12 papers · ranked by Valyu relevance
Andrea Avena-Koenigsberger, Joaquín Goñi, Ricard Solé, Olaf Sporns
The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design…
Joaquín Goñi, Andrea Avena-Koenigsberger, Nieves Velez de Mendizabal, Martijn P. van den Heuvel + 3 more
Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the…
Duy Duong-Tran, Kausar Abbas, Enrico Amico, Bernat Corominas-Murtra + 4 more
The quantification of human brain functional (re)configurations across varying cognitive demands remains an unresolved topic. We propose that such functional configurations may be categorized into three different types: (a) network configural breadth, (b) task-to task transitional reconfiguration, and (c) within-task…
Andrea Avena-Koenigsberger, Joaquín Goñi, Richard F. Betzel, Martijn P. van den Heuvel + 4 more
'Martijn P. van den Heuvel' 'Alessandra Griffa' 'Patric Hagmann' 'Jean-Philippe Thiran' 'Olaf Sporns'] Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial…
Sarah E. Morgan, Sophie Achard, Maite Termenon, Edward T. Bullmore + 1 more
'Petra E. Vértes'] We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal…
Junji Ma, Xitian Chen, Yue Gu, Liangfang Li + 2 more
'Zhengjia Dai'] Title: Abstract The human brain structural network is thought to be shaped by the optimal trade-off between cost and efficiency. However, most studies on this problem have focused on only the trade-off between cost and global efficiency (i.e., integration) and have overlooked the efficiency of…
Filip Milisav, Vincent Bazinet, Richard F. Betzel, Bratislav Misic
Scientific discovery in connectomics relies on network null models. The prominence of network features is conventionally evaluated against null distributions estimated using randomized networks. Modern imaging technologies provide an increasingly rich array of biologically meaningful edge weights. Despite the…
P. David Polly
A morphospace is any mathematical space defined by morphological variables. The simplest morphospaces are univariate, but they can have any number of dimensions defined directly by variables like length, width, and height, by transformed variables like principal components axes, or by axes derived from pairwise…
Marco Tamborini
This paper proposes the integration of an ethical dimension into the concept and design of morphospace. This is traditionally used in paleontology, architecture, and bioengineering to visualize and generate theoretically possible forms given certain parameters. Drawing from Value-Sensitive Design (VSD) and Responsible…
Pablo S. Milla Carmona, Oscar E. R. Lehmann, William J. Deakin, Eduardo M. Soto + 1 more
'Eduardo M. Soto' 'Ignacio M. Soto'] Title: ABSTRACT Ordination is a critical step of geometric morphometrics that allows simplification of high-dimensional shape spaces into low-dimensional representations summarising shape variation. While this is routinely used to visualise the main patterns of morphometric data…
Borja Esteve-Altava
The study of morphological modularity using anatomical networks is growing in recent years. A common strategy to find the best network partition uses community detection algorithms that optimize the modularity Q function. Because anatomical networks and their modules tend to be small, this strategy often produces two…
Dinghua Shi, Zhifeng Chen, Chuang Ma, Guanrong Chen
Topological data analysis can extract effective information from higher-dimensional data. Its mathematical basis is persistent homology. The persistent homology can calculate topological features at different spatiotemporal scales of the dataset, that is, establishing the integrated taxonomic relation among points…