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相关论文: Frequency-based brain networks: From a multiplex f…

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Human brains exhibit highly organized multiscale neurophysiological dynamics. Understanding those dynamic changes and the neuronal networks involved is critical for understanding how the brain functions in health and disease. Functional…

神经元与认知 · 定量生物学 2024-09-09 Manuel Morante , Kristian Frølich , Naveed ur Rehman

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications. Such systems include…

The human brain is organized as a complex network, where connections between regions are characterized by both functional connectivity (FC) and structural connectivity (SC). While previous studies have primarily focused on network-level…

Network motifs can capture basic interaction patterns and inform the functional properties of networks. However, real-world complex systems often have multiple types of relationships, which cannot be represented by a monolayer network. The…

物理与社会 · 物理学 2019-03-06 Lu Zhong , Qingpeng Zhang , Dong Yang , Guanrong Chen , Shi Yu

Oscillatory synchrony is hypothesized to support the flow of information between brain regions, with different phase-locked configurations enabling activation of different effective interactions. Along these lines, past work has proposed…

神经元与认知 · 定量生物学 2022-08-26 Lia Papadopoulos , Demian Battaglia , Dani S. Bassett

Multilayer networks offer a powerful framework for modeling complex systems across diverse domains, effectively capturing multiple types of connections and interdependent subsystems commonly found in real world scenarios. To analyze these…

社会与信息网络 · 计算机科学 2026-02-20 Martin Guillemaud , Vera Dinkelacker , Mario Chavez

The interactions among the elementary components of many complex systems can be qualitatively different. Such systems are therefore naturally described in terms of multiplex or multi-layer networks, i.e. networks where each layer stands for…

物理与社会 · 物理学 2015-09-15 Vincenzo Nicosia , Vito Latora

Brain network discovery aims to find nodes and edges from the spatio-temporal signals obtained by neuroimaging data, such as fMRI scans of human brains. Existing methods tend to derive representative or average brain networks, assuming…

机器学习 · 计算机科学 2023-11-07 Hang Yin , Yao Su , Xinyue Liu , Thomas Hartvigsen , Yanhua Li , Xiangnan Kong

Empirical studies over the past two decades have supported the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically-mediated…

神经元与认知 · 定量生物学 2013-06-28 Felix Siebenhuhner , Shennan A. Weiss , Richard Coppola , Daniel R. Weinberger , Danielle S. Bassett

We propose a novel class of separable multilayer network models to capture cross-layer dependencies in multilayer networks, enabling the analysis of how interactions in one or more layers may influence interactions in other layers. Our…

统计理论 · 数学 2025-01-10 Jiaheng Li , Jonathan R. Stewart

What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents,…

物理与社会 · 物理学 2017-04-18 Federico Battiston , Vincenzo Nicosia , Vito Latora

Data produced by resting-state functional Magnetic Resonance Imaging are widely used to infer brain functional connectivity networks. Such networks correlate neural signals to connect brain regions, which consist in groups of dependent…

统计方法学 · 统计学 2023-12-05 Hanâ Lbath , Alexander Petersen , Sophie Achard

The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semi-annealed approximation to study the stability properties of Random Boolean Networks…

物理与社会 · 物理学 2012-10-31 Emanuele Cozzo , Alex Arenas , Yamir Moreno

We study the relationship between the frequency of a function and the speed at which a neural network learns it. We build on recent results that show that the dynamics of overparameterized neural networks trained with gradient descent can…

机器学习 · 计算机科学 2019-12-03 Ronen Basri , David Jacobs , Yoni Kasten , Shira Kritchman

In neurosciences, the brain processes information via the firing patterns of connected neurons operating across a spectrum of frequencies. To better understand the effects of these frequencies in the neuron dynamics, we have simulated a…

神经元与认知 · 定量生物学 2025-11-21 Gabriel Marghoti , Thiago L. Prado , Miguel A. F. Sanjuán , Sergio R. Lopes

Brain activity is intrinsically a neural dynamic process constrained by anatomical space. This leads to significant variations in spatial distribution patterns and correlation patterns of neural activity across variable and heterogeneous…

机器学习 · 计算机科学 2026-03-10 Hongjie Jiang , Yifei Tang , Shuqiang Wang

Among the versatile forms of dynamical patterns of activity exhibited by the brain, oscillations are one of the most salient and extensively studied, yet are still far from being well understood. In this paper, we provide various structural…

系统与控制 · 电气工程与系统科学 2021-08-12 Erfan Nozari , Robert Planas , Jorge Cortes

Functional connections in the brain are frequently represented by weighted networks, with nodes representing locations in the brain, and edges representing the strength of connectivity between these locations. One challenge in analyzing…

应用统计 · 统计学 2022-09-28 Yura Kim , Daniel Kessler , Elizaveta Levina

The coexistence of multiple types of interactions within social, technological and biological networks has moved the focus of the physics of complex systems towards a multiplex description of the interactions between their constituents.…

We study the time scales associated to diffusion processes that take place on multiplex networks, i.e. on a set of networks linked through interconnected layers. To this end, we propose the construction of a supra-Laplacian matrix, which…