Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis
Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis
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DOI：
10.1109/tip.2022.3159125
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发表时间：
2022-05
影响因子：
10.6
通讯作者：
Paris A. Karakasis;A. Liavas;N. Sidiropoulos;P. Simos;E. Papadaki
中科院分区：
文献类型：
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作者：
Paris A. Karakasis;A. Liavas;N. Sidiropoulos;P. Simos;E. Papadaki
功能性磁共振成像（fMRI）是研究人类大脑的最流行的方法之一。与任务相关的功能磁共振成像数据处理旨在确定当执行特定任务时哪些大脑区域被激活，并且通常基于血氧水平依赖（BOLD）信号。背景BOLD信号还反映了区域大脑活动的系统性波动，这归因于静息态大脑网络的存在。我们提出了一个新的功能磁共振成像数据生成模型，该模型考虑到存在共同的任务相关和静息态组件。我们首先估计共同的任务相关的时间分量，通过两个连续阶段的广义典型相关分析，然后，我们估计共同的任务相关的空间分量，导致任务相关的激活地图。我们的方法与合成数据的实验测试表明，我们能够获得非常准确的时间和空间的估计，即使在非常低的信噪比（SNR），这是通常的情况下，在fMRI数据处理。与基于一般线性模型（GLM）的标准程序相比，真实世界的功能磁共振成像数据的测试显示出显着的优势。
Functional magnetic resonance imaging (fMRI) is one of the most popular methods for studying the human brain. Task-related fMRI data processing aims to determine which brain areas are activated when a specific task is performed and is usually based on the Blood Oxygen Level Dependent (BOLD) signal. The background BOLD signal also reflects systematic fluctuations in regional brain activity which are attributed to the existence of resting-state brain networks. We propose a new fMRI data generating model which takes into consideration the existence of common task-related and resting-state components. We first estimate the common task-related temporal component, via two successive stages of generalized canonical correlation analysis and, then, we estimate the common task-related spatial component, leading to a task-related activation map. The experimental tests of our method with synthetic data reveal that we are able to obtain very accurate temporal and spatial estimates even at very low Signal to Noise Ratio (SNR), which is usually the case in fMRI data processing. The tests with real-world fMRI data show significant advantages over standard procedures based on General Linear Models (GLMs).