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

Exponential and Sinusoidal Signals01:18

Exponential and Sinusoidal Signals

262
The exponential function is crucial for characterizing waveforms that rise and decay rapidly. This continuous-time exponential function is defined using exponential terms with constants α and A. When both constants are real, the function is represented as,
262
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

495
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
495
Exponential Fourier series01:24

Exponential Fourier series

202
In audio signal processing, the exponential Fourier series plays a crucial role in sound synthesis, allowing complex sounds to be broken down into simpler sinusoidal components. This decomposition process is fundamental in analyzing and reconstructing musical notes and other audio signals. The exponential Fourier series expresses periodic signals as the sum of complex exponentials at both positive and negative harmonic frequencies, providing a powerful tool for signal analysis.
Euler's identity...
202
Propagation of Action Potentials01:23

Propagation of Action Potentials

5.7K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
5.7K
Properties of DTFT II01:24

Properties of DTFT II

198
In the study of discrete-time signal processing, understanding the properties of the Discrete-Time Fourier Transform (DTFT) is crucial for analyzing and manipulating signals in the frequency domain. Several properties, including frequency differentiation, convolution, accumulation, and Parseval's relation, offer powerful tools for signal analysis.
The frequency differentiation property is illustrated by considering a DTFT pair and differentiating both sides with respect to ω.
198
Action Potential01:31

Action Potential

7.9K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they...
7.9K

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

Node persistence from topological data analysis reveals changes in brain functional connectivity.

Patterns (New York, N.Y.)·2026
Same author

Graph entropy, degree assortativity, and hierarchical structures in networks.

Physical review. E·2026
Same author

Effect of diversity distribution symmetry on global oscillations of networks of excitable units.

Physical review. E·2025
Same author

Dynamical equivalence between resonant translocation of a polymer chain and diversity-induced resonance.

Chaos (Woodbury, N.Y.)·2025
Same author

Impact of symmetry in local learning rules on predictive neural representations and generalization in spatial navigation.

PLoS computational biology·2025
Same author

An informed deep learning model of the Omicron wave and the impact of vaccination.

Computers in biology and medicine·2025
Same journal

From episodes to populations: evolutionary explanation requires a constructive epistemology.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

Cortical neuron classes and recursive curvature collapse: a neurobiological model of conscious dynamics.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

On model of weight gain of farm animals.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

An investigative network analysis mapping global cancer epidemiology.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

The challenge of distinguishing living from non-living entities.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

Red fescue (Festuca rubra L.) variety recognition using subset division and neural networks.

Theory in biosciences = Theorie in den Biowissenschaften·2026
查看所有相关文章

相关实验视频

Updated: Jul 1, 2025

External Excitation of Neurons Using Electric and Magnetic Fields in One- and Two-dimensional Cultures
08:32

External Excitation of Neurons Using Electric and Magnetic Fields in One- and Two-dimensional Cultures

Published on: May 7, 2017

13.4K

神经场的动力学与指数式时间内核的神经场.

Elham Shamsara1, Marius E Yamakou2, Fatihcan M Atay3

  • 1Methods in Medical Informatics, Department of Computer Science, University of Tübingen, 72076, Tübingen, Germany.

Theory in biosciences = Theorie in den Biowissenschaften
|March 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究表明神经场中的指数式时间内核可以防止静态分叉,但可以实现动态分叉,如图灵-霍夫分叉,产生移动波并计算神经记忆.

关键词:
分支分析的分析.指数时间内核指数时间内核.泄漏情况 泄漏情况神经领域的神经场.时间空间的模式.传输延迟导致传输延迟.

更多相关视频

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent
08:31

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

Published on: November 30, 2017

12.3K
Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

9.9K

相关实验视频

Last Updated: Jul 1, 2025

External Excitation of Neurons Using Electric and Magnetic Fields in One- and Two-dimensional Cultures
08:32

External Excitation of Neurons Using Electric and Magnetic Fields in One- and Two-dimensional Cultures

Published on: May 7, 2017

13.4K
Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent
08:31

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

Published on: November 30, 2017

12.3K
Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

9.9K

科学领域:

  • 计算神经科学是一种计算神经科学.
  • 数学生物学的数学生物学
  • 动态系统理论 动态系统理论

背景情况:

  • 神经场方程模拟大规模的大脑活动.
  • 时间内核会随着时间的推移塑造神经信号的整合.
  • 了解分叉揭示了模式形成机制.

研究的目的:

  • 分析神经场中的分叉与指数式时间内核.
  • 调查静态和动态模式的形成.
  • 描述新出现的时空波浪模式.

主要方法:

  • 分析时间独立的 (静态) 两叉.
  • 时间依赖 (动态) 两叉的分析.
  • 使用核系数,传输速度,突触延迟和激发抑制比率等参数进行分叉分析.

主要成果:

  • 指数式时间内核排除了静态分叉 (马节点,叉,图灵).
  • 这些内核捕获有限的神经记忆,与格林的函数不同.
  • 动态分叉分析为霍普和图灵-霍普分叉产生了明确的条件.
  • 图灵-霍普夫分叉产生空间和时间复杂的解决方案,包括移动的波.

结论:

  • 指数式时间内核支持动态模式形成,这对于神经计算至关重要.
  • 该模型通过图灵-霍夫分叉预测波浪的移动.
  • 有限神经内存是这种内核类型启用的关键功能.