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

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

A three-component dynamical index of consciousness-related neural organisation.

Biological cybernetics·2026
Same author

Subject-Wise Depression Screening from Eight-Channel Resting-State EEG Using Asymmetry-Aware Spectral Features and Connectivity Ablation.

Sensors (Basel, Switzerland)·2026
Same author

Comparative analysis of energy transfer mechanisms for neural implants.

Frontiers in neuroscience·2024
Same author

Gene cloning and characterization of a novel recombinant 40-kDa heat shock protein from Mesobacillus persicus B48.

World journal of microbiology & biotechnology·2023
Same author

Social distancing enhanced automated optimal design of physical spaces in the wake of the COVID-19 pandemic.

Sustainable cities and society·2021
Same author

The Effectiveness of Image Augmentation in Deep Learning Networks for Detecting COVID-19: A Geometric Transformation Perspective.

Frontiers in medicine·2021

相关实验视频

Updated: May 10, 2025

Author Spotlight: Streamlined Brain and Skull Modeling for Enhanced Neurosurgical Planning in NHP Research
06:33

Author Spotlight: Streamlined Brain and Skull Modeling for Enhanced Neurosurgical Planning in NHP Research

Published on: February 9, 2024

1.0K

脑植入器的神经形态算法:一个审查

Wiktoria Agata Pawlak1, Newton Howard1

  • 1ni2o, Washington, DC, United States.

Frontiers in neuroscience
|April 28, 2025
PubMed
概括

神经形态计算为植入大脑提供了高效的算法. 这篇评论强调了算法进步,旨在推进神经植入物和医疗诊断和机器人等相关领域.

科学领域:

  • 神经科学是一个神经科学.
  • 计算机科学 计算机科学
  • 生物医学工程 生物医学工程

背景情况:

  • 神经形态计算正在成为一种变革性的技术.
  • 目前的研究主要集中在硬件进步上.
  • 对于神经形态系统的算法开发,特别是神经植入物,需要集中注意力.

研究的目的:

  • 审查最近神经形态计算用于脑植入物的算法进展.
  • 探索适合神经形态硬件的神经计算模型.
  • 激发下一代神经植入物和相关应用的开发.

主要方法:

  • 关于神经形态计算中的算法进步的文献评论.
  • 对当前和新兴的神经计算模型的分析.
  • 讨论在神经形态硬件上的潜在实现.

主要成果:

  • 针对神经形态硬件量身定制的算法取得了重大进展.
  • 识别具有提高效率潜力的神经计算模型.
  • 演示算法与传统方法相匹配或超过传统方法的潜力.

结论:

关键词:
生物杂交接口 生物杂交接口植入大脑植入物是为了大脑.大脑与计算机接口 (BCI)数据压缩数据压缩.混合信号设计的设计.神经计算模型是一种神经计算模型.神经形态计算是一种神经形态计算.尖端神经网络 (SNN) 的发展

更多相关视频

Syringe-injectable Mesh Electronics for Stable Chronic Rodent Electrophysiology
09:58

Syringe-injectable Mesh Electronics for Stable Chronic Rodent Electrophysiology

Published on: July 21, 2018

23.0K
Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model
08:11

Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model

Published on: November 19, 2017

11.3K

相关实验视频

Last Updated: May 10, 2025

Author Spotlight: Streamlined Brain and Skull Modeling for Enhanced Neurosurgical Planning in NHP Research
06:33

Author Spotlight: Streamlined Brain and Skull Modeling for Enhanced Neurosurgical Planning in NHP Research

Published on: February 9, 2024

1.0K
Syringe-injectable Mesh Electronics for Stable Chronic Rodent Electrophysiology
09:58

Syringe-injectable Mesh Electronics for Stable Chronic Rodent Electrophysiology

Published on: July 21, 2018

23.0K
Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model
08:11

Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model

Published on: November 19, 2017

11.3K
  • 算法创新对于实现神经形态大脑植入物的潜力至关重要.
  • 先进的算法可以提高神经植入物中的计算效率和性能.
  • 这些进步对医学诊断,机器人技术和未来的神经接口技术都有影响.