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Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. Network control theory is a powerful tool…

Neurons and Cognition · Quantitative Biology 2019-08-12 Teresa M. Karrer , Jason Z. Kim , Jennifer Stiso , Ari E. Kahn , Fabio Pasqualetti , Ute Habel , Danielle S. Bassett

There has been huge interest in studying human brain connectomes inferred from different imaging modalities and exploring their relationship with human traits, such as cognition. Brain connectomes are usually represented as networks, with…

Machine Learning · Statistics 2021-09-14 Meimei Liu , Zhengwu Zhang , David B. Dunson

Motivated by the flexibility of biological neural networks whose connectivity structure changes significantly during their lifetime, we introduce the Unstructured Recursive Network (URN) and demonstrate that it can exhibit similar…

Machine Learning · Computer Science 2019-11-27 Siavash Golkar

It is widely believed that the formation of brain network structure is under the pressure of optimal trade-off between reducing wiring cost and promoting communication efficiency. However, the question of whether this trade-off exists in…

Neurons and Cognition · Quantitative Biology 2020-12-10 Junji Ma , Jinbo Zhang , Ying Lin , Zhengjia Dai

Rich-club, assortativity and clustering coefficients are frequently-used measures to estimate topological properties of complex networks. Here we find that the connectivity among a very small portion of the richest nodes can dominate the…

Physics and Society · Physics 2015-05-20 Xiao-Ke Xu , Jie Zhang , Michael Small

Networks are widely used to represent interaction pattern among the components in complex systems. Structures of real networks from differ- ent domains may vary quite significantly. Since there is an interplay be- tween network architecture…

Quantitative Methods · Quantitative Biology 2016-05-10 Krishanu Deyasi , Shashankaditya Upadhyay , Anirban Banerjee

Endowing brain anatomy, dynamics, and function with a network structure is becoming standard in neuroscience. In its simplest form, a network is a collection of units and relationships between them. The pattern of relations among the units…

Neurons and Cognition · Quantitative Biology 2025-07-22 David Papo , Javier M. Buldú

Driven by growing interest in the sciences, industry, and among the broader public, a large number of empirical studies have been conducted in recent years of the structure of networks ranging from the internet and the world wide web to…

Social and Information Networks · Computer Science 2018-06-08 M. E. J. Newman

Rich-club ordering and the dyadic effect are two phenomena observed in complex networks that are based on the presence of certain substructures composed of specific nodes. Rich-club ordering represents the tendency of highly connected and…

Social and Information Networks · Computer Science 2019-04-12 Matteo Cinelli , Giovanna Ferraro , Antonio Iovanella

Many observables of brain dynamics appear to be optimized for computation. Which connectivity structures underlie this fine-tuning? We propose that many of these structures are naturally encoded in the space that more directly relates to…

Disordered Systems and Neural Networks · Physics 2023-09-18 Lorenzo Tiberi , David Dahmen , Moritz Helias

Social groups are fundamental elements of any social system. Their emergence and evolution are closely related to the structure and dynamics of a social system. Research on social groups was primarily focused on the growth and the structure…

Physics and Society · Physics 2022-12-09 Ana Vranić , Jelena Smiljanić , Marija Mitrović Dankulov

Neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of…

Neurons and Cognition · Quantitative Biology 2015-05-13 Sebastian Ahnert , Luciano da Fontoura Costa

Deep learning (DL) methods are increasingly outperforming classical approaches in brain imaging, yet their generalizability across diverse imaging cohorts remains inadequately assessed. As age and sex are key neurobiological markers in…

The brain is a complex system comprising a myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying such intricate…

The connectome, a map of the structural and/or functional connections in the brain, provides a complex representation of the neurobiological phenotypes on which it supervenes. This information-rich data modality has the potential to…

The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of functions and behaviors. Understanding patterns of these complex interactions and how they are…

Neurons and Cognition · Quantitative Biology 2024-08-06 Suman Kulkarni , Dani S. Bassett

Functional brain network has been widely studied to understand the relationship between brain organization and behavior. In this paper, we aim to explore the functional connectivity of brain network under a \emph{multi-step} cognitive task…

Neurons and Cognition · Quantitative Biology 2017-12-06 Shi-Min Cai , Wei Chen , Dong-Bai Liu , Ming Tang , Xun Chen

One of the most important features of spatial networks such as transportation networks, power grids, Internet, neural networks, is the existence of a cost associated with the length of links. Such a cost has a profound influence on the…

Physics and Society · Physics 2013-06-04 Rémi Louf , Pablo Jensen , Marc Barthelemy

Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. One crucial step when studying the structure and dynamics of…

Physics and Society · Physics 2010-09-16 Yong-Yeol Ahn , James P. Bagrow , Sune Lehmann

Understanding how decision making changes across the lifespan is a central challenge for neuroscience, yet research on cognitive aging has remained largely disconnected from the theoretical and computational advances that now shape modern…

Neurons and Cognition · Quantitative Biology 2026-03-04 Michael B. Ryan , Letizia Ye , Anne K. Churchland
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