Before revision: We propose that homogeneous image regions may be used to quickly segment a visual scene, when an object hypothesis is not yet available. In a cooperative model of the konio-cellular and the parvo- or magno-cellular visual pathway of primates, we demonstrate how homogeneity-selective responses can be gained from LGN neurons using a spike-latency code, and how these responses can confine edge detection to borders between mid-sized objects. We propose that spike-latency-based homogeneity detection is a general neural principle that may apply to any sensory feature and modality. The mechanism is sensitive to exact spike timing, which makes it vulnerable to noise. Nevertheless we demonstrate how the mechanism can be made robust against realistic levels of neural cross talk in the brain .
After revision: In studies of the visual system as well as in computer vision, the focus is often on contrast edges. However, the primate visual system contains a large number of cells that are insensitive to spatial contrast and, instead, respond to uniform homogeneous illumination of their visual field. The purpose of this information remains unclear. Here, we propose a mechanism that detects feature homogeneity in visual areas, based on latency coding and spike time coincidence, in a purely feed-forward and therefore rapid manner. We demonstrate how homogeneity information can interact with information on contrast edges to potentially support rapid image segmentation. Furthermore, we analyze how neuronal crosstalk (noise) affects the mechanism's performance .