Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

Figure-ground segregation is a necessary process for accurate visual recognition. Previous neurophysiological and human brain imaging studies have suggested that foreground-background segregation relies on both enhanced foreground representation and suppressed background representation. However, in humans, it is not known when and how foreground and background processing play a role in texture segregation.
To answer this question, it is crucial to extract and dissociate the neural signals elicited by the foreground and background of a figure texture with high temporal resolution. Here, we combined an electroencephalogram (EEG) recording and a temporal response function (TRF) approach to specifically track the neural responses to the foreground and background of a figure texture from the overall EEG recordings in the luminance-tracking TRF. A uniform texture was included as a neutral condition. The texture segregation visual evoked potential (tsVEP) was calculated by subtracting the uniform TRF from the foreground and background TRFs, respectively, to index the specific segregation activity.
We found that the foreground and background of a figure texture were processed differently during texture segregation. In the posterior region of the brain, we found a negative component for the foreground tsVEP in the early stage of foreground-background segregation, and two negative components for the background tsVEP in the early and late stages. In the anterior region, we found a positive component for the foreground tsVEP in the late stage, and two positive components for the background tsVEP in the early and late stages of texture processing.
In this study we investigated the temporal profile of foreground and background processing during texture segregation in human participants at a high time resolution. The results demonstrated that the foreground and background jointly contribute to figure-ground segregation in both the early and late phases of texture processing. Our findings provide novel evidence for the neural correlates of foreground-background modulation during figure-ground segregation in humans.

Saccadic localisation of targets of various properties has been extensively studied, but rarely for texture-defined figures. In this paper, three experiments that investigate the way information from a texture target is processed in order to provide a signal for eye movement control are presented. Participants made saccades to target regions embedded in a background structure, and the saccade landing position and latency were measured. The textures comprised line elements, with orientations of the lines configured to form the figure and ground. Various orientation profile configurations (Block, Blur, and Cornsweet), were used in order to measure the role of edge profiles in driving eye movements and producing salience. We found that in all cases the visual system is in fact able to effectively segregate a texture figure from the ground in order to accurately plan a saccade to the target-figure. While saccadic latency was the highest for the Blur profile, the mean saccadic landing position was mostly unaffected by the various profiles (Experiment 1). More specifically, we showed that saccades were directed to the centre-of-gravity of the target (Experiment 2). We also found that figures with information of orientation contrast at both the edge and centre of figure (i.e. Block) produced the highest level of saliency in attracting eye movements (Experiment 3). Overall, the results show that saccades are planned on the representation of the whole target shape rather than a local salient region based on orientation contrast cues, and that the various texture profiles were important only to the extent that they affected the time to programme a saccade.

Behavioral and electroencephalography (EEG) data were analyzed from 30 participants performing a demanding, attention-capturing task in which they had to detect an occasional decrement of luminance of small discs. Crucially, numerous white segments in the background were presented either in random orientations or configuring a contour shape of a square or a diamond. The participants\' awareness of these background configurations was tested with a questionnaire after the first and second sessions. Based on the questionnaire responses, participants were divided into \"aware\" and \"unaware\" groups. These data may be of interest to researchers who wish to understand attentional effects on Gestalt integration processes, as well as luminance discrimination.

The visual cortex is hierarchically organized, with low-level areas coding for simple features and higher areas for complex ones. Feedforward and feedback connections propagate information between areas in opposite directions, but their functional roles are only partially understood. We used electrical microstimulation to perturb the propagation of neuronal activity between areas V1 and V4 in monkeys performing a texture-segregation task. In both areas, microstimulation locally caused a brief phase of excitation, followed by inhibition. Both these effects propagated faithfully in the feedforward direction from V1 to V4. Stimulation of V4, however, caused little V1 excitation, but it did yield a delayed suppression during the late phase of visually driven activity. This suppression was pronounced for the V1 figure representation and weaker for background representations. Our results reveal functional differences between feedforward and feedback processing in texture segregation and suggest a specific modulating role for feedback connections in perceptual organization.

In contour integration, increased difficulty in detection and shape discrimination of a chain of parallel elements (a ladder contour) compared to collinear elements (a snake contour) suggests more extensive processing of ladders than of snakes. In addition, conceptual similarities between ladders and textures - which also involve grouping of parallel elements - raises the question whether ladder and texture processing requires feedback from higher visual areas while snakes are processed in a fast feedforward sweep. We tested this in a response priming paradigm, where participants responded as quickly and accurately as possible to the orientation of a diagonal contour in a Gabor array (target). The diagonal was defined either by a snake, ladder, texture, or a continuous line. The target was preceded with varying stimulus onset asynchrony (SOA) by a prime that was either a snake, ladder, or texture, and was consistent or inconsistent to the response demands of the target. Resulting priming effects clearly distinguished between processing of snakes, ladders, and textures. Effects generally increased with SOA but were stronger for snakes and textures compared to ladders. Importantly, only priming effects for snakes were fully present already in the fastest response times, in accordance with a simple feedforward processing model. We conclude that snakes, ladders, and textures do not share similar processing characteristics, with snakes exhibiting a pronounced processing advantage.