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

Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

9.9K
Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
9.9K

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

Stability and neurophysiological validity of graph connectivity features for non-stationary motor imagery BCIs.

Journal of neural engineering·2026
Same author

But do we need high bandwidth? Applications and scaling challenges of invasive brain-computer interfaces.

Journal of neural engineering·2026
Same author

Capacitive Sensors for Label-Free Detection in High-Ionic-Strength Bodily Fluids: A Review.

Biosensors·2025
Same author

A multi-channel stimulator with an active electrode array implant for vagal-cardiac neuromodulation studies.

Bioelectronic medicine·2024
Same author

DualSort: online spike sorting with a running neural network.

Journal of neural engineering·2023
Same author

Dictionary selection for compressed sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning.

Biomedical physics & engineering express·2022
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
Same journal

Online decoding of rat self-paced locomotion speed from EEG using recurrent neural networks.

Journal of neural engineering·2026
Same journal

The seizure embedding map: A spatio-temporal transformer for comparing patients by ictal intracranial EEG features at scale.

Journal of neural engineering·2026
Same journal

Decoding imagined Chinese speech: A capsule neural network based on bidirectional knowledge transfer for hierarchical multi-label classification.

Journal of neural engineering·2026
查看所有相关文章

相关实验视频

Updated: May 4, 2026

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

基于深度学习的尖端分类:一项调查调查.

Luca M Meyer1, Majid Zamani2, János Rokai3

  • 1Currently not Affiliated with any Institution, Wiesbaden, Germany.

Journal of neural engineering
|October 25, 2024
PubMed
概括
此摘要是机器生成的。

本调查回顾了神经科学中尖端分类的深度学习方法,突出了卷积神经网络和自动编码器,以改进神经活动分析. 它提供了对最先进的技术和神经信号处理的潜在未来方向的洞察.

关键词:
深度学习是一种深度学习.功能提取 特性提取神经网络的神经网络的神经网络尖峰的分类是指尖峰的分类.尖刺检测探测器可以检测到.尖刺分类 分类.

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

10.3K
A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

11.0K

相关实验视频

Last Updated: May 4, 2026

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
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

10.3K
A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

11.0K

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.
  • 机器学习 机器学习

背景情况:

  • 深度学习越来越多地应用于神经科学信号处理,特别是细胞外记录.
  • 尖端分类对于从人口记录中分配动作潜力 (尖端) 到个别神经元至关重要.

研究的目的:

  • 从最近的基于深度学习的尖端分类方法学中批判性地综合发现.
  • 提供当前最先进的方法,方法和结果的深入评估.

主要方法:

  • 审查了2023年12月之前发表的基于深度学习的尖端分类的24篇文章.
  • 将方法分类为尖峰检测,特征提取和分类,包括集成系统.

主要成果:

  • 多道数据模型显示出有前途,具有高效的硬件实现.
  • 卷积神经网络在尖端检测和分类方面表现出色,这是由于时空处理.
  • 自动编码器用于减小维度,集成系统提供端到端解决方案.

结论:

  • 深度神经网络在解决尖端分类挑战方面显示出显著的潜力.
  • 该调查强调了模型的能力和潜在的偏见,作为研究人员的资源.
  • 这项工作旨在激发神经信号处理深度学习的未来发展.