burr, J. Ross, M. C. Morrone, “Smooth and sampled motion,” Vision Res. 26, 643–652 (1986).
[CrossRef] [PubMed]

Carpenter, G. A.

G. A. Carpenter, S. Grossberg, “A massively parallel architecture for a self-organizing neural patternrecognition machine,” Comput. Vision Graphics Image Process. 37, 54–115 (1987).
[CrossRef]

Castet, E.

E. Castet, J. Lorenceau, M. Shiffrar, C. Bonnet, “Perceived speed of moving lines depends on orientation, length, speedand luminance,” Vision Res. 33, 1921–1936 (1993).
[CrossRef] [PubMed]

J. Lorenceau, M. Shiffrar, N. Wells, E. Castet, “Different motion sensitive units are involved in recovering the directionof moving lines,” Vision Res. 33, 1207–1217 (1993).
[CrossRef] [PubMed]

Cavanagh, P.

P. Tse, P. Cavanagh, “Line motion occurs after surface parsing,” Invest. Ophthalmol. Visual Sci. 36, 1919 (1995).

P. Cavanagh, “Attention-based motion perception,” Science 257, 1563–1565 (1992).
[CrossRef] [PubMed]

P. Tse, P. Cavanagh, K. Nakayama, “The role of parsing in high level motion processing,” in High Level Motion Processing, T. Watanabe, ed. (MIT Press, Cambridge, Mass., to be published).

Charles, E. R.

N. K. Logothetis, P. H. Schiller, E. R. Charles, A. C. Hurlbert, “Perceptual deficits and the activity of the color-opponent and broad-bandpathways at isoluminance,” Science 247, 214–217 (1990).
[CrossRef] [PubMed]

P. H. Schiller, N. K. Logothetis, E. R. Charles, “Functions of the colour-opponent and broad-band channels of the visualsystem,” Science 343, 68–70 (1990).

Chey, J.

J. Chey, S. Grossberg, E. Mingolla, “Neural dynamics of motion processing and speed discrimination,” , 1994 (Boston U., Boston, Mass.).

Cohen, M.

S. Grossberg, I. Boardman, M. Cohen, “Neural dynamics of variable-rate speech categorization,” J. Exp. Psychol. Hum. Percept. Perf. 23, 481–503 (1997).

M. Cohen, S. Grossberg, “Neutral dynamics of speech and language coding: developmental programs,perceptual grouping, and competition for short term memory,” Human Neurobiol. 5, 1–22 (1986).

G. Govindarajan, S. Grossberg, L. Wyse, M. Cohen, “A neural network model of auditory scene analysis and source segregation,” , 1994) (Boston U., Boston, Mass.).

Daw, N. W.

M. Ariel, N. W. Daw, “Pharmacological analysis of directionally sensitive rabbit retinalganglion cells,” J. Physiol. (London) 324, 161–185 (1982).

de Bruyn, B.

B. de Bruyn, G. A. Orban, “Human velocity and direction discrimination measured with random dotpatterns,” Vision Res. 28, 1323–1335 (1988).
[CrossRef]

de Wolf, J. D.

G. A. Orban, J. D. de Wolf, H. Maes, “Factors influencing velocity coding in the human visual system,” Vision Res. 24, 33–39 (1984).
[CrossRef] [PubMed]

Desimone, R.

T. D. Albright, R. Desimone, C. G. Gross, “Columnar organization of directionally sensitive cells in visual areaMT of the macaque,” J. Neurophysiol. 51, 16–31 (1984).
[PubMed]

Dichgans, J.

H. C. Diener, E. R. Wist, J. Dichgans, T. Brandt, “The spatial frequency effect on perceived velocity,” Vision Res. 16, 169–176 (1976).
[CrossRef] [PubMed]

Diener, H. C.

H. C. Diener, E. R. Wist, J. Dichgans, T. Brandt, “The spatial frequency effect on perceived velocity,” Vision Res. 16, 169–176 (1976).
[CrossRef] [PubMed]

Douglas, R. J.

R. J. Douglas, C. Koch, M. Mahowald, K. A. C. Martin, H. H. Suarez, “Recurrent excitation in neocortical circuits,” Science 269, 981–985 (1995).
[CrossRef] [PubMed]

Emerson, R. C.

R. C. Emerson, G. L. Gerstein, “Simple striate neurons in the cat: II. Mechanisms underlying directionalasymmetry and directional selectivity,” J. Neurophysiol. 40, 136–155 (1977).
[PubMed]

Enroth-Cugell, C.

C. Enroth-Cugell, J. Robson, “The contrast sensitivity of retinal ganglion cells of the cat,” J. Physiol. (London) 187, 517–552 (1966).

Faubert, J.

J. Faubert, M. von Grünau, “The influence of two spatially distinct primers and attribute primingon motion induction,” Vision Res. 35, 3119–3130 (1995).
[CrossRef] [PubMed]

M. von Grünau, J. Faubert, “Intraattribute and interattribute motion induction,” Perception 23, 913–928 (1994).

J. Faubert, M. von Grünau, “The extent of split attention and attribute priming in motion induction,” Perception 21, 105b (1992).

Ferrera, V. P.

H. R. Wilson, V. P. Ferrera, C. Yo, “A psychophysically motivated model for two-dimensional motion perception,” Visual Neurosci. 9, 79 (1992).

V. P. Ferrera, H. R. Wilson, “Perceived speed of moving two-dimensional patterns,” Vision Res. 31, 877–893 (1991).
[CrossRef] [PubMed]

V. P. Ferrera, H. R. Wilson, “Perceived direction of moving two-dimensional patterns,” Vision Res. 30, 273–287 (1990).
[CrossRef] [PubMed]

V. P. Ferrera, H. R. Wilson, “Direction specific masking and the analysis of motion in two dimensions,” Vision Res. 27, 1783–1796 (1987).
[CrossRef] [PubMed]

Francis, G.

G. Francis, S. Grossberg, “Cortical dynamics of boundary segmentation and reset: persistence, afterimages, and residual traces,” Perception 26, 543–567 (1996).

G. Francis, S. Grossberg, “Cortical dynamics of form and motion integration: persistence, apparentmotion and illusory contours,” Vision Res. 36, 149–173 (1996).
[CrossRef] [PubMed]

G. Francis, S. Grossberg, E. Mingolla, “Cortical dynamics of feature binding and reset: control of visual persistence,” Vision Res. 34, 1089–1104 (1994).
[CrossRef] [PubMed]

Ganz, L.

L. Ganz, “Visual cortical mechanisms responsible for direction selectivity,” Vision Res. 24, 3–11 (1984).
[CrossRef] [PubMed]

Gengerelli, J. A.

J. A. Gengerelli, “Apparent movement in relation to homonymous and heteronymous stimulationof the cerebral hemispheres,” J. Exp. Psychol. 38, 592–599 (1948).
[CrossRef] [PubMed]

Gerstein, G. L.

R. C. Emerson, G. L. Gerstein, “Simple striate neurons in the cat: II. Mechanisms underlying directionalasymmetry and directional selectivity,” J. Neurophysiol. 40, 136–155 (1977).
[PubMed]

Gizzi, M. S.

W. T. Newsome, M. S. Gizzi, J. A. Movshon, “Spatial and temporal properties of neurons in macaque MT,” Invest. Ophthalmol. Visual Sci. 24, 106 (1983).

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, Vol. 11 of Experimental Brain Research Supplementum, C. Chagas, R. Gattass, C. Gross, eds. (Springer-Verlag, Berlin, 1985), pp. 117–151.

Goodwin, A. W.

A. W. Goodwin, G. H. Henry, P. O. Bishop, “Direction selectivity of simple striate cells: properties and mechanisms,” J. Neurophysiol. 38, 1500–1523 (1975).
[PubMed]

Gove, A.

A. Gove, S. Grossberg, E. Mingolla, “Brightness perception, illusory contours, and corticogeniculate feedback,” Visual Neurosci. 12, 1027–1052 (1995).
[PubMed]

Govindarajan, G.

G. Govindarajan, S. Grossberg, L. Wyse, M. Cohen, “A neural network model of auditory scene analysis and source segregation,” , 1994) (Boston U., Boston, Mass.).

Groner, M.

R. Groner, D. Hofer, M. Groner, “The role of anticipation in the encoding of motion signals-sensitization or bias,” in Human Memory and Cognitive Capabilities, F. Klix, H. Hagendorf, eds. (Elsevier, Amsterdam, 1986).

Groner, R.

R. Groner, D. Hofer, M. Groner, “The role of anticipation in the encoding of motion signals-sensitization or bias,” in Human Memory and Cognitive Capabilities, F. Klix, H. Hagendorf, eds. (Elsevier, Amsterdam, 1986).

Gross, C. G.

T. D. Albright, R. Desimone, C. G. Gross, “Columnar organization of directionally sensitive cells in visual areaMT of the macaque,” J. Neurophysiol. 51, 16–31 (1984).
[PubMed]

Grossberg, S.

S. Grossberg, “Cortical dynamics of 3-D figure–ground perception of 2-D pictures,” Psychol. Rev. 104, 618–658 (1997).
[CrossRef] [PubMed]

S. Grossberg, I. Boardman, M. Cohen, “Neural dynamics of variable-rate speech categorization,” J. Exp. Psychol. Hum. Percept. Perf. 23, 481–503 (1997).

G. Francis, S. Grossberg, “Cortical dynamics of boundary segmentation and reset: persistence, afterimages, and residual traces,” Perception 26, 543–567 (1996).

A. Baloch, S. Grossberg, “Neural dynamics of morphing motion,” Invest. Ophthalmol. Visual Sci. 37, 3419 (1996).

G. Francis, S. Grossberg, “Cortical dynamics of form and motion integration: persistence, apparentmotion and illusory contours,” Vision Res. 36, 149–173 (1996).
[CrossRef] [PubMed]

S. Grossberg, , “The attentive brain,” Am. Scientist 83, 438–449 (1995).

A. Gove, S. Grossberg, E. Mingolla, “Brightness perception, illusory contours, and corticogeniculate feedback,” Visual Neurosci. 12, 1027–1052 (1995).
[PubMed]

G. Francis, S. Grossberg, E. Mingolla, “Cortical dynamics of feature binding and reset: control of visual persistence,” Vision Res. 34, 1089–1104 (1994).
[CrossRef] [PubMed]

S. Grossberg, “3-D vision and figure–ground separation by visual cortex,” Percept. Psychophys. 55, 48–120 (1994).
[CrossRef] [PubMed]

S. Grossberg, E. Mingolla, W. D. Ross, “A neural theory of attentive visual search: interactions of boundary,surface, spatial, and object recognition,” Psychol. Rev. 101, 470–489 (1994).
[CrossRef] [PubMed]

C. A. M. Nogueira, E. Mingolla, S. Grossberg, “Computation of first order and second order motion by a model of magnocellulardynamics,” Invest. Ophthalmol. Visual Sci. 34, 1029 (1993).

S. Grossberg, E. Mingolla, “Neural dynamics of motion perception: direction fields, apertures,and resonant grouping,” Percept. Psychophys. 53, 243–278 (1993).
[CrossRef] [PubMed]

S. Grossberg, M. E. Rudd, “Cortical dynamics of visual motion perception: short-range and long-rangeapparent motion,” Psychol. Rev. 99, 78–121 (1992).
[CrossRef] [PubMed]

S. Grossberg, “Why do parallel cortical systems exist for the perception of staticform and moving form?” Percept. Psychophys. 49, 117–141 (1991).
[CrossRef] [PubMed]

S. Grossberg, M. E. Rudd, “A neural architecture for visual motion perception: group and elementapparent motion,” Neural Networks 2, 421–450 (1989).
[CrossRef]

G. A. Carpenter, S. Grossberg, “A massively parallel architecture for a self-organizing neural patternrecognition machine,” Comput. Vision Graphics Image Process. 37, 54–115 (1987).
[CrossRef]

S. Grossberg, “Cortical dynamics of three-dimensional form, color, and brightnessperception. II: Binocular theory,” Percept. Psychophys. 41, 117–158 (1987).
[CrossRef] [PubMed]

M. Cohen, S. Grossberg, “Neutral dynamics of speech and language coding: developmental programs,perceptual grouping, and competition for short term memory,” Human Neurobiol. 5, 1–22 (1986).

S. Grossberg, , “The quantized geometry of visual space: the coherent computation ofdepth, form, and lightness,” Behav. Brain Sci. 6, 625–657 (1983).
[CrossRef]

S. Grossberg, “How does a brain build a cognitive code?” Psychol. Rev. 87, 1–51 (1980).
[CrossRef] [PubMed]

S. Grossberg, “How is a moving target continuously tracked behind occluding cover?” in High Level Motion Processing, T. Watanabe, ed. (MIT Press, Cambridge, Mass., 1997).

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G. Govindarajan, S. Grossberg, L. Wyse, M. Cohen, “A neural network model of auditory scene analysis and source segregation,” , 1994) (Boston U., Boston, Mass.).

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Figures (19)

Fig. 1
Fig. 1

Feature tracking and motion capture: Often only a small subset of image features (e.g., line ends) generate unambiguous motion direction signals, as a result of aperture ambiguity and image or detector noise. We model how these unambiguous locations generate feature tracking signals that are used to capture ambiguous signals: (a) moving line, (b) barberpole illusion.

Fig. 2
Fig. 2

Effects of line length and orientation on perceived speed of horizontally moving lines. Relative perceived speed for three different line orientations and lengths are shown as percentages of the perceived speed of a vertical line of the same length. Part (a) shows data from Castet et al. (Ref. 1, p. 1925). Each data line corresponds to a different line length (0.21, 0.88, and 1.76 deg). The horizontal axis shows the ratio of the speed normal to the line's orientation relative to the actual translation speed. The three data points from left to right for each line length correspond to line angles of 60, 45, and 30 deg from vertical, respectively. The horizontal dotted line indicates a veridical speed perception; results below this line indicate a bias toward the perception of slower speeds. Part (b) shows simulation results, also for three lengths and orientations. In both cases perceived relative speed decreases with line length and angle from vertical. Simulated lines use slightly different orientations from those in the experiments so that the simulated input conforms to the Cartesian grid.

Fig. 3
Fig. 3

(a) In type 2 plaids, the IOC solution lies outside the arc formed by the directions normal to the components. In (b) the IOC solution predicts motion upward, whereas the vector sum of the component directions lies between the directions of the two components.

Fig. 4
Fig. 4

Model processing stages. See the text for details.

Fig. 5
Fig. 5

Maximal response of one-dimensional model cells to a range of simulated speeds. For levels where there are multiple spatial scales at each position, activities from different scales are shown as different curves superimposed on the same plot. The smaller scales tend to respond less vigorously to fast speeds. See the text for details.

Fig. 6
Fig. 6

Simulated responses to moving tilted line. Line length in each direction codes the activity level of the maximally active directionally tuned scale at that location. Ambiguous filter activation occurs in the line interior, and unambiguous responses occur at the line ends after thresholding in (c).

Fig. 7
Fig. 7

Simulations of long-range filtering: Part (a) shows maximal activities from each scale after long-range filtering. Filtering enhances activity at feature points relative to ambiguous motion signals. The ambiguous motion signals are relatively uniform along the length of the line. Part (b) shows the same activities interpreted as motion vectors.

Fig. 8
Fig. 8

Long-range directional grouping and feedback in which each grouping cell nonspecifically inhibits all long-range filters while exciting cells with the same directional preference.

Fig. 9
Fig. 9

Maximal activities across all scales of the long-range filters during the rightward motion of a 45-deg line at three successive times. Ambiguous motion signals are eliminated by feedback inhibition from the long-range directional grouping cells.

Fig. 10
Fig. 10

Motion direction and speed of a moving line derived from long-range filter activity over time (the same filter activities are shown in Fig. 9). The top plot shows how the perceived direction of a moving line gradually converges to its actual direction of motion (0 deg from horizontal) after starting at a direction almost perpendicular to the line's orientation (45 deg). The bottom plot shows how the perceived speed of the line gradually asymptotes over time.  

Fig. 11
Fig. 11

Time slices from the movement of a line behind a rectangular aperture illustrating the two phases of motion in the barberpole illusion. Each graphic shows long-range filter cell activity interpreted as motion vectors. In the first time slice, the line moves through the corner region, and signals in the line interior indicate motion perpendicular to the line's orientation. Feature signals dominate the output near the aperture edges but do not dominate the ambiguous motion signals along the rest of the line. In the later time slice, motion is captured by feature motion signals in the direction coincident with the long axis of the aperture.

Fig. 12
Fig. 12

Perceived direction of lines moving behind a rectangular aperture (barberpole illusion) over time. Results are shown from two independent simulations utilizing two different line orientations. When the orientation of the line is tilted away from 45 deg, the perceived direction of the line converges more rapidly to the direction coincident with the long axis of the aperture.  

Fig. 13
Fig. 13

(a) Input luminance, (b) On transient cell, and (c) Off transient cell responses for a type 1 symmetric plaid whose components are oriented at 45 deg from vertical during rightward movement.

Fig. 14
Fig. 14

Long-range filter responses combining On and Off channels during simulated motion of a type 1 symmetric plaid. Components are aligned at 45 deg from vertical. Filter responses have been magnified to show ambiguous signals clearly. The large feature signals do not therefore appear at their true magnitude. Such feature signals are present at the four corners, where the components intersect.

Fig. 15
Fig. 15

(a) Long-range filter outputs interpreted as motion vectors during the coherent plaid motion with components oriented at 45 deg from vertical. Motion signals are almost entirely uniform across the pattern, indicating rigid motion. (b) Long-range filter outputs interpreted as motion vectors for a plaid pattern during incoherent motion. The two components move independently. The feature points still move horizontally, a common perceptual phenomenon when viewing incoherently moving plaid patterns.

Fig. 16
Fig. 16

Adaptation levels at which simulated type 1 symmetric plaids are perceived to move incoherently for a range of component angles from horizontal for a horizontally moving plaid. Each adaptation level is the ratio of the adapted to the nonadapted long-range filter outputs. Only the rightward selective filters are adapted. When the component angles are near horizontal, greater adaptation is required for incoherent motion to be produced. This result is consistent with the smaller probability of seeing coherent motion with these components.

Fig. 17
Fig. 17

The perceived direction of type 2 patterns is duration dependent. At small exposure durations, patterns are perceived to move in the vector sum direction. For longer durations the IOC direction dominates. Data in (a) are replotted from Yo and Wilson,9 obtained by using components whose normals are at 48.2 and 70.5 deg from the direction of motion (vector sum 55.5 deg). Simulated results are shown in (b), obtained by using components oriented at 45 and 67.5 deg (vector sum 56.25 deg). The simulations use slightly different orientations to suit the Cartesian grid underlying the simulated input. In both cases component speeds are adjusted so that the IOC prescribed direction of motion of the plaid is at 0 deg.

Fig. 18
Fig. 18

The perceived direction of type 1 symmetric plaid patterns is dependent on component contrasts. (a) Data from Stone et al.6 show bias in perceived direction as a function of the contrast ratio between the two components for four different base contrasts. (b) Simulation results show the same qualitative biases for two different base contrasts. In both cases components were oriented at 67.5 deg from vertical.

Fig. 19
Fig. 19

Model mechanisms. Level 1 consists of change-sensitive units that are transiently activated for fixed time intervals by a moving stimulus. Transient cells sum and time-average activities from fixed, nonoverlapping sets of the change-sensitive units. Directional interneurons veto responses of directional transient cells to establish early directional selectivity. Multiple level 2 short-range filters at each spatial position draw input from a set of directional transient cells, the size of which is determined by the spatial scale of the filter. The thresholded outputs of the short-range filters form input to level 3 intrascale competition across space. Interscale competition then takes place between all scales at each spatial position. Competition between directions within each scale normalizes activity across directions at each location. Level 4 long-range filtering tracks the output of the interdirectional competition. Long-range filter outputs are selected through feedback from level 5 long-range directional grouping cells.

Tables (1)

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Table 1 Experimental Durations and Simulation Durations for Three Sets of Experiments

Equations (21)

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dxdt=α[-x+(β-γx)E-(δ+x)I].
aijOn=0ift-tOn1ηif0<t-tOn<1,
aijOff=0ift-tOff1ηif0<t-tOff<1,
dbijdt=-bij+(1-bij)(x, y)Bijaxy,
dcijddt=-cij+bij-10[cIJD]+.
deijddt=10(-eijd+bijd-10[cIJD]+).
dfijsddt=10-fijsd+(I, J)FijsdeIJsd.
gijds=(I, J)Gijd{exp[-(i-I)2-(j-J)2]}[fIJds]3s/2.
dhijdsdt=10-hijds+(I, J)EijdgIJdsEijd-(I, J)IijdgIJdsIijd.
dkijdsdt=-kijds+(1-kijds)([hijdt]+)3-(1+kijds) ts([hijdt]+)3{ts}.
dlijdsdt=10-lijds+10[kijds]+-110 lijdsDdt|D-d|[kijDt]+.
dmijdsdt=-mijds+(x, y)Mijd[lxyds]+Mijd-3(1+mijds)Dd[oD]+.
dnijddt=15 -nijd+(1-nijd)Nijd-10Dd[nijD]+,
Nijd=(I, J)OijDsX(|d-D|)Ψ(|D|)([mIJDs]+)2Oij.
yijd=sSmijds;
yij=dyijd.
sijd=sSmijdssyijd.
vijd=(sijd cos d, sijd sin d).
vij=dvijd.
wij=(0,0)ifyij<1vijifyij1.
v=(i, j)yijwij(i, j)yij,

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