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Developing reliable methods to discriminate different transient brain states that change over time is a key neuroscientific challenge in brain imaging studies. Topological data analysis (TDA), a novel framework based on algebraic topology,…

神经元与认知 · 定量生物学 2023-12-19 Moo K. Chung , Soumya Das , Hernando Ombao

Computational models of cortical activity provide insight into the mechanisms of higher-order processing in the human brain including planning, perception and the control of movement. Activity in the cortex is ongoing even in the absence of…

神经元与认知 · 定量生物学 2023-07-07 Lysea Haggie , Thor Besier , Angus McMorland

We consider exploratory methods for the discovery of cortical functional connectivity. Typically, data for the i-th subject (i=1...NS) is represented as an NVxNT matrix Xi, corresponding to brain activity sampled at NT moments in time from…

统计方法学 · 统计学 2011-03-17 Roberto D. Pascual-Marqui , Rolando J. Biscay-Lirio

We investigated how the organization of functional brain networks was related to cognitive reserve (CR) during a memory task in healthy aging. We obtained the magnetoencephalographic functional networks of 20 elders with a high or low CR…

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to…

神经元与认知 · 定量生物学 2017-07-05 Luca Ambrogioni , Marcel A. J. van Gerven , Eric Maris

Large-scale functional networks have been extensively studied using resting state functional magnetic resonance imaging. However, the pattern, organization, and function of fine-scale network activity remain largely unknown. Here we…

神经元与认知 · 定量生物学 2017-03-01 Kun-Han Lu , Jun Young Jeong , Haiguang Wen , Zhongming Liu

The dynamics of neural networks is often characterized by collective behavior and quasi-synchronous events, where a large fraction of neurons fire in short time intervals, separated by uncorrelated firing activity. These global temporal…

无序系统与神经网络 · 物理学 2014-10-03 Raffaella Burioni , Mario Casartelli , Matteo di Volo , Roberto Livi , Alessandro Vezzani

Brain function emerges from coordinated activity across anatomically connected regions, where structural connectivity (SC) -- the network of white matter pathways - provides the physical substrate for functional connectivity (FC) -- the…

神经元与认知 · 定量生物学 2025-07-09 Sam Frank Kelemen , Joaquín Gõni , Sérgio Pequito , Arian Ashourvan

Working memory is a cognitive function involving the storage and manipulation of latent information over brief intervals of time, thus making it crucial for context-dependent computation. Here, we use a top-down modeling approach to examine…

神经元与认知 · 定量生物学 2021-11-17 Elham Ghazizadeh , ShiNung Ching

It has become increasingly popular to study the brain as a network due to the realization that functionality cannot be explained exclusively by independent activation of specialized regions. Instead, across a large spectrum of behaviors,…

神经元与认知 · 定量生物学 2014-07-22 Petko Bogdanov , Nazli Dereli , Danielle S. Bassett , Scott T. Grafton , Ambuj K. Singh

The functional brain network emerges from the complex, coordinated activity of distinct yet connected regions, which underlie the diverse repertoire of human cognitive functions. Structural Balance Theory (SBT) has been successfully applied…

神经元与认知 · 定量生物学 2025-09-09 Fahimeh Ahmadi , Zahra Moradimanesh , Reza Khosrowabadi , G. Reza Jafari

Little is currently known about the coordination of neural activity over longitudinal time-scales and how these changes relate to behavior. To investigate this issue, we used resting-state fMRI data from a single individual to identify the…

神经元与认知 · 定量生物学 2017-05-30 James M. Shine , Oluwasanmi Koyejo , Russell A. Poldrack

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these…

神经元与认知 · 定量生物学 2013-03-11 Sungwoo Ahn , Leonid L. Rubchinsky

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

We have investigated the role that different connectivity regimes play on the dynamics of a network of Hodgkin-Huxley neurons by computer simulations. The different connectivity topologies exhibit the following features: random connectivity…

无序系统与神经网络 · 物理学 2025-03-24 Luis F. Lago-Fernandez , Ramon Huerta , Fernando Corbacho , Juan A. Siguenza

Real-world networks in technology, engineering and biology often exhibit dynamics that cannot be adequately reproduced using network models given by smooth dynamical systems and a fixed network topology. Asynchronous networks give a…

动力系统 · 数学 2017-02-07 Christian Bick , Michael Field

Network theory provides a principled abstraction of the human brain: reducing a complex system into a simpler representation from which to investigate brain organisation. Recent advancement in the neuroimaging field are towards representing…

神经元与认知 · 定量生物学 2016-03-23 A. W. Chung , M. D. Schirmer , M. L. Krishna , G. Ball , P. Aljabar , A. D. Edwards , G. Montana

The human brain has been studied at multiple scales, from neurons, circuits, areas with well defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed…

生物物理 · 物理学 2012-05-17 Lazaros K. Gallos , Mariano Sigman , Hernan A. Makse

Complex systems of many interacting components exhibit patterns of recurrence and emergent behaviors in their time evolution that can be understood from a new perspective of physics of information dynamics, modeled after one such system,…

无序系统与神经网络 · 物理学 2026-01-27 Uday S. Goteti , Shane A. Cybart , Robert C. Dynes

Human brain networks can be characterized at different temporal or spatial scales given by the age of the subject or the spatial resolution of the neuroimaging method. Integration of data across scales can only be successful if the combined…