相关实验视频

Updated: Jun 3, 2025

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

从活动数据推断皮层神经网络的结构:统计物理方法.

Ho Fai Po1, Akke Mats Houben2,3, Anna-Christina Haeb2,3

  • 1Department of Mathematics, Aston University, Birmingham B4 7ET, United Kingdom.

PNAS nexus
|January 10, 2025
PubMed
概括

研究人员开发了一种新的概率方法,从大脑信号中推断出神经元网络结构和活动. 这种方法准确地预测神经元功能,并优于现有的技术来理解大脑可塑性和学习.

关键词:
生物学神经元网络的推断推断预期最大化算法的算法一般化最大概率概率.运动性 伊辛格模型神经元类型分类分类神经元类型分类

更多相关视频

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

9.4K
Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes10:10

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Published on: October 4, 2018

8.8K

相关概念视频

Action Potential01:31

Action Potential

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...
7.8K