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

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...

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

Flexible Gravitational-Wave Parameter Estimation with Transformers.

Physical review letters·2026
Same author

Neural timescales from a computational perspective.

Nature neuroscience·2026
Same author

Corrigendum to "Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes" [Medical Image Analysis 103 (2025) 103580].

Medical image analysis·2026
Same author

EDAPT: towards calibration-free BCIs with continual online adaptation.

Journal of neural engineering·2026
Same author

JAXLEY: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics.

Nature methods·2025
Same author

Simulation-based inference for subject-specific tuning of middle ear finite-element models towards personalized objective diagnosis.

Scientific reports·2025

相关实验视频

Updated: Jul 11, 2026

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
07:41

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

9.9K

产生现实的神经生理学时间序列,与无声的扩散概率模型.

Julius Vetter1, Jakob H Macke1,2, Richard Gao1

  • 1Machine Learning in Science, University of Tübingen and Tübingen AI Center, Tübingen, Germany.

Patterns (New York, N.Y.)
|November 21, 2024
PubMed
概括

否认扩散概率模型 (DDPMs) 现在可以生成现实的神经生理学数据. 这一进步为神经科学研究提供了新的工具,改善了数据分析和合成数据生成.

科学领域:

  • 神经科学是一个神经科学.
  • 机器学习 机器学习
  • 信号处理 信号处理

背景情况:

  • 否定扩散概率模型 (DDPMs) 擅长生成像图像和音频这样的复杂数据.
  • 精确生成神经生理时间序列对于推进神经科学应用至关重要.

研究的目的:

  • 提出一种基于DDPM的灵活方法,用于建模多通道,密集采样的神经生理记录.
  • 为了证明DDPMs在生成现实的合成神经生理学数据方面的实用性.

主要方法:

  • 开发了一种基于DDPM的方法,适用于多通道神经生理记录.
  • 在不同物种和记录技术的不同数据集上验证了模型.

主要成果:

  • DDPM成功地生成了合成神经生理数据,捕获了关键统计数据 (例如频谱,相振幅合) 和细粒度特征 (例如尖的波浪浪).
  • 生成的数据反映了实验条件.
  • 在大脑状态分类和缺失数据归算中展示了应用.

结论:

  • DDPMs为神经生理记录提供了一个准确的生成建模框架.
  • 该方法在神经科学研究中对合成数据的概率生成具有广泛的实用性.
关键词:
计算神经科学是一种神经科学.扩散模型的扩散模型生成式建模生成式建模机器学习是机器学习.神经生理记录 神经生理记录

更多相关视频

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K
Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.1K

相关实验视频

Last Updated: Jul 11, 2026

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
07:41

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

9.9K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K
Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.1K