Spontaneous Low-Frequency Fluctuation Observed with Functional Magnetic Resonance Imaging as a Potential Biomarker in Neuropsychiatric Disorders
As functional magnetic resonance imaging (fMRI) studies have yielded increasing amounts of information about the brains spontaneous activity, they have revealed fMRFs potential to locate changes in brain hemodynamics in neuropsychiatric disorders. In this paper, we review studies that support the notion that changes in spontaneous low-frequency fluctuation (SLFF) observed by fMRI can be used as potential biomarkers for diagnosis and treatment evaluation in neuropsychiatric disorders. In this paper, we review the methods used to study SLFF from individual region of interest analysis, to local network analysis, to whole brain network analysis. We also summarize the major findings associated with major neurological and psychiatric disorders obtained using these methods.
Resting-state fMRI Low frequency fluctuation Functional connectivity ICA Alzheimers disease Schizophrenia
Yuan Zhou Kun Wang Yong Liu Ming Song Sonya W. Song Tianzi Jiang
National Laboratory of Pattern Recognition, LIAMA Center for Computational Medicine, Institute of Automation, Chinese Academy of Sciences, Beijing, PR. China
国际会议
The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)
杭州
英文
47-60
2009-11-15（万方平台首次上网日期，不代表论文的发表时间）