Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks

Abstract We analyze networks of functional correlations between brain regions to identify changes in their structure caused by Attention Deficit Hyperactivity Disorder (adhd). We express the task for finding changes as a network anomaly detection problem on temporal networks. We propose the use of a...

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Autores principales:	Tanima Chatterjee, Réka Albert, Stuti Thapliyal, Nazanin Azarhooshang, Bhaskar DasGupta
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d059dd5758ab48b8b4455c31f954b891
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spelling	oai:doaj.org-article:d059dd5758ab48b8b4455c31f954b8912021-12-02T18:03:15ZDetecting network anomalies using Forman–Ricci curvature and a case study for human brain networks10.1038/s41598-021-87587-z2045-2322https://doaj.org/article/d059dd5758ab48b8b4455c31f954b8912021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87587-zhttps://doaj.org/toc/2045-2322Abstract We analyze networks of functional correlations between brain regions to identify changes in their structure caused by Attention Deficit Hyperactivity Disorder (adhd). We express the task for finding changes as a network anomaly detection problem on temporal networks. We propose the use of a curvature measure based on the Forman–Ricci curvature, which expresses higher-order correlations among two connected nodes. Our theoretical result on comparing this Forman–Ricci curvature with another well-known notion of network curvature, namely the Ollivier–Ricci curvature, lends further justification to the assertions that these two notions of network curvatures are not well correlated and therefore one of these curvature measures cannot be used as an universal substitute for the other measure. Our experimental results indicate nine critical edges whose curvature differs dramatically in brains of adhd patients compared to healthy brains. The importance of these edges is supported by existing neuroscience evidence. We demonstrate that comparative analysis of curvature identifies changes that more traditional approaches, for example analysis of edge weights, would not be able to identify.Tanima ChatterjeeRéka AlbertStuti ThapliyalNazanin AzarhooshangBhaskar DasGuptaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tanima Chatterjee Réka Albert Stuti Thapliyal Nazanin Azarhooshang Bhaskar DasGupta Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
description	Abstract We analyze networks of functional correlations between brain regions to identify changes in their structure caused by Attention Deficit Hyperactivity Disorder (adhd). We express the task for finding changes as a network anomaly detection problem on temporal networks. We propose the use of a curvature measure based on the Forman–Ricci curvature, which expresses higher-order correlations among two connected nodes. Our theoretical result on comparing this Forman–Ricci curvature with another well-known notion of network curvature, namely the Ollivier–Ricci curvature, lends further justification to the assertions that these two notions of network curvatures are not well correlated and therefore one of these curvature measures cannot be used as an universal substitute for the other measure. Our experimental results indicate nine critical edges whose curvature differs dramatically in brains of adhd patients compared to healthy brains. The importance of these edges is supported by existing neuroscience evidence. We demonstrate that comparative analysis of curvature identifies changes that more traditional approaches, for example analysis of edge weights, would not be able to identify.
format	article
author	Tanima Chatterjee Réka Albert Stuti Thapliyal Nazanin Azarhooshang Bhaskar DasGupta
author_facet	Tanima Chatterjee Réka Albert Stuti Thapliyal Nazanin Azarhooshang Bhaskar DasGupta
author_sort	Tanima Chatterjee
title	Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
title_short	Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
title_full	Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
title_fullStr	Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
title_full_unstemmed	Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
title_sort	detecting network anomalies using forman–ricci curvature and a case study for human brain networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d059dd5758ab48b8b4455c31f954b891
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Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks

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