  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. We
show that the detrimental effects of crosstalk can be partly mitigated through
delayed feed-forward inhibition that shapes bi-phasic post-synaptic events. The
delay of the feed-forward inhibition allows effectively controlling the size of
the temporal integration window and, thereby, the coincidence threshold. The
proposed model is based on single-spike latency codes in a purely feed-forward
architecture that supports low-latency processing, making it an attractive
scheme of computation in spiking neuronal networks where rapid responses and
low spike counts are desired.
