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相关概念视频

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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相关实验视频

Updated: May 2, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

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任务唤起的脑网络动态,是使用源本地化EEG和机器学习进行认知控制的基础.

Alfia Parvez1, Shreya Verma1, Jonathan Cerna2

  • 1Department of Health and Kinesiology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
|February 28, 2026
PubMed
概括
此摘要是机器生成的。

这项研究揭示了在认知任务期间大脑网络连接的变化. 年龄和BMI影响这些变化,影响认知控制性能.

关键词:
大脑网络 大脑网络认知控制 认知控制在EEG源的定位.功能连接性的功能连接性.肥胖和大脑功能的关系与任务相关的大脑激活

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Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping
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科学领域:

  • 神经科学是一个神经科学.
  • 认知神经科学 认知神经科学
  • 大脑连接性研究 研究大脑连接性研究

背景情况:

  • 功能连接 (FC) 对于认知任务至关重要.
  • 人口统计学和健康对动态FC在任务中的影响尚不清楚.
  • 调查了七个核心大脑网络:默认模式 (DMN),腹部注意力 (VAN),体力运动 (SMN),背部注意力 (DAN),前端对面 (FPN),视觉 (VIN) 和边缘 (LIN).

研究的目的:

  • 在修改的埃里克森侧翼任务中识别与认知控制需求相关的网络配置.
  • 评估人口 (年龄,性别,收入) 和健康 (BMI) 因素如何影响与任务相关的动态FC.
  • 了解高性能个体的动态FC模式和反应时间 (RT) 之间的关系.

主要方法:

  • 对来自255名成年人的来源局部化EEG数据的二次分析.
  • 隐藏的马尔科夫模型 (HMM) 用于提取时空动态和量化网络相关性.
  • 极端梯度提升 (XGBoost) 和递归特征消除,以确定RT的预测FC特征.
  • 回归模型用于评估年龄,性别,BMI和收入对任务相关FC的影响.

主要成果:

  • 机器学习模型准确地预测了对一致 (AUC=0.81) 和不一致 (AUC=0.86) 试验的RT.
  • 特定的FC模式 (例如VAN-LIN,VIN-VAN,SMN-DAN) 是对一致性试验的关键,而其他模式 (例如SMN-DMN,LIN-FPN,VIN-DAN) 是对不一致性试验的关键.
  • 增加的年龄与减少的FC相关;较高的BMI显示在特定网络 (LIN-FPN,VIN-DAN) 中与FC存在适度的积极关联. 性别和收入并不是重要的预测因素.

结论:

  • 大脑网络内部和大脑网络之间的动态相互作用对于认知控制至关重要.
  • 年龄和BMI是影响认知任务期间大脑连接的重要人口和健康因素.
  • 未来的研究应该在检查基于任务的功能连接时考虑这些因素.