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

Visual System01:26

Visual System

565
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
565
Vision01:24

Vision

53.1K
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.
53.1K
Parallel Processing01:20

Parallel Processing

150
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
150
Association Areas of the Cortex01:21

Association Areas of the Cortex

5.2K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
5.2K

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

Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding.

eLife·2026
Same author

Dynamics of striatal action selection and reinforcement learning.

eLife·2025
Same author

Selective consolidation of learning and memory via recall-gated plasticity.

eLife·2024
Same author

Dynamics of striatal action selection and reinforcement learning.

bioRxiv : the preprint server for biology·2024
Same author

The connectome of the adult Drosophila mushroom body provides insights into function.

eLife·2020
Same author

Neural dynamics at successive stages of the ventral visual stream are consistent with hierarchical error signals.

eLife·2018

相关实验视频

Updated: Jun 21, 2025

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
07:08

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

8.3K

灵长类动物视觉系统和深度神经网络中的因子化视觉表示.

Jack W Lindsey1,2, Elias B Issa1,2

  • 1Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States.

eLife
|July 5, 2024
PubMed
概括

分因,即场景信息的分离,是灵长类视觉系统和深度神经网络 (DNN) 的关键原则. 这一策略通过有效地组织视觉数据来增强对象识别.

科学领域:

  • 神经科学是一个神经科学.
  • 计算机视觉 计算机视觉
  • 计算神经科学是一种神经科学.

背景情况:

  • 对象分类是灵长类动物腹部视觉流的主要功能.
  • 深度神经网络 (DNN) 模型被优化为视觉系统分类,但可能会丢弃或纠其他场景信息.
  • 了解视觉区域如何代表物体身份之外的各种信息至关重要.

研究的目的:

  • 研究因子化作为生物视觉表征中的规范原则.
  • 为了确定场景参数的因子化是否能改善对象身份解码.
  • 分析DNN中的因子分解,并将其与神经和行为数据进行比较.

主要方法:

  • 在子腹视觉层次结构中,从对象身份中检查了对象姿势和背景的因子化.
  • 评估了因数分解对对象身份解码性能的贡献.
  • 在DNN模型库中分析了场景参数 (照明,背景,视角,姿势) 的分解.
  • 将DNN性能与12个数据集中的人类和子的神经,fMRI和行为数据进行比较.

主要成果:

  • 对象姿势和背景的因子化从身份增加在子更高的视觉区域.
  • 增加的因子化显著改善了生物视觉中的对象身份解码.
关键词:
深度神经网络是一个神经网络.功能磁力共振成像 (fMRI) 是一种人类 人类 人类 人类 人类 人类 人类神经生理学神经生理学神经科学 神经科学对象识别对象识别器rhesus 子 子 子 子 子视觉皮层 视觉皮层 视觉皮层视觉场景 视觉场景 视觉场景

更多相关视频

The Gateway to the Brain: Dissecting the Primate Eye
07:37

The Gateway to the Brain: Dissecting the Primate Eye

Published on: May 27, 2009

14.1K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

相关实验视频

Last Updated: Jun 21, 2025

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
07:08

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

8.3K
The Gateway to the Brain: Dissecting the Primate Eye
07:37

The Gateway to the Brain: Dissecting the Primate Eye

Published on: May 27, 2009

14.1K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K
  • 最好匹配神经和行为数据的DNN模型表现出更强的场景参数因子化.
  • 与场景参数的不变性与相应的生物数据相比,与因子化相比,与相应的生物数据的相关性不太一致.
  • 结论:

    • 分因式是生物视觉表征中的规范原则.
    • 视觉场景信息的因子化是大脑和DNN中普遍存在的策略.
    • 在因子化子空间中保持非类信息通常比抛弃它 (不变性) 更好.