LYNSU: automated 3D neuropil segmentation of fluorescent images for Drosophila brains [0.03%]
LYNSU：对荧光图像的果蝇大脑神经脉络进行自动化三维分割
Kai-Yi Hsu,Chi-Tin Shih,Nan-Yow Chen et al.
Kai-Yi Hsu et al.
The brain atlas, which provides information about the distribution of genes, proteins, neurons, or anatomical regions, plays a crucial role in contemporary neuroscience research. To analyze the spatial distribution of those substances based...
Horea-Ioan Ioanas,Austin Macdonald,Yaroslav O Halchenko
Horea-Ioan Ioanas
The value of research articles is increasingly contingent on complex data analysis results which substantiate their claims. Compared to data production, data analysis more readily lends itself to a higher standard of transparency and repeat...
Dynamic topological data analysis: a novel fractal dimension-based testing framework with application to brain signals [0.03%]
一种基于分形维度的拓扑数据分析新框架及其在脑信号处理中的应用
Anass B El-Yaagoubi,Moo K Chung,Hernando Ombao
Anass B El-Yaagoubi
Topological data analysis (TDA) is increasingly recognized as a promising tool in the field of neuroscience, unveiling the underlying topological patterns within brain signals. However, most TDA related methods treat brain signals as if the...
Editorial: Innovative methods for sleep staging using neuroinformatics [0.03%]
专家观点：基于神经信息学的睡眠分期创新方法
Antonio Fernández-Caballero,Michel Le Van Quyen
Antonio Fernández-Caballero
Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage [0.03%]
可解释的深度学习框架：解读虚假信念任务中幼儿的大脑活动并预测个体表现
Km Bhavna,Azman Akhter,Romi Banerjee et al.
Km Bhavna et al.
Decoding of cognitive states aims to identify individuals' brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand bra...
Enhancing brain tumor detection in MRI with a rotation invariant Vision Transformer [0.03%]
一种旋转不变的视觉变换器在MRI脑肿瘤检测中的应用增强
Palani Thanaraj Krishnan,Pradeep Krishnadoss,Mukund Khandelwal et al.
Palani Thanaraj Krishnan et al.
Background: The Rotation Invariant Vision Transformer (RViT) is a novel deep learning model tailored for brain tumor classification using MRI scans. Metho...
Identifying discriminative features of brain network for prediction of Alzheimer's disease using graph theory and machine learning [0.03%]
基于图论和机器学习的阿尔茨海默病预测脑网络判别特征识别
S M Shayez Karim,Md Shah Fahad,R S Rathore
S M Shayez Karim
Alzheimer's disease (AD) is a challenging neurodegenerative condition, necessitating early diagnosis and intervention. This research leverages machine learning (ML) and graph theory metrics, derived from resting-state functional magnetic re...
Finding the limits of deep learning clinical sensitivity with fractional anisotropy (FA) microstructure maps [0.03%]
基于分数各向异性(Fractional Anisotropy, FA)微结构图的深度学习临床敏感性分析
Marta Gaviraghi,Antonio Ricciardi,Fulvia Palesi et al.
Marta Gaviraghi et al.
Background: Quantitative maps obtained with diffusion weighted (DW) imaging, such as fractional anisotropy (FA) -calculated by fitting the diffusion tensor (DT) model to the data,-are very useful to study neurological dis...
Events in context-The HED framework for the study of brain, experience and behavior [0.03%]
情境中的事件——脑、经验与行为研究的HED框架
Scott Makeig,Kay Robbins
Scott Makeig
The brain is a complex dynamic system whose current state is inextricably coupled to awareness of past, current, and anticipated future threats and opportunities that continually affect awareness and behavioral goals and decisions. Brain ac...
Harmonizing data on correlates of sleep in children within and across neurodevelopmental disorders: lessons learned from an Ontario Brain Institute cross-program collaboration [0.03%]
在神经发育障碍内部和跨障碍中协调儿童睡眠相关数据：从安大略省脑研究所跨计划合作中吸取的教训
Patrick G McPhee,Anthony L Vaccarino,Sibel Naska et al.
Patrick G McPhee et al.
There is an increasing desire to study neurodevelopmental disorders (NDDs) together to understand commonalities to develop generic health promotion strategies and improve clinical treatment. Common data elements (CDEs) collected across stud...