Evaluating machine learning pipelines for multimodal neuroimaging in small cohorts: an ALS case study [0.03%]
小样本队列中多模态神经影像机器学习流程的评估：ALS病例研究
Shailesh Appukuttan,Aude-Marie Grapperon,Mounir Mohamed El Mendili et al.
Shailesh Appukuttan et al.
Advancements in machine learning hold great promise for the analysis of multimodal neuroimaging data. They can help identify biomarkers and improve diagnosis for various neurological disorders. However, the application of such techniques fo...
NESTML: a generic modeling language and code generation tool for the simulation of spiking neural networks with advanced plasticity rules [0.03%]
巢氏语言及代码生成工具：用于具有先进可塑性规则的脉冲神经网络仿真的通用建模语言和代码生成工具
Charl Linssen,Pooja N Babu,Jochen M Eppler et al.
Charl Linssen et al.
With increasing model complexity, models are typically re-used and evolved rather than starting from scratch. There is also a growing challenge in ensuring that these models can seamlessly work across various simulation backends and hardwar...
Modeling of whole brain sleep electroencephalogram using deep oscillatory neural network [0.03%]
基于深度振荡神经网络的全脑睡眠电生理建模研究
Sayan Ghosh,Dipayan Biswas,N R Rohan et al.
Sayan Ghosh et al.
This study presents a general trainable network of Hopf oscillators to model high-dimensional electroencephalogram (EEG) signals across different sleep stages. The proposed architecture consists of two main components: a layer of interconne...
Net2Brain: a toolbox to compare artificial vision models with human brain responses [0.03%]
Net2Brain：比较人工视觉模型与人类大脑反应的工具箱
Domenic Bersch,Martina G Vilas,Sari Saba-Sadiya et al.
Domenic Bersch et al.
In cognitive neuroscience, the integration of deep neural networks (DNNs) with traditional neuroscientific analyses has significantly advanced our understanding of both biological neural processes and the functioning of DNNs. However, chall...
Radiomics-driven neuro-fuzzy framework for rule generation to enhance explainability in MRI-based brain tumor segmentation [0.03%]
基于影像组学的神经模糊框架在脑肿瘤分割中的规则生成及可解释性研究
Leondry Mayeta-Revilla,Eduardo P Cavieres,Matías Salinas et al.
Leondry Mayeta-Revilla et al.
Introduction: Brain tumors are a leading cause of mortality worldwide, with early and accurate diagnosis being essential for effective treatment. Although Deep Learning (DL) models offer strong performance in tumor detect...
Large-scale EM data reveals myelinated axonal changes and altered connectivity in the corpus callosum of an autism mouse model [0.03%]
大规模电磁数据揭示了自闭症小鼠模型胼胝体髓鞘轴突的变化及连接组的改变
Guoqiang Zhao,Ao Cheng,Jiahao Shi et al.
Guoqiang Zhao et al.
Introduction: Autism spectrum disorder (ASD) encompasses a diverse range of neurodevelopmental disorders with complex etiologies, including genetic, environmental, and neuroanatomical factors. While the exact mechanisms u...
Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning [0.03%]
基于扩展的LSR感应迁移学习的MI-EEG信号识别
Zhibin Jiang,Keli Hu,Jia Qu et al.
Zhibin Jiang et al.
Introduction: Motor imagery electroencephalographic (MI-EEG) signal recognition is used in various brain-computer interface (BCI) systems. In most existing BCI systems, this identification relies on classification algorit...
The quest to share data [0.03%]
分享数据的尝试
Arthur W Toga,Sidney Taiko Sheehan,Tyler Ard
Arthur W Toga
Data sharing in scientific research is widely acknowledged as crucial for accelerating progress and innovation. Mandates from funders, such as the NIH's updated Data Sharing Policy, have been beneficial in promoting data sharing. However, t...
Developing a multiscale neural connectivity knowledgebase of the autonomic nervous system [0.03%]
自主神经系统多尺度神经连接知识库的构建
Fahim T Imam,Thomas H Gillespie,Ilias Ziogas et al.
Fahim T Imam et al.
The Stimulating Peripheral Activity to Relieve Conditions (SPARC) program is a U.S. National Institutes of Health (NIH) funded effort to enhance our understanding of the neural circuitry responsible for visceral control. SPARC's mission is ...
Eberechi Wogu,George Ogoh,Patrick Filima et al.
Eberechi Wogu et al.
Introduction: The effectiveness of research and innovation often relies on the diversity or heterogeneity of datasets that are Findable, Accessible, Interoperable and Reusable (FAIR). However, the global landscape of brai...