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

Vision01:24

Vision

59.3K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
59.3K

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

Impact of 1-month dual antiplatelet therapy after treatment with drug-coated balloon for femoropopliteal artery disease.

Heart and vessels·2026
Same author

The Prognostic Value of Circulating Tumor DNA for Clinical Outcomes in Patients Undergoing Hematopoietic Cell Transplantation: A Systematic Review and Meta-Analysis.

International journal of molecular sciences·2026
Same author

Gastrointestinal bypass surgery for non-strangulated adhesive small bowel obstruction.

Surgery today·2026
Same author

Response to letter: 'Interpreting educational inequalities in site-specific cancer mortality: statistical significance versus public health relevance'.

Journal of epidemiology and community health·2026
Same author

Megacolon Associated with Multiple Endocrine Neoplasia Type 2B: A Case Successfully Managed with Ileostomy.

Surgical case reports·2026
Same author

Trends in Female Breast Cancer Incidence among Japanese, Korean, and US Populations: An Age-Period-Cohort Analysis.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026

相关实验视频

Updated: Jan 11, 2026

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex
08:42

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

Published on: February 8, 2020

11.2K

在小鼠视觉皮层中的信息理论梯度流.

Erik D Fagerholm1, Hirokazu Tanaka2, Milan Brázdil1

  • 1First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czechia.

Frontiers in neuroinformatics
|November 17, 2025
PubMed
概括
此摘要是机器生成的。

研究人员开发了一个新的数学框架来分析神经活动如何在大脑区域之间转化. 这种方法通过测量和预期的变化来量化信息流,提供对大脑组织的见解.

关键词:
的成像成像技术可以帮助我们.进入的过程中,预期 期望 期待 预期梯度流动流动的梯度流动.信息几何学信息几何学神经连接的神经连接.两个光子的两个光子.

更多相关视频

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis
08:57

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

Published on: July 8, 2025

1.1K
Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus
10:43

Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus

Published on: April 21, 2023

4.3K

相关实验视频

Last Updated: Jan 11, 2026

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex
08:42

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

Published on: February 8, 2020

11.2K
En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis
08:57

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

Published on: July 8, 2025

1.1K
Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus
10:43

Author Spotlight: Unveiling Neural Coding and Mechanisms of Visual Processing in the Superior Colliculus

Published on: April 21, 2023

4.3K

科学领域:

  • 计算神经科学是一种计算神经科学.
  • 信息理论是信息理论.
  • 神经成像分析分析神经成像分析

背景情况:

  • 神经活动的特点是不断演变的概率分布.
  • 了解这些分布在皮层区域之间的转换对于破译大脑信息处理至关重要.

研究的目的:

  • 开发一个数学框架来量化神经信号转换.
  • 通过信息理论概念来解释这些转换.

主要方法:

  • 开发了信息理论梯度流来模型神经概率分布变化.
  • 将框架应用于来自小鼠视觉皮层的成像数据.
  • 验证了框架的有效性 *in silico*.

主要成果:

  • 在小鼠中确定了面向侧面区域和初级视觉皮层之间的一致的双向信息流.
  • 证明了和预期贡献可以明确地描述信息流.
  • 展示了框架分析神经概率分布动态的能力.

结论:

  • 引入了一个可通用的框架来分解神经信号转换.
  • 该方法提供可解释的信息理论组件,用于分析皮质通信.
  • 适用于各种神经成像模式和尺度,以理解信息几何.