Increased functional network segregation in glioma patients posttherapy: A neurological compensatory response or catastrophe for cognition? [0.03%]
胶质瘤患者治疗后的功能网络分离增加：是神经补偿反应还是认知灾难？
Laurien De Roeck,Rob Colaes,Patrick Dupont et al.
Laurien De Roeck et al.
The brain operates through networks of interconnected regions, which can be disrupted by glial tumors and their treatment. This study investigates associations between this altered functional network topology and cognition in gliomas. We st...
Multilayer network analysis across cortical depths in 7-T resting-state fMRI [0.03%]
基于7T静息态功能磁共振的皮层深度多层网络分析
Parker Kotlarz,Kaisu Lankinen,Maria Hakonen et al.
Parker Kotlarz et al.
In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae," which is becoming...
Quantifying the influence of biophysical factors in shaping brain communication through remnant functional networks [0.03%]
通过残余功能网络量化生物物理因素在塑造脑沟通中的影响
Johan Nakuci,Javier Garcia,Kanika Bansal
Johan Nakuci
Functional connectivity (FC) reflects brain-wide communication essential for cognition, yet the role of underlying biophysical factors in shaping FC remains unclear. We quantify the influence of physical factors-structural connectivity (SC)...
Metric structural human connectomes: Localization and multifractality of eigenmodes [0.03%]
具有度量结构的人体连接组：特征模式的定位及多分形性
Anna Bobyleva,Alexander Gorsky,Sergei Nechaev et al.
Anna Bobyleva et al.
We explore the fundamental principles underlying the architecture of the human brain's structural connectome through the lens of spectral analysis of Laplacian and adjacency matrices. Building on the idea that the brain balances efficient i...
The impact of transcranial random noise stimulation (tRNS) on alpha coherence and verbal divergent thinking [0.03%]
经颅随机噪声刺激(tRNS)对alpha相干性和言语发散性思维的影响
Magdalena Camenzind,Rahel A Steuri,Branislav Savic et al.
Magdalena Camenzind et al.
Random noise stimulation (tRNS) applied to the dorsolateral prefrontal cortex (DLPFC) enhances fluency and originality in verbal divergent thinking tasks. However, the underlying neural mechanisms of this behavioral change remain unclear. G...
Whole-brain modular dynamics at rest predict sensorimotor learning performance [0.03%]
静息态全脑模块动力学预测感觉运动学习表现
Dominic I Standage,Daniel J Gale,Joseph Y Nashed et al.
Dominic I Standage et al.
Neural measures that predict cognitive performance are informative about the mechanisms underlying cognitive phenomena, with diagnostic potential for neuropathologies with cognitive symptoms. Among such markers, the modularity (subnetwork c...
Interdependence patterns of multifrequency oscillations predict visuomotor behavior [0.03%]
多频振荡的相互依赖模式可以预测视动行为
Jyotika Bahuguna,Antoine Schwey,Demian Battaglia et al.
Jyotika Bahuguna et al.
We show that sensorimotor behavior can be reliably predicted from single-trial EEG oscillations fluctuating in a coordinated manner across brain regions, frequency bands, and movement time epochs. We define high-dimensional oscillatory port...
Modelling low-dimensional interacting brain networks reveals organising principle in human cognition [0.03%]
建模低维相互作用脑网络可揭示人类认知中的组织原理
Yonatan Sanz Perl,Sebastian Geli,Eider Pérez-Ordoyo et al.
Yonatan Sanz Perl et al.
The discovery of resting-state networks shifted the focus from the role of local regions in cognitive tasks to the ongoing spontaneous dynamics in global networks. Recently, efforts have been invested to reduce the complexity of brain activ...
Predicting response speed and age from task-evoked effective connectivity [0.03%]
利用任务诱发有效连接度预测反应速度和年龄
Shufei Zhang,Kyesam Jung,Robert Langner et al.
Shufei Zhang et al.
Recent neuroimaging studies demonstrated that task-evoked functional connectivity (FC) may better predict individual traits than resting-state FC. However, the prediction properties of task-evoked effective connectivity (EC) remain unexplor...
Yosuke Morishima,Martijn van den Heuvel,Werner Strik et al.
Yosuke Morishima et al.
Recent advancements in neuroimaging data analysis facilitate the characterization of adaptive changes in brain network integration. This study introduces a distinctive approach that merges knowledge-informed and data-driven methodologies, o...