SEEG4D: a tool for 4D visualization of stereoelectroencephalography data [0.03%]
SEEG4D：一种立体脑电图数据的4D可视化工具
James L Evans,Matthew T Bramlet,Connor Davey et al.
James L Evans et al.
Epilepsy is a prevalent and serious neurological condition which impacts millions of people worldwide. Stereoelectroencephalography (sEEG) is used in cases of drug resistant epilepsy to aid in surgical resection planning due to its high spa...
Interpretable machine learning comprehensive human gait deterioration analysis [0.03%]
可解释机器学习在全面人类步态退化分析中的应用
Abdullah S Alharthi
Abdullah S Alharthi
Introduction: Gait analysis, an expanding research area, employs non-invasive sensors and machine learning techniques for a range of applications. In this study, we investigate the impact of cognitive decline conditions o...
Predicting the clinical prognosis of acute ischemic stroke using machine learning: an application of radiomic biomarkers on non-contrast CT after intravascular interventional treatment [0.03%]
基于治疗后非 Contrast CT 的影像组学标志物的急性脑梗死临床预后机器学习预测研究
Hongxian Gu,Yuting Yan,Xiaodong He et al.
Hongxian Gu et al.
Purpose: This study aimed to develop a radiomic model based on non-contrast computed tomography (NCCT) after interventional treatment to predict the clinical prognosis of acute ischemic stroke (AIS) with large vessel occl...
Investigating cortical complexity and connectivity in rats with schizophrenia [0.03%]
大鼠精神分裂症模型的皮层复杂度和连接性研究
Zongya Zhao,Yifan Feng,Menghan Wang et al.
Zongya Zhao et al.
Background: The above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on th...
A canonical polyadic tensor basis for fast Bayesian estimation of multi-subject brain activation patterns [0.03%]
一种用于快速估计多被试脑激活模式的Bayesian张量典范聚类基底方法
Michelle F Miranda
Michelle F Miranda
Task-evoked functional magnetic resonance imaging studies, such as the Human Connectome Project (HCP), are a powerful tool for exploring how brain activity is influenced by cognitive tasks like memory retention, decision-making, and languag...
Customizable automated cleaning of multichannel sleep EEG in SleepTrip [0.03%]
睡眠信号处理平台SleepTrip中的多导睡眠EEG信号自动批量化处理技术及参数优化研究
Roy Cox,Frederik D Weber,Eus J W Van Someren
Roy Cox
While standard polysomnography has revealed the importance of the sleeping brain in health and disease, more specific insight into the relevant brain circuits requires high-density electroencephalography (EEG). However, identifying and hand...
Corrigendum: Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism [0.03%]
更正：使用稳态机制构建具有独立表征的现实而可扩展的记忆模型
Marvin Kaster,Fabian Czappa,Markus Butz-Ostendorf et al.
Marvin Kaster et al.
[This corrects the article DOI: 10.3389/fninf.2024.1323203.]. Keywords: homeostatic plasticity; learning; me...
Published Erratum
Frontiers in neuroinformatics. 2024 Aug 9:18:1461597. DOI:10.3389/fninf.2024.1461597 2024
Peter A Tass,Hemant Bokil
Peter A Tass
Exploring white matter dynamics and morphology through interactive numerical phantoms: the White Matter Generator [0.03%]
通过交互式数值模型探索白质动态和形态：白质生成器
Sidsel Winther,Oscar Peulicke,Mariam Andersson et al.
Sidsel Winther et al.
Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. T...
M 3: using mask-attention and multi-scale for multi-modal brain MRI classification [0.03%]
使用掩模注意和多尺度的多模式脑MRI分类
Guanqing Kong,Chuanfu Wu,Zongqiu Zhang et al.
Guanqing Kong et al.
Introduction: Brain diseases, particularly the classification of gliomas and brain metastases and the prediction of HT in strokes, pose significant challenges in healthcare. Existing methods, relying predominantly on clin...