2020/11/27 by Debasis Mazumdar, Mazumdar, Debasis · 1 citation
Agricultural and Biological Sciences · Mathematics · Neuroscience · #Advanced Scientific Research Methods #FOS: Computer and information sciences #Morphological variations and asymmetry #Neural and Evolutionary Computing (cs.NE) #Visual perception and processing mechanisms
paper · pdf · doi:10.48550/arxiv.2011.13585
openalex publication_date 2020/11/27 · openalex created_date 2022/09/13 · openalex updated_date 2026/07/28
Representation of 2D frame less visual space as neural manifold and its\nmodelling in the frame work of information geometry is presented. Origin of\nhyperbolic nature of the visual space is investigated using evidences from\nneuroscience. Based on the results we propose that the processing of spatial\ninformation, particularly estimation of distance, perceiving geometrical curves\netc. in the human brain can be modeled in a parametric probability space\nendowed with Fisher-Rao metric. Compactness, convexity and differentiability of\nthe space is analysed and found that they obey the axioms of G space, proposed\nby Busemann. Further it is shown that it can be considered as a homogeneous\nRiemannian space of constant negative curvature. It is therefore ensured that\nthe space yields geodesics into it. Computer simulation of geodesics\nrepresenting a number of visual phenomena and advocating the hyperbolic\nstructure of visual space is carried out. Comparison of the simulated results\nwith the published experimental data is presented.\n