林秋华

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:信息与通信工程学院

学科:信号与信息处理

联系方式:84706002-3326; 84706697

电子邮箱:qhlin@dlut.edu.cn

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Spatial source phase: A new feature for identifying spatial differences based on complex-valued resting-state fMRI data

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论文类型:期刊论文

发表时间:2019-06-15

发表刊物:HUMAN BRAIN MAPPING

收录刊物:PubMed、SCIE

卷号:40

期号:9

页面范围:2662-2676

ISSN号:1065-9471

关键字:auditory cortex; complex-valued fMRI data; default mode network; independent component analysis; resting-state fMRI data; schizophrenia; spatial source phase

摘要:Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data-driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex-valued resting-state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post-ICA phase de-ambiguity and denoising are then performed. The ability of spatial source phase to characterize spatial differences is examined by the homogeneity of variance test (voxel-wise F-test) with false discovery rate correction. Resampling techniques are performed to ensure that the observations are significant and reliable. We focus on two components of interest widely used in analyzing SZs, including the default mode network (DMN) and auditory cortex. Results show that the spatial source phase exhibits more significant variance changes and higher sensitivity to the spatial differences between SZs and HCs in the anterior areas of DMN and the left auditory cortex, compared to the magnitude of spatial activations. Our findings show that the spatial source phase can potentially serve as a new brain imaging biomarker and provide a novel perspective on differences in SZs compared to HCs, consistent with but extending previous work showing increased variability in patient data.