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

Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

2.7K
The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor...
2.7K
Somatosensory, Motor, and Association Cortex01:24

Somatosensory, Motor, and Association Cortex

345
The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at...
345

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

Map of spiking activity underlying change detection in the mouse visual system.

Cell·2026
Same author

Multimodal characterization of variation in neuronal types in the mouse basal ganglia.

bioRxiv : the preprint server for biology·2026
Same author

Connecting single-cell transcriptomes to projectomes in the mouse visual cortex.

Nature·2026
Same author

Conserved Cell Type Signatures Across the Brainstem and Spinal Cord in the Mouse Central Nervous System.

bioRxiv : the preprint server for biology·2026
Same author

Learning using switching synaptic plasticity rules.

bioRxiv : the preprint server for biology·2026
Same author

Brain-wide topographic coordination of rotating waves.

Science (New York, N.Y.)·2026

相关实验视频

Updated: May 20, 2025

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

4.5K

整合多模式数据以了解皮质电路架构和功能.

Anton Arkhipov1, Nuno da Costa2, Saskia de Vries3

  • 1Allen Institute, Seattle, WA, USA. antona@alleninstitute.org.

Nature neuroscience
|March 25, 2025
PubMed
概括

新技术使得神经系统的详细研究成为可能. 整合多式联络数据,特别是在小鼠视觉皮层中,有助于我们更好地理解大脑的结构和功能.

更多相关视频

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

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

Published on: June 30, 2018

11.6K

相关实验视频

Last Updated: May 20, 2025

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

4.5K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

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

Published on: June 30, 2018

11.6K

科学领域:

  • 神经科学是一个神经科学.
  • 系统神经科学 系统神经科学
  • 计算神经科学是一种神经科学.

背景情况:

  • 神经技术的快速发展促进了对神经系统的大规模,高度详细的研究.
  • 越来越多的趋势涉及组合不同的技术,以建立不同数据模式之间的直接联系.

研究的目的:

  • 审查将多式联络数据整合到小鼠视觉皮层中的方法.
  • 突出计算和理论在分析和建模神经科学数据中的作用.

主要方法:

  • 对整合皮质细胞类型,连接性 (区域,细胞类型和单细胞水平) 和体内神经活动数据的技术的审查.
  • 强调对数据分析和建模的计算和理论贡献.

主要成果:

  • 鼠标视觉皮层作为多式联络数据集成的关键模型系统.
  • 整合各种数据类型对于推进对神经系统的理解至关重要.

结论:

  • 综合性方法,加上开放数据和工具共享,对于现代神经科学至关重要.
  • 这些方法提高了对大脑结构,机制和功能的理解.