Neurogeometry of perception: isotropic and anisotropic aspects
This work addresses the problem of accurately modeling visual perception mechanisms for neuroscience and computer vision researchers, but appears incremental as it builds on existing geometric models.
The paper tackled the problem of modeling visual cortex connectivity by recognizing that edge co-occurrence histograms are not isotropic and are biased toward horizontal and vertical directions, and introduced a new non-isotropic cortical connectivity model that justified oblique phenomena comparable with experimental findings.
In this paper we first recall the definition of geometical model of the visual cortex, focusing in particular on the geometrical properties of horizontal cortical connectivity. Then we recognize that histograms of edges - co-occurrences are not isotropic distributed, and are strongly biased in horizontal and vertical directions of the stimulus. Finally we introduce a new model of non isotropic cortical connectivity modeled on the histogram of edges - co-occurrences. Using this kernel we are able to justify oblique phenomena comparable with experimental findings.