Coding of Border Ownership in Monkey Visual Cortex

By Hong Zhou, H. Friedman, R. von der Heydt. 2000

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Areas V1 and V2 of the visual cortex have traditionally been conceived as stages of local feature representations. We investigated whether neural responses carry information about how local features belong to objects. Single-cell activity was recorded in areas V1, V2, and V4 of awake behaving monkeys. Displays were used in which the same local feature (contrast edge or line) could be presented as part of different figures. For example, the same light–dark edge could be the left side of a dark square or the right side of a light square. Each display was also presented with reversed contrast. We found significant modulation of responses as a function of the side of the figure in >50% of neurons of V2 and V4 and in 18% of neurons of the top layers of V1. Thus, besides the local contrast border information, neurons were found to encode the side to which the border belongs (“border ownership coding”). A majority of these neurons coded border ownership and the local polarity of luminance–chromaticity contrast. The others were insensitive to contrast polarity. Another 20% of the neurons of V2 and V4, and 48% of top layer V1, coded local contrast polarity, but not border ownership. The border ownership-related response differences emerged soon (<25 msec) after the response onset. In V2 and V4, the differences were found to be nearly independent of figure size up to the limit set by the size of our display (21°). Displays that differed only far outside the conventional receptive field could produce markedly different responses. When tested with more complex displays in which figure-ground cues were varied, some neurons produced invariant border ownership signals, others failed to signal border ownership for some of the displays, but neurons that reversed signals were rare. The influence of visual stimulation far from the receptive field center indicates mechanisms of global context integration. The short latencies and incomplete cue invariance suggest that the border-ownership effect is generated within the visual cortex rather than projected down from higher levels.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neuroscience

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Citations in the corpus

What can the brain teach us about building artificial intelligence? (2016, background): “Evidence indicate that contours and surfaces are represented in a factored manner in the visual cortex [3], potentially giving rise to the ability of humans to imagine and recognize objects with surface appearances that are not prototypical — like a blanket made of bananas, or a banana made of blank”
Figure–ground organization and the emergence of proto-objects in the visual cortex (2015, background): “We have termed this ‘border ownership coding’ (Zhou et al., 2000).”
Image Signature: Highlighting Sparse Salient Regions (2012, background): “The brain can perform this separation very quickly [3], and doing so on a machine remains a major challenge for engineers and scientists.”
A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs (2017, background): “The timing and topography of cortical activations give clues about contoursurface representations and inference algorithms (22, 23).”
Figure-ground mechanisms provide structure for selective attention (2007, background): “Single-cell recordings from monkey visual cortex have shown that assignment of border ownership occurs at stages as low in the hierarchy as areas V1 and V2 (refs”
A neural model of figure-ground organization. (2007, positive): “9 of Gattass et al. (1981) it can be seen that two neurons with receptive fields located 2.5 and 6.5° below the center of gaze (cells 5 and 11) are separated by 21 mm [because no scale bars are provided, we estimated the scale based on brain sections of the monkeys of Zhou et al. (2000) to be 3:1].”
Border ownership from intracortical interactions in visual area v2. (2005, background): “They observed that a cell tuned to a figure to the left prefers Figures 1B–1E to Figures 1F–1I (Zhou et al., 2000; F.T. Qiu et al., 2001, Soc. Neurosci., abstract; R. von der Heydt et al., 2003, J. Vis., abstract; von der Heydt et al., 2000).”
Mechanisms of perceptual organization provide auto-zoom and auto-localization for attention to objects (2010, background): “One of its crucial elements, border ownership, is represented in the response properties of single neurons in early cortical areas, most prominently in secondary visual cortex (area V2) (12).”
Correspondence of Deep Neural Networks and the Brain for Visual Textures (2018, background): “For instance, biological studies have found selectivity in V2 to conjunctions of orientations, and to ﬁgure ground [51], [52], [53], with some aspects addressed in computational models of V2 [54], [55], [56], [57], [58] [59].”
Feed-Forward Segmentation of Figure-Ground and Assignment of Border-Ownership (2010, background): “This has also been described in the visual cortex where edge detection is mainly observed for neurons that have an orientation preference [15].”
Surrounding Suppression and Facilitation in the Determination of Border Ownership (2006, methodology): “, a part of a contour) is projected onto the CRF of the neuron (Zhou et al., 2000).”