Скачать или смотреть Quantitative Characterization of the Human Retinotopic Map Based on Quasiconformal Mapping

Speaker: Yalin Wang, Dept. of Computer Science, Arizona State University, USA

Title: Quantitative Characterization of the Human Retinotopic Map Based on Quasiconformal Mapping

Abstract: The retinotopic map depicts the cortical neurons' response to visual stimuli on the retina and has contributed significantly to our understanding of human visual system. Although recent advances in high field functional magnetic resonance imaging (fMRI) have made it possible to generate the in vivo retinotopic map with great detail, quantifying the map remains challenging. Existing quantification methods do not preserve surface topology and often introduce large geometric distortions to the map. We introduced a new framework based on computational conformal geometry and quasiconformal Teichmuller theories to quantify the retinotopic map and further refine its topological condition. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to rigorously and complete characterize the retinotopy map by quantifying the local quasiconformal mapping distortion at each visual field location. The obtained Beltrami coefficient map (BCM) provided fully invertible retinotopic maps. We successfully applied the new framework to analyze the V1 retinotopic maps from the Human Connectome Project (HCP, n=181), the largest state of the art retinotopy dataset currently available. With unprecedented precision, we found that the V1 retinotopic map was quasiconformal and the local mapping distortions were similar across observers. The new framework can be applied to other visual areas and retinotopic maps of individuals with and without eye diseases, and improve our understanding of visual cortical organization in normal and clinical populations. In this talk, we will also briefly introduce our recent progress on retinotopic map topological smoothing and retinotopic map registration research.