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

Storage01:23

Storage

134
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
134
Somatosensation01:33

Somatosensation

38.5K
The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
38.5K
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

4.6K
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....
4.6K

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

Strong strain dependence of friction in graphene kirigami allows engineering a negative coefficient of friction.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

An Extended Energy-Biased Aggregation-Volume-Bias Monte Carlo (EB-AVBMC) Method for Nucleation Simulation of a Reactive Water Potential.

Journal of chemical theory and computation·2025
Same author

Hexagons all the way down: grid cells as a conformal isometric map of space.

PLoS computational biology·2025
Same author

Genetic Algorithm Workflow for Parameterization of a Water Model Using the Vashishta Force Field.

The journal of physical chemistry. B·2025
Same author

Inferring causal connectivity from pairwise recordings and optogenetics.

PLoS computational biology·2023
Same author

Optogenetic pacing of medial septum parvalbumin-positive cells disrupts temporal but not spatial firing in grid cells.

Science advances·2021
Same journal

Restraint of melanoma progression by cells in the local skin environment.

eLife·2026
Same journal

Brawn before bite in endemic Asian eutherian mammals after the end-Cretaceous extinction.

eLife·2026
Same journal

Experimental evolution to thermal stress indicates climate resilience in a cosmopolitan arthropod.

eLife·2026
Same journal

Correlates of protection against African swine fever virus identified by a systems immunology approach.

eLife·2026
Same journal

Retrosplenial cortex enables context-dependent goal-directed sensorimotor transformation.

eLife·2026
Same journal

Direct contact between iPSC-derived macrophages and hepatocytes drives reciprocal acquisition of Kupffer cell identity and hepatocyte maturation.

eLife·2026
查看所有相关文章

相关实验视频

Updated: Sep 13, 2025

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus
09:59

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus

Published on: October 11, 2017

12.8K

通过解码认知地图来学习位置细胞和重新绘制地图.

Markus Borud Pettersen1,2, Vemund Schøyen2, Anders Malthe-Sørenssen3

  • 1Simula Research Laboratory, Oslo, Norway.

eLife
|July 28, 2025
PubMed
概括
此摘要是机器生成的。

这项研究模拟了海马的位置细胞,展示了神经网络如何学习空间表示和重绘,可能解释了在导航过程中与边界和网格细胞的相互作用.

关键词:
人工智能的人工智能是人工智能.边境细胞边境细胞机器学习是机器学习.神经科学 神经科学没有,没有,没有.位置细胞 细胞 位置细胞经常性的神经网络.空间导航空间导航

更多相关视频

Utilizing a Reconfigurable Maze System to Enhance the Reproducibility of Spatial Navigation Tests in Rodents
04:41

Utilizing a Reconfigurable Maze System to Enhance the Reproducibility of Spatial Navigation Tests in Rodents

Published on: December 2, 2022

2.9K
Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.2K

相关实验视频

Last Updated: Sep 13, 2025

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus
09:59

Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus

Published on: October 11, 2017

12.8K
Utilizing a Reconfigurable Maze System to Enhance the Reproducibility of Spatial Navigation Tests in Rodents
04:41

Utilizing a Reconfigurable Maze System to Enhance the Reproducibility of Spatial Navigation Tests in Rodents

Published on: December 2, 2022

2.9K
Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.2K

科学领域:

  • 神经科学是一个神经科学.
  • 计算神经科学是一种神经科学.
  • 认知科学 认知科学

背景情况:

  • 海马的位置细胞编码位置并形成认知地图.
  • 当环境发生变化时,位置单元格会显示重新映射 (速度变化).
  • 位置,边界和网格细胞之间的相互作用仍然不清楚.

研究的目的:

  • 开发一个规范计算模型的位置细胞功能和重新映射.
  • 研究神经网络如何学习空间表示和执行路径集成.
  • 探索不同类型的空间调节神经元之间的相互作用的潜在机制.

主要方法:

  • 开发了一个神经网络模型用于位置重建和路径集成.
  • 使用一种无法训练的解码方案,从网络输出中估计位置.
  • 该模型在多个模拟环境中训练,以观察重新映射现象.

主要成果:

  • 网络输出单元开发了类似于地点的空间表示.
  • 上游经常性单位变得边界调整.
  • 类似位置的单位展示了与生物细胞相似的全球,几何和速率重新映射.
  • 位置单位中心显示了六角格子集群,在小鼠数据中的初步证据.
  • 重制地图的支持是上游单位的利率变化.

结论:

  • 该模型为理解位置细胞场形成和重新绘制提供了一个规范框架.
  • 这些发现表明,地方,边界和网格细胞之间相互作用的潜在机制.
  • 这项工作为基础空间认知的计算原理提供了新的见解.