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

Associative Learning01:27

Associative Learning

276
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
276
Cognitive Learning01:21

Cognitive Learning

144
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
144
Neural Circuits01:25

Neural Circuits

974
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...
974
Improving Translational Accuracy02:07

Improving Translational Accuracy

8.5K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
8.5K
Information Processing Approach01:30

Information Processing Approach

28
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
28
Purposive Learning01:22

Purposive Learning

96
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
96

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

Rapid Epidemiological Data Collection on Social Media for COVID-19: Comparative Study Between Online Surveys and Conventional Cohorts.

Journal of medical Internet research·2026
Same author

Impaired visuospatial working memory but preserved attentional control in bipolar disorder.

Psychological medicine·2025
Same author

Continuous dynamics of cooperation and competition in social decision-making.

Communications psychology·2025
Same author

Testing paradox may explain increased observed prevalence of bacterial STIs among MSM on HIV PrEP: A modeling study.

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

Inferring effective networks of spiking neurons using a continuous-time estimator of transfer entropy.

PLoS computational biology·2025
Same author

Higher-order interactions in neuronal function: From genes to ionic currents in biophysical models.

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

相关实验视频

Updated: May 24, 2025

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

一个基于局部信息理论目标函数的可解释神经学习的一般框架.

Abdullah Makkeh1,2, Marcel Graetz1,3, Andreas C Schneider2,4,5

  • 1Department of Data-driven Analysis of Biological Networks, Göttingen Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen 37077, Germany.

Proceedings of the National Academy of Sciences of the United States of America
|March 5, 2025
PubMed
概括
此摘要是机器生成的。

研究人员通过从部分信息分解 (PID) 导出局部学习规则来开发"信息形态"神经网络. 这些网络提供了一种可解释的方法来理解局部神经元动力学如何推动网络层面的学习和任务执行.

关键词:
信息理论信息理论当地学习学习 当地学习神经网络的神经网络的神经网络部分信息的分解分解.

更多相关视频

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.8K
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

451

相关实验视频

Last Updated: May 24, 2025

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
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.8K
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

451

科学领域:

  • 计算神经科学是一种神经科学.
  • 人工智能的人工智能
  • 信息理论 信息理论

背景情况:

  • 了解生物和人工网络中的本地学习动态是一项挑战.
  • 现有的方法缺乏一个一般的,可解释的和适应的框架,以满足当地的学习目标.

研究的目的:

  • 根据部分信息分解 (PID) 来推导一个参数局部学习规则.
  • 介绍和展示新型"信息形态"神经网络的功能.

主要方法:

  • 制定了对分区模型神经元的局部信息处理目标.
  • 使用部分信息分解 (PID) 的进步推导出了本地学习规则.
  • 在各种学习任务中引入并测试了"信息形态"神经网络.

主要成果:

  • 成功推导出一个参数局部学习规则.
  • 在监督,无监督和记忆学习任务中展示了信息形态网络的多功能性.
  • 展示了PID框架用于分析本地学习的可解释性.

结论:

  • 信息形神经网络为研究本地学习提供了有价值的,可解释的工具.
  • 这种方法有助于更好地理解地方动态如何为网络层面的解决方案做出贡献.
  • 该框架可以适应各种学习任务和网络结构.