Consistency of Border-Ownership Cells across Artificial Stimuli, Natural Stimuli, and Stimuli with Ambiguous Contours

Abstract

Segmentation and recognition of objects in a visual scene are two problems that are hard to solve separately from each other. When segmenting an ambiguous scene, it is helpful to already know the present objects and their shapes. However, for recognizing an object in clutter, one would like to consider its isolated segment alone to avoid confounds from features of other objects. Border-ownership cells (Zhou et al., 2000) appear to play an important role in segmentation, as they signal the side-of-figure of artificial stimuli. The present work explores the role of border-ownership cells in dorsal macaque visual areas V2 and V3 in the segmentation of natural object stimuli and locally ambiguous stimuli. We report two major results. First, compared with previous estimates, we found a smaller percentage of cells that were consistent across artificial stimuli used previously. Second, we found that the average response of those neurons that did respond consistently to the side-of-figure of artificial stimuli also consistently signaled, as a population, the side-of-figure for borders of single faces, occluding faces and, with higher latencies, even stimuli with illusory contours, such as Mooney faces and natural faces completely missing local edge information. In contrast, the local edge or the outlines of the face alone could not always evoke a significant border-ownership signal. Our results underscore that border ownership is coded by a population of cells, and indicate that these cells integrate a variety of cues, including low-level features and global object context, to compute the segmentation of the scene.

Foreground-background segmentation revealed during natural image viewing

“…Thus, indirect evidence of figure-ground modulation of natural images could be retrieved in the activity of multiple areas of the visual processing stream. This is consistent with a recent study, which reported that border-ownership of natural images cannot be resolved by single cells, but requires a population of cells in monkey V2 and V3 (Hesse JK and DY Tsao 2016).…”

“…In addition, from an experimental viewpoint, the role of visual segmentation has been demonstrated only by means of non-ecological stimuli (e.g., binary figures, random dots, oriented line segments and textures). Although two recent studies investigated border-ownership in monkeys with both artificial and natural stimuli (Hesse JK and DY Tsao 2016;Williford JR and R von der Heydt 2016), a proof of the occurrence of foreground-background segmentation in the human brain during visual processing of naturalistic stimuli (e.g., natural images and movies) is still lacking.…”

Object segmentation controls image reconstruction from natural scenes

“…which specific electrodes, filtering regime and others). The relevant region within Fig 7E (indicated by black rectangular outline) presents substantial modulations (reflected by red tint) between 30 ms and 70 ms. More accurate estimates of the timescale involved will require further EEG investigations combined with relevant single-unit measurements [ 53 , 68 ].…”

A recurrent neural model for proto-object based contour integration and figure-ground segregation

“…For a more detailed operational definition of how border-ownership selectivity is determined experimentally, see Section 2.4. Border-ownership coding has been studied using a wide variety of artificial stimuli, including those defined by luminance contrast, color contrast, figure outlines (Zhou et al, 2000), motion (von der Heydt et al, 2003), disparity (Zhou et al, 2000; Qiu and von der Heydt, 2005), and transparency (Qiu and von der Heydt, 2007) as well as, more recently, with faces (Hesse and Tsao, 2016) and within complex natural scenes (Williford and von der Heydt, 2014). …”