The perception of globally coherent motion

Mingolla, Ennio; Todd, James T.; Norman, J. Farley

doi:10.1016/0042-6989(92)90003-2

Cited by 107 publications

(81 citation statements)

References 31 publications

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“…However, in the absence of contrast or depth cues, or special features like terminators, the visual system defaults to simple pooling over space to produce estimates of global velocity (Mingolla et al, 1992;Rubin and Hochstein, 1993;Lorenceau and Zago, 1999). Neurons in MT behave similarly, their response to spatially separate features presented within their receptive fields being the average of their responses to each of the features presented alone, whether the features differ in contrast (Britten and Heuer, 1999;Heuer and Britten, 2002) or direction of motion (Britten and Newsome, 1990;Ferrera and Lisberger, 1997;Recanzone et al, 1997).…”

Section: Discussionmentioning

confidence: 99%

Motion Integration by Neurons in Macaque MT Is Local, Not Global

Majaj

Carandini

Movshon³

2007

J. Neurosci.

128

112

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Direction-selective neurons in primary visual cortex have small receptive fields that encode the motions of local features. These motions often differ from the motion of the object to which they belong and must therefore be integrated elsewhere. A candidate site for this integration is visual cortical area MT (V5), in which cells with large receptive fields compute the motion of patterns. Previous studies of motion integration in MT have used stimuli that fill the receptive field, and thus do not test whether motion information is really integrated across this whole area. For each MT neuron, we identified two regions ("patches") within the receptive field that were approximately equally effective in driving responses. We then measured responses to plaids whose component gratings overlapped within a patch, and compared them with responses to the same component gratings presented in separate patches. Cells that were selective for the direction of motion of the whole pattern when the gratings overlapped lost this selectivity when the gratings were separated and became selective instead for the direction of motion of the individual components. If MT cells simply pooled all of the inputs that endow them with a receptive field, they would encode all of the motions in the receptive field as belonging to a single object. Our results indicate instead that critical elements of the computations underlying pattern-direction selectivity in MT are done locally, on a scale smaller than the whole receptive field.

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Section: Discussionmentioning

confidence: 99%

Motion Integration by Neurons in Macaque MT Is Local, Not Global

Majaj

Carandini

Movshon³

2007

J. Neurosci.

128

112

View full text Add to dashboard Cite

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“…There are several theories which speculate on how and where pattern motion is computed from V1 outputs. One idea is that pattern motion is computed in MT (Adelson and Movshon 1982;Albright 1984;Heeger 1987;Movshon et al 1985;Simoncelli and Heeger 1998) where the V1 outputs are combined using the intersection of constraints (IOC) rule (Adelson and Movshon 1982;Simoncelli and Heeger 1998) or vector averaging (Mingolla et al 1992;Rubin and Hochstein 1993). Another idea is that end-stopped cells in V1 could be involved in encoding pattern motion because they respond well to line terminators (or features) moving in their preferred direction and speed, independent of the orientation of the contour (Pack and Born 2001;Pack et al 2003;Born and Bradley 2005).…”

Section: Discussionmentioning

confidence: 99%

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

Petkov

Subramanian

2007

Biol Cybern

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We study the orientation and speed tuning properties of spatiotemporal three-dimensional (3D) Gabor and motion energy filters as models of time-dependent receptive fields of simple and complex cells in the primary visual cortex (V1). We augment the motion energy operator with surround suppression to model the inhibitory effect of stimuli outside the classical receptive field. We show that spatiotemporal integration and surround suppression lead to substantial noise reduction. We propose an effective and straightforward motion detection computation that uses the population code of a set of motion energy filters tuned to different velocities. We also show that surround inhibition leads to suppression of texture and thus improves the visibility of object contours and facilitates figure/ground segregation and the detection and recognition of objects.

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“…Due to the aperture problem, outputs from the directional transient cell network (equation 3.3) do not unambiguously signal the direction of object motion (Marr & Ullman, 1981;Wallach, 1935;Wuerger et al, 1996). Cross-directional normalizing competition enhances the least ambiguous regions and suppresses the most ambiguous regions, thus strengthening feature tracking signals which help reduce the effects of the aperture problem (Bayerl & Neumann, 2004;Berzhanskaya et al, 2007;Chey et al, 1997;Lucas & Kanade, 1981;Mingolla, Todd & Norman, 1992). .2), scale 1 is at the original input resolution, scale 2 is reduced by a factor of 2, and scale 3 is reduced by a factor of 4.…”

Section: Level 1: On-center Off-surround Network (γ)mentioning

confidence: 99%