神经退行性疾病中的代谢脑网络：一种功能成像方法。
Metabolic brain networks in neurodegenerative disorders: a functional imaging approach.
作者信息
Eidelberg David
机构信息
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-LIJ Health System, Manhasset, NY, USA.
出版信息
Trends Neurosci. 2009 Oct;32(10):548-57. doi: 10.1016/j.tins.2009.06.003. Epub 2009 Sep 16.
Abstract
Network analysis of functional brain imaging data is an innovative approach to study circuit abnormalities in neurodegenerative diseases. In Parkinson's disease, spatial covariance analysis of resting-state metabolic images has identified specific regional patterns associated with motor and cognitive symptoms. With functional imaging, these metabolic networks have recently been used to measure system-related progression and to evaluate novel treatment strategies. Network analysis is also being used to characterize specific functional biomarkers for Huntington's disease and Alzheimer's disease. These networks have been particularly helpful in uncovering compensatory mechanisms in genetically at-risk individuals. Ongoing developments in network applications are likely to enhance the role of functional imaging in the investigation of neurodegenerative disorders.
摘要
对功能性脑成像数据进行网络分析是研究神经退行性疾病中神经回路异常的一种创新方法。在帕金森病中，静息态代谢图像的空间协方差分析已经确定了与运动和认知症状相关的特定区域模式。借助功能成像，这些代谢网络最近已被用于测量与系统相关的进展情况并评估新的治疗策略。网络分析也正被用于确定亨廷顿舞蹈病和阿尔茨海默病的特定功能生物标志物。这些网络在揭示有遗传风险个体的代偿机制方面特别有帮助。网络应用的不断发展可能会增强功能成像在神经退行性疾病研究中的作用。
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