Metabolic brain networks in neurodegenerative disorders: a functional imaging approach

被引：300

作者：

Eidelberg, David ^{[1
,2
,3
,4
]}

机构：

[1] N Shore LIJ Hlth Syst, Feinstein Inst Med Res, Ctr Neurosci, Manhasset, NY USA

[2] N Shore Univ Hosp, Dept Neurol, Manhasset, NY USA

[3] N Shore Univ Hosp, Dept Med, Manhasset, NY USA

[4] NYU, Sch Med, Manhasset, NY USA

来源：

TRENDS IN NEUROSCIENCES | 2009年 / 32卷 / 10期

关键词：

MILD COGNITIVE IMPAIRMENT; PARKINSONS-DISEASE; SUBTHALAMIC NUCLEUS; ALZHEIMERS-DISEASE; STATISTICAL LIMITATIONS; DIFFERENTIAL-DIAGNOSIS; GLUCOSE-METABOLISM; GENE-THERAPY; MULTIVARIATE; STIMULATION;

D O I：

10.1016/j.tins.2009.06.003

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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.

引用

页码：548 / 557

页数：10

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