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

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

2.8K
2.8K
Steps in the Modeling Process01:14

Steps in the Modeling Process

202
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
202
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

53
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
53

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

Human hippocampal ripples tune cortical responses based on predicted uncertainty.

Nature neuroscience·2026
Same author

Testing and tracking in the UK: A dynamic causal modelling study.

Wellcome open research·2026
Same author

The evolutionary and organizational bases of active affordance.

Cerebral cortex (New York, N.Y. : 1991)·2026
Same author

Functional neuroanatomy of musical object processing in Alzheimer's disease and frontotemporal dementia.

Brain communications·2026
Same author

The methodological foundations of lesion network mapping remain sound.

bioRxiv : the preprint server for biology·2026
Same author

Protocol for investigating the warping of spatial experience across the blind spot to contrast predictions of the Integrated Information Theory and Predictive Processing accounts of consciousness.

PloS one·2026
Same journal

Cortical similarity networks in the rat brain: Postnatal development and sensitivity to early life stress.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Increased sensitivity in identifying language-related functional connectivity using jackknife resampling analyses.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Phase-dependent stimulation response is shaped by the brain's dynamic functional connectivity.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Restoring oscillatory dynamics in Alzheimer's disease: A laminar whole-brain model of serotonergic psychedelic effects.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Distributed cortical network dynamics of binocular convergent eye movements in humans.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

High-resolution Bayesian Virtual Epileptic Patient using neural field models.

Network neuroscience (Cambridge, Mass.)·2026
查看所有相关文章

相关实验视频

Updated: Jun 29, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K

快速和缓慢地链接:生成模型的情况

Johan Medrano1, Karl Friston1, Peter Zeidman1

  • 1The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK.

Network neuroscience (Cambridge, Mass.)
|April 2, 2024
PubMed
概括
此摘要是机器生成的。

神经科学研究现在可以分析大脑活动的数毫秒到几年的时间. 层次模型和贝叶斯推理揭示了潜在的大脑机制,而不仅仅是相关性.

关键词:
贝叶斯统计学 贝叶斯统计学动态系统是动态系统.生成型模型是一种生成型模型.隐藏的马尔科夫模型层次化的建模模型.时间尺度是时间尺度.

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

9.9K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.9K

相关实验视频

Last Updated: Jun 29, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K
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

9.9K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.9K

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.
  • 复杂系统建模 复杂系统建模

背景情况:

  • 分析随着时间的推移神经元连接的变化是神经科学的一个关键挑战.
  • 记录技术的进步允许更长时间,更自然的神经元数据采集.
  • 了解自我组织的大脑需要连接不同时间尺度的方法.

研究的目的:

  • 为了证明等级生成模型和贝叶斯推理如何在多个时间尺度上描述神经元活动.
  • 提供状态空间建模概念的概述和这些方法的分类学.
  • 介绍时间尺度分离的数学原理,并审查测试假设的贝叶斯方法.

主要方法:

  • 层次化的生成模型.
  • 贝叶斯的推理 贝叶斯的推理
  • 国家空间建模.
  • 这就是奴役原则.

主要成果:

  • 层次模型和贝叶斯推理使得我们能够推断底层神经元机制.
  • 这些方法将神经元动态连接在几毫秒到几年的时间.
  • 这篇评论为分析多尺度大脑数据提供了一个框架.

结论:

  • 层次生成模型和贝叶斯推理是理解神经元连接变化的强大工具.
  • 这些方法超越了统计学关联,转向了机械推理.
  • 这篇评论作为神经科学家在多尺度数据分析技术的入门书.