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

Cerebrum: Anatomical Overview II01:11

Cerebrum: Anatomical Overview II

Each cerebral hemisphere can be divided into three main regions. The outermost region, the cerebral cortex, is a thin layer (2 to 4 millimeters thick) made up of gray matter, consisting of neuron cell bodies, dendrites, glial cells, and blood vessels. The middle region, or white matter, is primarily composed of myelinated nerve fibers organized into three types of large tracts: association fibers, commissures, and projection fibers. Association fibers connect different areas within the same...
Functional Brain Systems: Reticular Formation01:13

Functional Brain Systems: Reticular Formation

The reticular formation is a complex network of gray and white matter located within the brainstem extending from the medulla to the midbrain.
Within the reticular formation, there are several distinct nuclei that can be classified into three broad categories. The Raphe nuclei are located along the midline of the brainstem. They are primarily known for their role in synthesizing and releasing serotonin, a neurotransmitter involved in regulating mood, appetite, sleep, and circadian rhythms. The...
Organization of the Brain01:30

Organization of the Brain

The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...
Cerebral Hemispheres01:05

Cerebral Hemispheres

The human brain, a complex organ, is functionally divided into two cerebral hemispheres—left and right. These hemispheres are interconnected by a structure of paramount importance, the corpus callosum. This substantial bundle of neural fibers is not just a bridge between the hemispheres but a crucial element for the brain's comprehensive functioning. It enables efficient communication between the two hemispheres, allowing each side of the brain to control and receive sensory and motor...

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

HARMONY: A large-scale harmonized neuroimaging dataset for research on anxious misery disorders.

bioRxiv : the preprint server for biology·2026
Same author

Challenges and opportunities of gap score methods for studying psychopathology resilience and vulnerability.

medRxiv : the preprint server for health sciences·2026
Same author

Modelling discrete states and long-term dynamics in functional brain networks.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

KMO deletion preserves non-associative learning and SVZ neurogenesis in aging mice.

Behavioural brain research·2026
Same author

Canonical Hidden Markov Model Networks for studying M/EEG.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Effects of Age on Resting-State Cortical Networks.

Human brain mapping·2026

相关实验视频

Updated: May 12, 2026

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.7K

功能性大脑连接的多尺度模式

S Rezvan Farahibozorg1, Samuel J Harrison1, Janine D Bijsterbosch2

  • 1FMRIB, Oxford Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neuroscience, Oxford University, Oxford, United Kingdom.

Imaging neuroscience (Cambridge, Mass.)
|December 15, 2025
PubMed
概括

我们介绍了多尺度概率函数模式 (mPFMs),这是一种新的大脑绘图技术. mPFM能够更好地估计多个尺度的功能性大脑连接,从而从fMRI数据中更好地预测个性化的特征.

关键词:
这是一个很好的香水.大数据就是大数据.个体特定的建模.多尺度模式多尺度模式静止状态的fMRI进行.预测特征 预测特征

更多相关视频

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.6K
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

5.7K

相关实验视频

Last Updated: May 12, 2026

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.7K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.6K
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

5.7K

科学领域:

  • 神经科学是一个神经科学.
  • 计算生物学 计算生物学
  • 医疗成像医学成像

背景情况:

  • 大脑信息处理涉及在多个尺度上运行的局部化和分布式系统.
  • 当前的功能性大脑连接方法往往错过了跨度相互作用.
  • 现有的方法使用有限的模式或分片,未能捕捉多个规模的动态.

研究的目的:

  • 为全面的功能性大脑连接分析引入多尺度概率函数模式 (mPFMs).
  • 为了使功能连接在脑组织的不同尺度内和跨越不同尺度的直接估计.
  • 为个性化特征和疾病开发增强的功能性MRI (fMRI) 生物标志物.

主要方法:

  • 数据驱动的多层贝叶斯模型应用于大型功能性MRI (fMRI) 群体和个人数据.
  • 开发一种新型映射 (mPFMs),包括各种粒度尺度上的模式.
  • 使用模拟和真实英国生物库数据进行验证.

主要成果:

  • 从数据中出现了mPFM,捕捉了分布式大脑模式及其子组件.
  • 新的映射可以直接估计内部和跨规模的功能连接.
  • 与标准技术相比,mPFMs在预测来自英国生物库数据的约900个个性化的特征方面取得了更高的准确性.

结论:

  • mPFMs为功能连接建模提供了一个新的框架,将信息整合到多个大脑尺度中.
  • 这种方法提供了对大脑功能及其与个体特征的关系的更全面的理解.
  • mPFM可以产生增强的fMRI生物标志物,用于预测特征和潜在地识别疾病.