随机性
静息状态功能磁共振成像
功能磁共振成像
功能连接
计算机科学
通信噪声
信号(编程语言)
噪音(视频)
人工智能
模式识别(心理学)
神经科学
数学
心理学
统计
图像(数学)
程序设计语言
语言学
哲学
作者
Victor M. Vergara,Vince D. Calhoun
标识
DOI:10.1109/embc.2016.7591987
摘要
Separate brain regions exhibit synchronous intrinsic activity used to assess connectivity patterns known to appear among brain areas. Connectivity is evaluated from functional magnetic resonance imaging (fMRI) measuring the blood oxygen level dependent signal (BOLD) signal. Extensive research has revealed a distinctive pattern of connectivity among brain areas that can be visualized through a functional connectivity matrix (FCM) matrix. As in any measurement, BOLD signals are subject to contamination from noise and nuisances unrelated to brain's intrinsic activity. Up until now, little work has been developed to determine if patterns observed in FCMs occurred by chance or were driven by a more deterministic process. This work proposes a mathematical framework to test the randomness of FCM connectivity patterns in a systematic and statistical way. A cohort of 121 healthy controls is used to demonstrate the usefulness of the proposed framework. Results indicate that particular parts of the brain might exhibit decreasing randomness with age and gender. Results also show the framework's effectiveness in assessing FCM randomness.
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