Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations

Grossberg, Stephen; Mingolla, Ennio

doi:10.3758/bf03198851

Cited by 757 publications

(187 citation statements)

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“…In contrast, they failed to observe responses to illusory contours in area V1. The apparent absence of illusory-contour responses in area V1 is puzzling both because there are recurrent pathways from V2 to V1 and because interaction between modules is a key feature of many models for early perceptual organization (4)(5)(6)(7). Moreover, other groups have shown that neurons in area V1 do detect subjective contours defined indirectly in other ways, for example by the fracture line where lines or out of phase sine wave gratings abut (8,9).…”

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confidence: 99%

Dynamics of subjective contour formation in the early visual cortex

Lee¹

2001

Proceedings of the National Academy of Sciences

131

113

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To elucidate the roles of visual areas V1 and V2 and their interaction in early perceptual processing, we studied the responses of V1 and V2 neurons to statically displayed Kanizsa figures. We found evidence that V1 neurons respond to illusory contours of the Kanizsa figures. The illusory contour signals in V1 are weaker than in V2, but are significant, particularly in the superficial layers. The population averaged response to illusory contours emerged 100 msec after stimulus onset in the superficial layers of V1, and around 120 -190 msec in the deep layers. The illusory contour response in V2 began earlier, occurring at 70 msec in the superficial layers and at 95 msec in the deep layers. The temporal sequence of the events suggests that the computation of illusory contours involves intercortical interaction, and that early perceptual organization is likely to be an interactive process.W hen viewing the Kanizsa display shown in Fig. 1a, we perceive the borders of a square even in regions of the image where there is no direct visual evidence for them. This is one example of the phenomenon of illusory or subjective contours (1). This perceptual phenomenon has been reported by von der Heydt and colleagues (2, 3) to possess a direct physiological correlate in macaque area V2, where some neurons were found to respond to an illusory contour moving across their receptive fields. In contrast, they failed to observe responses to illusory contours in area V1. The apparent absence of illusory-contour responses in area V1 is puzzling both because there are recurrent pathways from V2 to V1 and because interaction between modules is a key feature of many models for early perceptual organization (4-7). Moreover, other groups have shown that neurons in area V1 do detect subjective contours defined indirectly in other ways, for example by the fracture line where lines or out of phase sine wave gratings abut (8, 9). Because of the nature of their stimuli, these studies (8, 9) did not resolve the question of whether their results would apply to the illusory contours as studied by Von der Heydt and colleagues. In light of these considerations, we decided to reexamine the issue of neural responses to illusory contours in areas V1 and V2. By using a technique designed to call attention to the illusory square and employing a static display that allowed tracking the temporal evolution of responses, we have found that neurons in area V1 do respond to illusory contours, although at a latency greater than that in V2.We conducted the following neurophysiological experiment on two awake behaving rhesus monkeys. In each trial, while the monkey was fixating a red dot on the screen within a 0.5°fixation window, a sequence of four stimuli was presented. The presentation of each stimulus in the sequence lasted for 400 msec. On completion of the sequence, the monkey had to make a saccadic eye movement to another red dot that appeared at a random position on the screen to complete the trial. The set of test stimuli included a Kanizsa figure with ...

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confidence: 99%

Dynamics of subjective contour formation in the early visual cortex

Lee¹

2001

Proceedings of the National Academy of Sciences

131

113

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“…Spatial Impenetrability and Textural Grouping: Gated Dipole Field Figure 14 depicts the results of computer simulations that illustrate how these properties of the CC loop can generate a perceptual grouping or emergent segmentation of figural elements (Grossberg & Mingolla, 1985b). Figure 14a depicts an array of nine vertically oriented input clusters.…”

Section: Dynamic Geometry Of Curves: Metacontrastmentioning

confidence: 99%

“…Such model cells, which play the role of complex cells in area 17 of the visual cortex, pool inputs from receptive fields with opposite directions-of-contrast in order to generate boundary detectors that can detect the broadest possible range of luminance or chromatic contrasts, as described in greater detail in Sections 23 and 31. These two successive stages of oriented contrast-sensitive cells are called the OC filter (Grossberg & Mingolla, 1985b).…”

Section: The Oc Filter and The Short-range Competitive Stagesmentioning

confidence: 99%

Cortical dynamics of three-dimensional form, color, and brightness perception: I. Monocular theory

Grossberg

1987

Perception & Psychophysics

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A real-time visual processing theory is developed to explain how three-dimensional form, color, and brightness percepts are coherently synthesized. The theory describes how several fundamental uncertainty principles which limit the computation of visual information at individual processing stages are resolved through parallel and hierarchical interactions among several processing stages. The theory hereby provides a unified analysis and many predictions of data about stereopsis, binocular rivalry, hyperacuity, McCollough effect, textural grouping, border distinctness, surface perception, monocular and binocular brightness percepts, filling-in, metacontrast, transparency, figural aftereffects, lateral inhibition within spatial frequency channels, proximityluminance covariance, tissue contrast, motion segmentation, and illusory figures, as well as about reciprocal interactions among the hypercolumns, blobs, and stripes of cortical areas VI, V2, and V4. Monocular and binocular interactions between a Boundary Contour (BC) System and a Feature Contour (FC) System are developed. The BC System, defined by a hierarchy of oriented in-.teractions, synthesizes an emergent and coherent binocular boundary segmentation from combinations of unoriented and oriented scenic elements. These BC System interactions instantiate a new theory of stereopsis and of how mechanisms of stereopsis are related to mechanisms of boundary segmentation. Interactions between the BC System and the FC System explain why boundary completion and segmentation processes become binocular at an earlier processing stage than do color and brightness perception processes. The new stereopsis theory includes a new model of how chromatically broadband cortical complex cells can be adaptively tuned to multiplex information about position, orientation, spatial frequency, positional disparity, and orientational disparity. These binocular cells input to spatially short-range competitive interactions (within orientations and between positions, followed by between orientations and within positions) that initiate suppression of binocular double images as they complete boundaries at scenic line ends and comers. The competitive interactions interact via both feedforward and feedback pathways with spatially long-range-oriented cooperative gating interactions that generate a coherent, multiple-scale, three-dimensional boundary segmentation as they complete the suppression of double-image boundaries. The completed BC System boundary segmentation generates output signals, called filling-in generators (FIGs) and filling-in barriers (FIBs), along parallel pathways to two successive FC System stages: the monocular syncytium and the binocular syncytium. FIB signals at the monocular syncytium suppress monocular color and brightness signals that are binocularly inconsistent and select binocularly consistent, monocular FC signals as outputs to the binocular syncytium. Binocular matching of these FC signals further suppresses binocularly inconsistent color and brightness signals. B...

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“…[Computations indicated, as expected, that E(Oij) to the striped and checked regions were highly similar. We therefore incorporated only differences in the stan-right that has been discussed by a number of people (Caelli, 1985(Caelli, , 1988Grossberg, 1987;Grossberg & Mingolla, 1985), although it is not explicitly studied here.…”

Section: Combining Channel Outputsmentioning

confidence: 99%

“…Much of this work was presented at the May 1988 meeting of the Association of Researchers in Vision and Ophthalmology (Sutter, Graham, & Beck, 1988). Correspondence may be addressed to Jacob Beck, Department of Psychology, University of Oregon, Eugene, OR 91403. proposed that texture segregation is, at least sometimes, directly based on differences in the outputs of spatialfrequency channels (e.g., Beck, Sutter, & Ivry, 1987;Bergen, in press;Bergen & Adelson, 1988;Caelli, 1985;Daugman, 1987Daugman, , 1988Ginsburg, 1984;Graham, 1981;Grossberg & Mingolla, 1985;Turner, 1986). Spatial-frequency channels are quasi-independent, parallel channels composed of local receptive fields that are distributed throughout the visual field and are alike in their sensitivity to spatial frequency and orientation.…”

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confidence: 99%

Contrast and spatial variables in texture segregation: Testing a simple spatial-frequency channels model

Sutter

Beck

Graham

1989

Perception & Psychophysics

146

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Observers were shown patterns composed oftwo textures in which each texture contained two types of elements. The elements were arranged in a striped pattern in the top and bottom regions and in a checked pattern in the center region. Observers rated the degree to which the three regions were seen as distinct. When the elements were squares or lines, perceived segregation resulting from differences in element size could be canceled by differences in element contrast. Minimal perceived segregation occurred when the products of the area and the contrast (areal contrasts) of the elements were equal. This dependence of perceived segregation on the areal contrasts of the elements is consistent with a simple model based on the hypothesis that the perceived segregation of the regions is a function of their differential stimulation of spatial-frequency channels. Two aspects ofthe data were not consistent with quantitative predictions of the model. First, as the size difference between the large and small elements increased, the ratings at the point of minimum perceived segregation increased. Second, some effects of changing the fundamental frequency of the textures were not predicted by the model. These discrepancies may be explained by a more complex model in which a rectification or similar nonlinearity occurs between two stages of orientation-and spatial-frequency-selective linear filters.Models of texture segregation fall into three classes. In one class of models, texture segregation is based on the geometric features of a texture pattern. Beck (1972Beck ( , 1982 and Marr (1976) proposed that texture segregation is based on differences in first-order statistics of simple features of a texture pattern, such as the slopes and sizes of texture elements or of their component parts. Julesz (1981) has labeled such features textons and proposed that there are three kinds: elongated blobs (e.g., line segments), terminators (e.g., line terminations), and intersections (e.g., crossings of line segments). In a second class of models, the primitives for texture segregation are not geometric features but the outputs of receptive-fieldlike operators. In many of the models in this class, texture segregation is based on differences in image statistics following the convolution of a texture with local, linear filters that have weighting functions like the receptive fields of simple cells. A number of investigators have This research was supported by AFOSR Grant AFOSR-85-o359 to Jacob Beck and by NIMH Fellowship MH09449 to Norma Graham. Experiments I and 4 were performed in partial fulfillment of the requirements for the PhD degree at the University of Oregon by Anne Sutter. Much of this work was presented at the May 1988 meeting of the Association of Researchers in Vision and Ophthalmology (Sutter, Graham, & Beck, 1988). Correspondence may be addressed to Jacob Beck, Department of Psychology, University of Oregon, Eugene, OR 91403. proposed that texture segregation is, at least sometimes, directly based on differences in the out...

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Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations

Cited by 757 publications

References 67 publications

Dynamics of subjective contour formation in the early visual cortex

Dynamics of subjective contour formation in the early visual cortex

Cortical dynamics of three-dimensional form, color, and brightness perception: I. Monocular theory

Contrast and spatial variables in texture segregation: Testing a simple spatial-frequency channels model

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