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

Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

2.8K
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
2.8K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

5.5K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
5.5K
Neural Circuits01:25

Neural Circuits

3.0K
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...
3.0K
Neuroplasticity01:01

Neuroplasticity

2.1K
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
2.1K
Neural Regulation01:37

Neural Regulation

43.8K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
43.8K

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

Closed-form feedback-free learning with forward projection.

Nature communications·2026
Same author

Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.

Brain communications·2024
Same author

Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks.

Entropy (Basel, Switzerland)·2024
Same author

Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction.

IEEE transactions on pattern analysis and machine intelligence·2023
Same author

Blind Source Separation of Intermittent Frequency Hopping Sources over LOS and NLOS Channels.

Entropy (Basel, Switzerland)·2023
Same author

Robust PAC<sub>m</sub>: Training Ensemble Models Under Misspecification and Outliers.

IEEE transactions on neural networks and learning systems·2023
Same journal

Inverse FIP effect plasma in the solar atmosphere: a synthesis of current understanding and new insights from AR 11967.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Signs of sulfur fractionation under high magnetic field strength.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

First ionization potential fractionation of sulfur observed with spectral imaging of the coronal environment.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Chromospheric dynamics and turbulence regulate the solar FIP effect.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Exploring the link between wave activity in the photospheric velocity driver and the FIP bias in the solar corona.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Radiative hydrodynamic simulations of first ionization potential fractionation in solar flares.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
查看所有相关文章

相关实验视频

Updated: Mar 2, 2026

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

10.9K

通过神经形态原理实现高效可靠的人工智能.

Bipin Rajendran1, Osvaldo Simeone1, Bashir Al-Hashimi2

  • 1Northeastern University London , London, UK.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
|February 28, 2026
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 需要超越大型神经网络的新原则来提高效率和可靠性. 采用由大脑启发的神经形态工程概念可以导致可持续的AI发展.

关键词:
6G 6G是什么意思深度学习是一种深度学习.神经形态计算的神经形态计算量子机器学习就是量子机器学习.不确定性量化不确定性量化

更多相关视频

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

8.4K
A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
09:13

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Published on: May 3, 2012

14.9K

相关实验视频

Last Updated: Mar 2, 2026

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

10.9K
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

8.4K
A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
09:13

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Published on: May 3, 2012

14.9K

科学领域:

  • 人工智能的人工智能
  • 神经形态工程的神经形态工程
  • 可持续的计算 可持续的计算

背景情况:

  • 目前的人工智能依赖于在GPU上训练的大型神经网络,导致高成本和能源使用.
  • 这种以硬件为中心的方法有风险偏爱适合当前硬件的算法,而不是内在优越的算法.
  • 现有的AI模型往往缺乏可靠性,无法量化不确定性并产生自信的不正确输出.

研究的目的:

  • 建议从当前的人工智能范式转向更高效,更可靠的系统.
  • 概述未来人工智能设计的关键神经形态工程原理.
  • 探索大脑启发的计算如何解决当前AI的局限性.

主要方法:

  • 讨论六个核心的神经形态原理:状态的反复模型,极端的动态稀疏性,无反向传播的学习,概率决策,内存计算和硬件软件联合设计.
  • 对每个主要领域的相关先前研究进行调查.
  • 确定未来的研究方向.

主要成果:

  • 确定适用于AI算法,架构和硬件的六个关键神经形态原则.
  • 这些原则有潜力指导开发更高效,可靠和可持续的AI系统.
  • 强调神经形态工程与人工智能进步之间的协同作用.

结论:

  • 实现高效可靠的人工智能需要采用神经形态原则.
  • 由大脑启发的计算为克服当前人工智能扩展的局限性提供了一条道路.
  • 未来的人工智能开发应该整合由神经科学为基础的算法,架构和硬件共同设计.