Topology-preserving smoothing of retinotopic maps.

Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortica...

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Autores principales:	Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/25d6a0b32d82487cb94fb5d3f7301839
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spelling	oai:doaj.org-article:25d6a0b32d82487cb94fb5d3f73018392021-12-02T19:58:09ZTopology-preserving smoothing of retinotopic maps.1553-734X1553-735810.1371/journal.pcbi.1009216https://doaj.org/article/25d6a0b32d82487cb94fb5d3f73018392021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009216https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps.Yanshuai TuDuyan TaZhong-Lin LuYalin WangPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009216 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Yanshuai Tu Duyan Ta Zhong-Lin Lu Yalin Wang Topology-preserving smoothing of retinotopic maps.
description	Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps.
format	article
author	Yanshuai Tu Duyan Ta Zhong-Lin Lu Yalin Wang
author_facet	Yanshuai Tu Duyan Ta Zhong-Lin Lu Yalin Wang
author_sort	Yanshuai Tu
title	Topology-preserving smoothing of retinotopic maps.
title_short	Topology-preserving smoothing of retinotopic maps.
title_full	Topology-preserving smoothing of retinotopic maps.
title_fullStr	Topology-preserving smoothing of retinotopic maps.
title_full_unstemmed	Topology-preserving smoothing of retinotopic maps.
title_sort	topology-preserving smoothing of retinotopic maps.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/25d6a0b32d82487cb94fb5d3f7301839
work_keys_str_mv	AT yanshuaitu topologypreservingsmoothingofretinotopicmaps AT duyanta topologypreservingsmoothingofretinotopicmaps AT zhonglinlu topologypreservingsmoothingofretinotopicmaps AT yalinwang topologypreservingsmoothingofretinotopicmaps
_version_	1718375767869489152

Topology-preserving smoothing of retinotopic maps.

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