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Understanding the intricate architecture of brain networks and its connection to brain function is essential for deciphering the underlying principles of cognition and disease. While traditional graph-theoretical measures have been widely…

混沌动力学 · 物理学 2025-11-13 Anca Radulescu , Eva Kaslik , Alexandru Fikl , Johan Nakuci , Sarah Muldoon , Michael Anderson

Connectomics and network neuroscience offer quantitative scientific frameworks for modeling and analyzing networks of structurally and functionally interacting neurons, neuronal populations, and macroscopic brain areas. This shift in…

神经元与认知 · 定量生物学 2020-10-06 Richard Betzel

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural…

神经元与认知 · 定量生物学 2020-02-27 Gabriel Koch Ocker , Krešimir Josić , Eric Shea-Brown , Michael A. Buice

Emerging evidence shows that the modular organization of the human brain allows for better and efficient cognitive performance. Many of these cognitive functions are very fast and occur in subsecond time scale such as the visual object…

神经元与认知 · 定量生物学 2018-08-01 J. Rizkallah , P. Benquet , A. Kabbara , O. Dufor , F. Wendling , M. Hassan

Multimodal MRI offers complementary multi-scale information to characterize the brain structure. However, it remains challenging to effectively integrate multimodal MRI while achieving neuroscience interpretability. Here we propose to use…

神经元与认知 · 定量生物学 2025-12-15 Chengzhi Xia , Jianwei Chen , Yixuan Jiang , Qi Yan , Chao Li

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

Understanding how the brain encodes external stimuli and how these stimuli can be decoded from the measured brain activities are long-standing and challenging questions in neuroscience. In this paper, we focus on reconstructing the complex…

神经元与认知 · 定量生物学 2022-10-05 Sikun Lin , Thomas Sprague , Ambuj K Singh

Dynamic instability in the cytoskeleton underlies a great many vital cellular processes. In neurons, it is thought to play a role in information processing and the establishment of synaptic connections. It is from this interneuronal…

医学物理 · 物理学 2019-12-19 Gweneth Andersen

The human brain forms functional networks on all spatial scales. Modern fMRI scanners allow to resolve functional brain data in high resolutions, allowing to study large-scale networks that relate to cognitive processes. The analysis of…

神经元与认知 · 定量生物学 2019-05-14 Melanie Weber , Johannes Stelzer , Emil Saucan , Alexander Naitsat , Gabriele Lohmann , Jürgen Jost

Rich, spontaneous brain activity has been observed across a range of different temporal and spatial scales. These dynamics are thought to be important t for efficient neural functioning. Experimental evidence suggests that these neural…

神经元与认知 · 定量生物学 2015-01-21 Peter J. Hellyer , Barbara Jachs , Robert Leech , Claudia Clopath

Historically, functional magnetic resonance imaging (fMRI) of the brain has focused primarily on gray matter, particularly the cortical gray matter and associated nuclei. However, recent work has demonstrated that functional activity in…

医学物理 · 物理学 2025-07-10 Zhiyuan Li , Kurt G. Schilling , Bennett A. Landman

We analyze the connectivity structure of weighted brain networks extracted from spontaneous magnetoencephalographic (MEG) signals of healthy subjects and epileptic patients (suffering from absence seizures) recorded at rest. We find that,…

数据分析、统计与概率 · 物理学 2011-01-21 M. Chavez , M. Valencia , V. Navarro , V. Latora , J. Martinerie

An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand the relationship between functional fluctuation and human cognition/behavior using a data-driven approach. To…

机器学习 · 计算机科学 2024-09-18 Jiaqi Ding , Tingting Dan , Ziquan Wei , Hyuna Cho , Paul J. Laurienti , Won Hwa Kim , Guorong Wu

The neural networks of the human brain act as very efficient parallel processing computers co-ordinating memory related responses to a multitude of input signals from sensory organs. Information storage, update and appropriate retrieval are…

chao-dyn · 物理学 2015-06-24 A. M. Selvam

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections at macro scale. Over the last two decades, the study of brain connectivity using…

We propose a framework for jointly modeling the geometry and functionality in high dimensional functional surfaces. The proposed mixed effects model characterizes effects of subject-specific covariates and exogenous stimuli on functional…

应用统计 · 统计学 2023-02-10 Jingjing Zou , Chi-Hua Chen , John A. D. Aston

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…

Activity in the human brain moves between diverse functional states to meet the demands of our dynamic environment, but fundamental principles guiding these transitions remain poorly understood. Here, we capitalize on recent advances in…

\hspace{2mm} Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of…

图像与视频处理 · 电气工程与系统科学 2025-12-30 Davood Karimi , Simon K. Warfield

White matter (WM) tract segmentation is a crucial step for brain connectivity studies. It is performed on diffusion magnetic resonance imaging (dMRI), and deep neural networks (DNNs) have achieved promising segmentation accuracy. Existing…

图像与视频处理 · 电气工程与系统科学 2023-09-26 Wan Liu , Chuyang Ye