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

Elaborative Rehearsals01:07

Elaborative Rehearsals

77
Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...
77
The Replisome03:01

The Replisome

6.1K
6.1K
Reinforcement01:23

Reinforcement

177
Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
177
Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

139
Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
139
Exon Recombination02:32

Exon Recombination

3.5K
The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
Exon shuffling follows “splice frame rules.” Each exon...
3.5K
Introduction to Nuclear Reprogramming01:14

Introduction to Nuclear Reprogramming

1.9K
Nuclear reprogramming is the process of switching gene expression of one cell type to that of another cell type, usually from a differentiated cell state to an undifferentiated cell state. Differentiation occurs during processes such as development and morphogenesis, tissue regeneration, and malignancy. Cells can also be artificially induced to reprogram their gene expression by techniques such as nuclear transfer, induced pluripotency, and cell fusion. Such techniques have many applications in...
1.9K

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

Neural signatures of model-based and model-free reinforcement learning across prefrontal cortex and striatum.

eLife·2026
Same author

Octopamine and tyramine dynamics predict learning rate phenotypes during associative conditioning in honey bees.

Science advances·2026
Same author

Composing egocentric and allocentric maps for flexible navigation.

PLoS computational biology·2026
Same author

Infinite hidden Markov models can dissect the complexities of learning.

Nature neuroscience·2025
Same author

Individual differences in tail risk sensitive exploration using Bayes-adaptive Markov decision processes.

eLife·2025
Same author

A computational approach to understanding effort-based decision-making in depression.

Psychological medicine·2025
Same journal

Plasmonic nanocomposite helices for weather-adaptive LiDAR function.

Nature communications·2026
Same journal

Multidirectional strain-insensitive stretchable RF electronics.

Nature communications·2026
Same journal

In-scanner thoughts contribute to resting-state functional connectivity.

Nature communications·2026
Same journal

Metal-center electron affinity modulates multicolor electrochromism in 2D conjugated metal-organic frameworks.

Nature communications·2026
Same journal

Hyperbranched dielectric polymer networks exhibiting giant energy storage density at 250 °C.

Nature communications·2026
Same journal

3D nanoprinting of metals by spatiotemporally confined hot electrons via multiple-electron excitations in nanocrystals.

Nature communications·2026
查看所有相关文章

相关实验视频

Updated: May 27, 2025

Hybrid Microdrive System with Recoverable Opto-Silicon Probe and Tetrode for Dual-Site High Density Recording in Freely Moving Mice
08:57

Hybrid Microdrive System with Recoverable Opto-Silicon Probe and Tetrode for Dual-Site High Density Recording in Freely Moving Mice

Published on: August 10, 2019

11.0K

探索重复播放的探索

Georgy Antonov1,2, Peter Dayan3,4

  • 1Max Planck Institute for Biological Cybernetics, Tübingen, Germany. georgy.antonov@tuebingen.mpg.de.

Nature communications
|February 15, 2025
PubMed
概括
此摘要是机器生成的。

这项研究模拟了动物如何探索未知的环境. 它提出,在休息期间重复体验有助于规划未来的探索,提供新的实验方向.

更多相关视频

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
05:19

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

7.0K

相关实验视频

Last Updated: May 27, 2025

Hybrid Microdrive System with Recoverable Opto-Silicon Probe and Tetrode for Dual-Site High Density Recording in Freely Moving Mice
08:57

Hybrid Microdrive System with Recoverable Opto-Silicon Probe and Tetrode for Dual-Site High Density Recording in Freely Moving Mice

Published on: August 10, 2019

11.0K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
05:19

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

7.0K

科学领域:

  • 神经科学是一个神经科学.
  • 强化学习是一种强化学习.
  • 计算生物学 计算生物学

背景情况:

  • 动物需要探索,以应对环境的不确定性.
  • 探索性选择背后的大脑机制仍然不太清楚.
  • 现有的离线处理模型 (例如,海马体重复) 仅限于已知的环境.

研究的目的:

  • 扩展现有的海马体重复的理论.
  • 调查重播在不确定性下大约最佳探索中的作用.
  • 为探索性重复模式推导可测试的预测.

主要方法:

  • 一个有影响力的海马重播理论的延伸.
  • 开发用于空间导航任务的计算模型.
  • 为线下序列重播推导预测.

主要成果:

  • 该模型提供了对探索性重复现有数据的规范性解释.
  • 这项研究强调了序列重复对探索的重要性.
  • 为探索性重复模式生成了可测试的预测.

结论:

  • 离线重播,特别是序列重播,对于在不确定的环境中进行有效的探索至关重要.
  • 这些发现为理解学习和行为过程中的探索性决策提供了一个框架.
  • 这项研究为研究离线处理的新实验范式开辟了道路.