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

53.5K
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.
53.5K
Visual System01:26

Visual System

588
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...
588
Neural Circuits01:25

Neural Circuits

1.3K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.3K
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

3.9K
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 cortex....
3.9K

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

Investigating the mechanisms underlying saccade generation in the frontal eye fields using multisite microstimulation.

Journal of neurophysiology·2026
Same author

State-switching navigation strategies in <i>Caenorhabditis elegans</i> are beneficial for chemotaxis.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Brain-wide arousal signals are segregated from movement planning in the superior colliculus of the macaque.

eLife·2026
Same author

Interactions across hemispheres in prefrontal cortex reflect global cognitive processing.

Nature communications·2026
Same author

Linking reaction time variability to physiological markers of arousal across timescales.

bioRxiv : the preprint server for biology·2026
Same author

From Breath to Behavior: Respiratory Features Predict Visual Detection Performance.

bioRxiv : the preprint server for biology·2026
Same journal

A human-specific genetic modifier reconfigures large-scale cortical network dynamics underlying behavioral performance.

bioRxiv : the preprint server for biology·2026
Same journal

<i>Staphylococcus aureus</i> uses a eukaryotic-like uridyltransferase to make UDP-GlcNAc for cell wall synthesis.

bioRxiv : the preprint server for biology·2026
Same journal

Dynamic redistribution of eIF4F controls cap-dependent translation initiation.

bioRxiv : the preprint server for biology·2026
Same journal

When does additional information improve accuracy of RNA secondary structure prediction?

bioRxiv : the preprint server for biology·2026
Same journal

Normative brain-state trajectories reveal deviation from healthy aging in Alzheimer's disease.

bioRxiv : the preprint server for biology·2026
Same journal

Noradrenergic infraslow rhythm during sleep is the critical link between heart-rate dynamics and memory consolidation.

bioRxiv : the preprint server for biology·2026
查看所有相关文章

相关实验视频

Updated: Jul 9, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

559

视觉皮层的紧型深度神经网络模型.

Benjamin R Cowley1,2, Patricia L Stan3,4,5, Jonathan W Pillow2

  • 1Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.

bioRxiv : the preprint server for biology
|December 4, 2023
PubMed
概括
此摘要是机器生成的。

研究人员开发了紧型深度神经网络 (DNN) 模型来解释视觉皮层计算. 这些较小的模型准确地预测神经反应,为V4神经元如何处理视觉信息提供了洞察力.

科学领域:

  • 计算神经科学是一种神经科学.
  • 系统神经科学 系统神经科学

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

相关实验视频

Last Updated: Jul 9, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

559
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K
  • 计算机视觉 计算机视觉
  • 背景情况:

    • 了解视觉皮层计算对神经科学至关重要.
    • 深度神经网络 (DNN) 模型擅长预测神经反应,但由于数百万个参数,缺乏可解释性.
    • 当前的DNN模型可能不必要地复杂,无法解释神经处理.

    结论:

    • 计算神经科学中的DNN模型可以在不牺牲准确性的情况下显著缩小尺寸.
    • 这种方法产生了可解释的,高精度的模型,用于理解视觉皮层神经元.
    • 这些发现为开发可解释的大脑功能模型提供了新的方向.