Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Rail-BEV: A LiDAR-Centric and Sensor-Aware BEV Perception Framework for Long-Range Railway Obstacle Detection.

Sensors (Basel, Switzerland)·2026
Same author

Privacy-Preserving Federated Deep Learning for Robust Anomaly Detection in Distributed Security Sensing Systems.

Sensors (Basel, Switzerland)·2026
Same author

Gain-of-function mutation in the sensor kinase CpxS modulates the antimicrobial resistance and virulence of Pseudomonas aeruginosa.

International journal of medical microbiology : IJMM·2026
Same author

Multi-omic analysis of deep learning-derived phenotypes links ophthalmic imaging to cardiovascular and neurological traits.

Nature cardiovascular research·2026
Same author

Nasal Instillation of Complex Metal Oxide Particles Induces Brain Metal Accumulation and Neurobehavioral Toxicity in Mice.

Environmental science & technology·2026
Same author

What makes a lonely child: environmental, health, and multimodal neuroimaging correlates of prospective loneliness in the ABCD study.

Journal of child psychology and psychiatry, and allied disciplines·2026
Same journal

Enhancing Alzheimer's Diagnosis: Leveraging Anatomical Landmarks in Graph Convolutional Neural Networks on Tetrahedral Meshes.

Information processing in medical imaging : proceedings of the ... conference·2026
Same journal

Cycle-Consistent Zero-Shot Through-Plane Super-Resolution for Anisotropic Head MRI.

Information processing in medical imaging : proceedings of the ... conference·2026
Same journal

Brightness-Invariant Tracking Estimation in Tagged MRI.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

Using Multiple Instance Learning to Build Multimodal Representations.

Information processing in medical imaging : proceedings of the ... conference·2025
Same journal

mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds.

Information processing in medical imaging : proceedings of the ... conference·2024
查看所有相关文章

相关实验视频

Updated: Jul 6, 2026

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.2K

异质图形卷积神经网络通过霍奇-拉普拉西安对大脑功能数据的功能数据.

Jinghan Huang1, Moo K Chung2, Anqi Qiu1,3,4,5,6

  • 1Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.

Information processing in medical imaging : proceedings of the ... conference
|May 22, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的异质图卷积神经网络 (HGCNN),用于分析大脑fMRI数据. 通过学习有意义的功能连接特征,HGCNN有效地预测通用智能,优于现有的图形神经网络方法.

更多相关视频

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.7K

相关实验视频

Last Updated: Jul 6, 2026

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.2K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.7K

科学领域:

  • 神经科学是一个神经科学.
  • 机器学习 机器学习
  • 图形神经网络的神经网络

背景情况:

  • 使用fMRI数据进行功能性大脑连接分析是复杂的.
  • 现有的图形神经网络 (GNN) 在处理异构的大脑数据方面面临着挑战.
  • 从大脑活动中准确预测认知能力,如一般智力,仍然是一个挑战.

研究的目的:

  • 为分析大脑fMRI数据提出一种新的异质图卷积神经网络 (HGCNN).
  • 引入使用k-th Hodge-Laplacian (HL) 运算符和拓图形聚合 (TGPool) 方法的光谱过器的通用配方.
  • 评估HL-节点,HL-边缘和HL-HGCNN模型在从fMRI数据中预测一般智能的性能.

主要方法:

  • 开发了一种新的异质图卷积神经网络 (HGCNN),利用k-th Hodge-Laplacian (HL) 运算符进行光谱过.
  • 引入了拓图形聚合 (TGPool) 方法,适用于任何维度的简单图形.
  • 设计并实施了HL-node,HL-edge和HL-HGCNN架构,用于在节点,边缘和组合级别学习信号表示.
  • 利用了青少年大脑认知发展 (ABCD) 研究 (n=7693) 的fMRI数据来预测一般智力.

主要成果:

  • 与HL节点网络相比,HL边缘网络在使用功能性大脑连接作为特征时表现出更高的性能.
  • 拟议的HL-HGCNN显著超过了最先进的GNN,包括GAT,BrainGNN,dGCN,BrainNetCNN和Hypergraph NN.
  • 由HL-HGCNN提取的功能连接特征被发现对解释与一般智能相关的神经回路具有意义.

结论:

  • 新的HGCNN框架,包括HL光谱过器和TGPool,为分析复杂的大脑fMRI数据提供了一种有效的方法.
  • HL-HGCNN模型显示了预测认知能力和理解底层神经机制的巨大潜力.
  • 在边缘层面考虑功能性大脑连接,可以增强基于图形的神经网络的智能预测预测能力.