计算机科学
窗口(计算)
滑动窗口协议
交叉口(航空)
算法
动态功能连接
能量(信号处理)
模式识别(心理学)
人工智能
数学
功能连接
统计
神经科学
工程类
生物
航空航天工程
操作系统
作者
Zoran Šverko,Saša Vlahinić,Nino Stojković,Ivan Markovinović
标识
DOI:10.1109/ispa58351.2023.10278731
摘要
This study compares methods for analyzing the dynamic functional connectivity of the brain using the imaginary component of the complex Pearson correlation coefficient as the index of functional connectivity. The most commonly used method of analysis using a constant sliding window with predefined narrow and wide window widths was compared to methods that use adaptive window widths for analysis, produced with the relative intersection of confidence intervals algorithm and single-scale time-dependent algorithm. The comparison of methods was done on synthetic signals by calculating the energy estimation error. Additionally, an example of dynamic functional connectivity estimation is provided using real signals.
科研通智能强力驱动
Strongly Powered by AbleSci AI